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Sample records for peptides prediction methods

  1. Method for predicting peptide detection in mass spectrometry

    DOEpatents

    Kangas, Lars [West Richland, WA; Smith, Richard D [Richland, WA; Petritis, Konstantinos [Richland, WA

    2010-07-13

    A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.

  2. Improved Methods for Classification, Prediction and Design of Antimicrobial Peptides

    PubMed Central

    Wang, Guangshun

    2015-01-01

    Peptides with diverse amino acid sequences, structures and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search and mining, but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database (http://aps.unmc.edu/AP) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or anti-oxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi or parasites. This comprehensive AMP database is a useful tool for both research and education. PMID:25555720

  3. Improved methods for classification, prediction, and design of antimicrobial peptides.

    PubMed

    Wang, Guangshun

    2015-01-01

    Peptides with diverse amino acid sequences, structures, and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search, and mining but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database ( http://aps.unmc.edu/AP ) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or antioxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi, or parasites. This comprehensive AMP database is a useful tool for both research and education.

  4. Method for enhanced accuracy in predicting peptides using liquid separations or chromatography

    DOEpatents

    Kangas, Lars J.; Auberry, Kenneth J.; Anderson, Gordon A.; Smith, Richard D.

    2006-11-14

    A method for predicting the elution time of a peptide in chromatographic and electrophoretic separations by first providing a data set of known elution times of known peptides, then creating a plurality of vectors, each vector having a plurality of dimensions, and each dimension representing the elution time of amino acids present in each of these known peptides from the data set. The elution time of any protein is then be predicted by first creating a vector by assigning dimensional values for the elution time of amino acids of at least one hypothetical peptide and then calculating a predicted elution time for the vector by performing a multivariate regression of the dimensional values of the hypothetical peptide using the dimensional values of the known peptides. Preferably, the multivariate regression is accomplished by the use of an artificial neural network and the elution times are first normalized using a transfer function.

  5. [A plain method of prediction of visibility of peptides in mass spectrometry with electrospray ionization].

    PubMed

    Rybina, A V; Skvortsov, V S; Kopylov, A T; Zgoda, V G

    2014-01-01

    A new method for screening of essential peptides for protein detection and quantification analysis in the direct positive electrospray mass spectrometry has been proposed. Our method is based on the prediction of the normalized abundance of the mass spectrometric peaks using a linear regression model. This method has the following limitations: (i) selected peptides should be taken so that at pH 2.5 the tested peptides must be presented mainly as the 2+ and 3+ ions; (ii) only peptides having C-terminal lysine or arginine residues are considered. The amino acid composition of the peptide, the peptide concentration, the ratio of the polar surface of peptide to common surface and ratio of the polar volume to common volume are used as independent variables in equation. Several combinations of variables were considered and the best linear regression model had a determination coefficient in leave-one-out validation procedure equal 0.54. This model confidently discriminates peptides with high response ability and peptides with low response ability, and therefore it allows to select only the most promising peptides. This screening method, a plain and fast, can be successfully applied to reduce the list of observed peptides.

  6. A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins

    PubMed Central

    Tsolis, Antonios C.; Papandreou, Nikos C.; Iconomidou, Vassiliki A.; Hamodrakas, Stavros J.

    2013-01-01

    The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/‘aggregation-prone’ peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins). PMID:23326595

  7. Molecular dynamics methods to predict peptide locations in membranes: LAH4 as a stringent test case.

    PubMed

    Farrotti, A; Bocchinfuso, G; Palleschi, A; Rosato, N; Salnikov, E S; Voievoda, N; Bechinger, B; Stella, L

    2015-02-01

    Determining the structure of membrane-active peptides inside lipid bilayers is essential to understand their mechanism of action. Molecular dynamics simulations can easily provide atomistic details, but need experimental validation. We assessed the reliability of self-assembling (or "minimum-bias") and potential of mean force (PMF) approaches, using all-atom (AA) and coarse-grained (CG) force-fields. The LAH4 peptide was selected as a stringent test case, since it is known to attain different orientations depending on the protonation state of its four histidine residues. In all simulations the histidine side-chains inserted in the membrane when neutral, while they interacted with phospholipid headgroups in their charged state. This led to transmembrane orientations for neutral-His LAH4 in all minimum-bias AA simulations and in most CG trajectories. By contrast, the charged-His peptide stabilized membrane defects in AA simulations, whereas it was located at the membrane surface in some CG trajectories, and interacted with both lipid leaflets in others. This behavior is consistent with the higher antimicrobial activity and membrane-permeabilizing behavior of the charged-His LAH4. In addition, good agreement with solid-state NMR orientational data was observed in AA simulations. PMF calculations correctly predicted a higher membrane affinity for the neutral-His peptide. Interestingly, the structures and relative populations of PMF local free-energy minima corresponded to those determined in the less computationally demanding minimum-bias simulations. These data provide an indication about the possible membrane-perturbation mechanism of the charged-His LAH4 peptide: by interacting with lipid headgroups of both leaflets through its cationic side-chains, it could favor membrane defects and facilitate translocation across the bilayer. PMID:25445672

  8. Predicting protein-peptide interactions from scratch

    NASA Astrophysics Data System (ADS)

    Yan, Chengfei; Xu, Xianjin; Zou, Xiaoqin; Zou lab Team

    Protein-peptide interactions play an important role in many cellular processes. The ability to predict protein-peptide complex structures is valuable for mechanistic investigation and therapeutic development. Due to the high flexibility of peptides and lack of templates for homologous modeling, predicting protein-peptide complex structures is extremely challenging. Recently, we have developed a novel docking framework for protein-peptide structure prediction. Specifically, given the sequence of a peptide and a 3D structure of the protein, initial conformations of the peptide are built through protein threading. Then, the peptide is globally and flexibly docked onto the protein using a novel iterative approach. Finally, the sampled modes are scored and ranked by a statistical potential-based energy scoring function that was derived for protein-peptide interactions from statistical mechanics principles. Our docking methodology has been tested on the Peptidb database and compared with other protein-peptide docking methods. Systematic analysis shows significantly improved results compared to the performances of the existing methods. Our method is computationally efficient and suitable for large-scale applications. Nsf CAREER Award 0953839 (XZ) NIH R01GM109980 (XZ).

  9. Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201.

    PubMed

    Doytchinova, Irini A; Blythe, Martin J; Flower, Darren R

    2002-01-01

    A method has been developed for prediction of binding affinities between proteins and peptides. We exemplify the method through its application to binding predictions of peptides with affinity to major histocompatibility complex class I molecule HLA-A*0201. The method is named "additive" because it is based on the assumption that the binding affinity of a peptide could be presented as a sum of the contributions of the amino acids at each position and the interactions between them. The amino acid contributions and the contributions of the interactions between adjacent side chains and every second side chain were derived using a partial least squares (PLS) statistical methodology using a training set of 420 experimental IC50 values. The predictive power of the method was assessed using rigorous cross-validation and using an independent test set of 89 peptides. The mean value of the residuals between the experimental and predicted pIC50 values was 0.508 for this test set. The additive method was implemented in a program for rapid T-cell epitope search. It is universal and can be applied to any peptide-protein interaction where binding data is known. PMID:12645903

  10. NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data.

    PubMed

    Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole; Buus, Søren; Nielsen, Morten

    2011-01-01

    Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign.

  11. On the hydrophobicity of peptides: Comparing empirical predictions of peptide log P values.

    PubMed

    Thompson, Sarah J; Hattotuwagama, Channa K; Holliday, John D; Flower, Darren R

    2006-01-01

    Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient logP, is useful for the development of predictive Quantitative Structure-Activity Relationships (QSARs). We have investigated the accuracy of available programs for the prediction of logP values for peptides with known experimental values obtained from the literature. Eight prediction programs were tested, of which seven programs were fragment-based methods: XLogP, LogKow, PLogP, ACDLogP, AlogP, Interactive Analysis's LogP and MlogP; and one program used a whole molecule approach: QikProp. The predictive accuracy of the programs was assessed using r(2) values, with ALogP being the most effective (r( 2) = 0.822) and MLogP the least (r(2) = 0.090). We also examined three distinct types of peptide structure: blocked, unblocked, and cyclic. For each study (all peptides, blocked, unblocked and cyclic peptides) the performance of programs rated from best to worse is as follows: all peptides - ALogP, QikProp, PLogP, XLogP, IALogP, LogKow, ACDLogP, and MlogP; blocked peptides - PLogP, XLogP, ACDLogP, IALogP, LogKow, QikProp, ALogP, and MLogP; unblocked peptides - QikProp, IALogP, ALogP, ACDLogP, MLogP, XLogP, LogKow and PLogP; cyclic peptides - LogKow, ALogP, XLogP, MLogP, QikProp, ACDLogP, IALogP. In summary, all programs gave better predictions for blocked peptides, while, in general, logP values for cyclic peptides were under-predicted and those of unblocked peptides were over-predicted. PMID:17597897

  12. Structural prediction of peptides bound to MHC class I.

    PubMed

    Fagerberg, Theres; Cerottini, Jean-Charles; Michielin, Olivier

    2006-02-17

    An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

  13. AVPpred: collection and prediction of highly effective antiviral peptides.

    PubMed

    Thakur, Nishant; Qureshi, Abid; Kumar, Manoj

    2012-07-01

    In the battle against viruses, antiviral peptides (AVPs) had demonstrated the immense potential. Presently, more than 15 peptide-based drugs are in various stages of clinical trials. Emerging and re-emerging viruses further emphasize the efforts to accelerate antiviral drug discovery efforts. Despite, huge importance of the field, no dedicated AVP resource is available. In the present study, we have collected 1245 peptides which were experimentally checked for antiviral activity targeting important human viruses like influenza, HIV, HCV and SARS, etc. After removing redundant peptides, 1056 peptides were divided into 951 training and 105 validation data sets. We have exploited various peptides sequence features, i.e. motifs and alignment followed by amino acid composition and physicochemical properties during 5-fold cross validation using Support Vector Machine. Physiochemical properties-based model achieved maximum 85% accuracy and 0.70 Matthew's Correlation Coefficient (MCC). Performance of this model on the experimental validation data set showed 86% accuracy and 0.71 MCC which is far better than the general antimicrobial peptides prediction methods. Therefore, AVPpred-the first web server for predicting the highly effective AVPs would certainly be helpful to researchers working on peptide-based antiviral development. The web server is freely available at http://crdd.osdd.net/servers/avppred. PMID:22638580

  14. Prediction of Biofilm Inhibiting Peptides: An In silico Approach.

    PubMed

    Gupta, Sudheer; Sharma, Ashok K; Jaiswal, Shubham K; Sharma, Vineet K

    2016-01-01

    Approximately 75% of microbial infections found in humans are caused by microbial biofilms. These biofilms are resistant to host immune system and most of the currently available antibiotics. Small peptides are extensively studied for their role as anti-microbial peptides, however, only a limited studies have shown their potential as inhibitors of biofilm. Therefore, to develop a unique computational method aimed at the prediction of biofilm inhibiting peptides, the experimentally validated biofilm inhibiting peptides sequences were used to extract sequence based features and to identify unique sequence motifs. Biofilm inhibiting peptides were observed to be abundant in positively charged and aromatic amino acids, and also showed selective abundance of some dipeptides and sequence motifs. These individual sequence based features were utilized to construct Support Vector Machine-based prediction models and additionally by including sequence motifs information, the hybrid models were constructed. Using 10-fold cross validation, the hybrid model displayed the accuracy and Matthews Correlation Coefficient (MCC) of 97.83% and 0.87, respectively. On the validation dataset, the hybrid model showed the accuracy and MCC value of 97.19% and 0.84, respectively. The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available freely as web server at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/. PMID:27379078

  15. Prediction of Biofilm Inhibiting Peptides: An In silico Approach

    PubMed Central

    Gupta, Sudheer; Sharma, Ashok K.; Jaiswal, Shubham K.; Sharma, Vineet K.

    2016-01-01

    Approximately 75% of microbial infections found in humans are caused by microbial biofilms. These biofilms are resistant to host immune system and most of the currently available antibiotics. Small peptides are extensively studied for their role as anti-microbial peptides, however, only a limited studies have shown their potential as inhibitors of biofilm. Therefore, to develop a unique computational method aimed at the prediction of biofilm inhibiting peptides, the experimentally validated biofilm inhibiting peptides sequences were used to extract sequence based features and to identify unique sequence motifs. Biofilm inhibiting peptides were observed to be abundant in positively charged and aromatic amino acids, and also showed selective abundance of some dipeptides and sequence motifs. These individual sequence based features were utilized to construct Support Vector Machine-based prediction models and additionally by including sequence motifs information, the hybrid models were constructed. Using 10-fold cross validation, the hybrid model displayed the accuracy and Matthews Correlation Coefficient (MCC) of 97.83% and 0.87, respectively. On the validation dataset, the hybrid model showed the accuracy and MCC value of 97.19% and 0.84, respectively. The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available freely as web server at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/. PMID:27379078

  16. Peptides and methods against diabetes

    DOEpatents

    Albertini, Richard J.; Falta, Michael T.

    2000-01-01

    This invention relates to methods of preventing or reducing the severity of diabetes. In one embodiment, the method involves administering to the individual a peptide having substantially the sequence of a on-conserved region sequence of a T cell receptor present on the surface of T cells mediating diabetes or a fragment thereof, wherein the peptide or fragment is capable of causing an effect on the immune system to regulate the T cells. In particular, the T cell receptor has the V.beta. regional V.beta.6 or V.beta.14. In another embodiment, the method involves gene therapy. The invention also relates to methods of diagnosing diabetes by determining the presence of diabetes predominant T cell receptors.

  17. Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information

    SciTech Connect

    Petritis, Konstantinos; Kangas, Lars J.; Yan, Bo; Monroe, Matthew E.; Strittmatter, Eric F.; Qian, Weijun; Adkins, Joshua N.; Moore, Ronald J.; Xu, Ying; Lipton, Mary S.; Camp, David G.; Smith, Richard D.

    2006-07-15

    We describe an improved artificial neural network (ANN)-based method for predicting peptide retention times in reversed phase liquid chromatography. In addition to the peptide amino acid composition, this study investigated several other peptide descriptors to improve the predictive capability, such as peptide length, sequence, hydrophobicity and hydrophobic moment, and nearest neighbor amino acid, as well as peptide predicted structural configurations (i.e., helix, sheet, coil). An ANN architecture that consisted of 1052 input nodes, 24 hidden nodes, and 1 output node was used to fully consider the amino acid residue sequence in each peptide. The network was trained using {approx}345,000 non-redundant peptides identified from a total of 12,059 LC-MS/MS analyses of more than 20 different organisms, and the predictive capability of the model was tested using 1303 confidently identified peptides that were not included in the training set. The model demonstrated an average elution time precision of {approx}1.5% and was able to distinguish among isomeric peptides based upon the inclusion of peptide sequence information. The prediction power represents a significant improvement over our earlier report (Petritis et al., Anal. Chem. 2003, 75, 1039-1048) and other previously reported models.

  18. Prediction of peptide retention at different HPLC conditions from multiple linear regression models.

    PubMed

    Baczek, Tomasz; Wiczling, Paweł; Marszałł, Michał; Heyden, Yvan Vander; Kaliszan, Roman

    2005-01-01

    To quantitatively characterize the structure of a peptide and to predict its gradient retention time at given HPLC conditions three structural descriptors are used: (i) logarithm of the sum of retention times of the amino acids composing the peptide, log SumAA, (ii) logarithm of the van der Waals volume of the peptide, log VDW(Vol), (iii) and the logarithm of the peptide's calculated n-octanol-water partition coefficient, clog P. The log SumAA descriptor is obtained from empirical data for 20 natural amino acids, determined in a given HPLC system. The two other descriptors are calculated from the peptides' structural formulas using molecular modeling methods. The quantitative structure-retention relationships (QSRR), build by multiple linear regression, describe HPLC retention of peptide on a given chromatographic system on which the retention of the 20 amino acids was predetermined. A structurally diversified series of 98 peptides was employed. The predicted gradient retention times on several chromatographic systems were in good agreement with the experimental data. The QSRR equations, derived for a given system operated at variable gradient times and temperatures allowed for the prediction of peptide retention in that system. Matching the experimental HPLC retention to the theoretically predicted for a presumed peptide could facilitate original protein identification in proteomics. In conjunction with MS data, prediction of the retention time for a given peptide might be used to improve the confidence of peptide identifications and to increase the number of correctly identified peptides.

  19. Predicting protein-ligand and protein-peptide interfaces

    NASA Astrophysics Data System (ADS)

    Bertolazzi, Paola; Guerra, Concettina; Liuzzi, Giampaolo

    2014-06-01

    The paper deals with the identification of binding sites and concentrates on interactions involving small interfaces. In particular we focus our attention on two major interface types, namely protein-ligand and protein-peptide interfaces. As concerns protein-ligand binding site prediction, we classify the most interesting methods and approaches into four main categories: (a) shape-based methods, (b) alignment-based methods, (c) graph-theoretic approaches and (d) machine learning methods. Class (a) encompasses those methods which employ, in some way, geometric information about the protein surface. Methods falling into class (b) address the prediction problem as an alignment problem, i.e. finding protein-ligand atom pairs that occupy spatially equivalent positions. Graph theoretic approaches, class (c), are mainly based on the definition of a particular graph, known as the protein contact graph, and then apply some sophisticated methods from graph theory to discover subgraphs or score similarities for uncovering functional sites. The last class (d) contains those methods that are based on the learn-from-examples paradigm and that are able to take advantage of the large amount of data available on known protein-ligand pairs. As for protein-peptide interfaces, due to the often disordered nature of the regions involved in binding, shape similarity is no longer a determining factor. Then, in geometry-based methods, geometry is accounted for by providing the relative position of the atoms surrounding the peptide residues in known structures. Finally, also for protein-peptide interfaces, we present a classification of some successful machine learning methods. Indeed, they can be categorized in the way adopted to construct the learning examples. In particular, we envisage three main methods: distance functions, structure and potentials and structure alignment.

  20. Predicting peptide binding to MHC pockets via molecular modeling, implicit solvation, and global optimization.

    PubMed

    Schafroth, Heather D; Floudas, Christodoulos A

    2004-02-15

    Development of a computational prediction method based on molecular modeling, global optimization, and implicit solvation has produced accurate structure and relative binding affinity predictions for peptide amino acids binding to five pockets of the MHC molecule HLA-DRB1*0101. Because peptide binding to MHC molecules is essential to many immune responses, development of such a method for understanding and predicting the forces that drive binding is crucial for pharmaceutical design and disease treatment. Underlying the development of this prediction method are two hypotheses. The first is that pockets formed by the peptide binding groove of MHC molecules are independent, separating the prediction of peptide amino acids that bind within individual pockets from those that bind between pockets. The second hypothesis is that the native state of a system composed of an amino acid bound to a protein pocket corresponds to the system's lowest free energy. The prediction method developed from these hypotheses uses atomistic-level modeling, deterministic global optimization, and three methods of implicit solvation: solvent-accessible area, solvent-accessible volume, and Poisson-Boltzmann electrostatics. The method predicts relative binding affinities of peptide amino acids for pockets of HLA-DRB1*0101 by determining computationally an amino acid's global minimum energy conformation. Prediction results from the method are in agreement with X-ray crystallography data and experimental binding assays.

  1. Limitations of Ab Initio Predictions of Peptide Binding to MHC Class II Molecules

    PubMed Central

    Xu, Ying; Sette, Alessandro; Bourne, Philip E.; Lund, Ole; Ponomarenko, Julia; Nielsen, Morten; Peters, Bjoern

    2010-01-01

    Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical potentials derived from the analysis of known protein structures; energetic evaluation of different peptide snapshots in a molecular dynamics simulation; and direct analysis of contacts made in known 3D structures of peptide:MHC complexes. These methods are ab initio in that they require structural data of the MHC molecule examined, but no specific peptide:MHC binding data. Moreover, these methods retain the ability to make predictions in a sufficiently short time scale to be useful in a real world application, such as screening a whole proteome for candidate binding peptides. A rigorous evaluation of each methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results together in order to support the notion that generating structure based predictions of peptide:MHC binding without using binding data is unlikely to give satisfactory results. PMID:20174654

  2. Improved nonlinear prediction method

    NASA Astrophysics Data System (ADS)

    Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

    2014-06-01

    The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

  3. Structural prediction and analysis of VIH-related peptides from selected crustacean species.

    PubMed

    Nagaraju, Ganji Purna Chandra; Kumari, Nunna Siva; Prasad, Ganji Lakshmi Vara; Rajitha, Balney; Meenu, Madan; Rao, Manam Sreenivasa; Naik, Bannoth Reddya

    2009-08-17

    The tentative elucidation of the 3D-structure of vitellogenesis inhibiting hormone (VIH) peptides is conversely underprivileged by difficulties in gaining enough peptide or protein, diffracting crystals, and numerous extra technical aspects. As a result, no structural information is available for VIH peptide sequences registered in the Genbank. In this situation, it is not surprising that predictive methods have achieved great interest. Here, in this study the molt-inhibiting hormone (MIH) of the kuruma prawn (Marsupenaeus japonicus) is used, to predict the structure of four VIHrelated peptides in the crustacean species. The high similarity of the 3D-structures and the calculated physiochemical characteristics of these peptides suggest a common fold for the entire family.

  4. On the Accuracy and Limits of Peptide Fragmentation Spectrum Prediction

    PubMed Central

    Li, Sujun; Arnold, Randy J.; Tang, Haixu; Radivojac, Predrag

    2011-01-01

    We estimated the reproducibility of tandem mass fragmentation spectra for the widely-used collision-induced dissociation (CID) instruments. Using the Pearson correlation coefficient as a measure of spectral similarity, we found that the within-experiment reproducibility of fragment ion intensities is very high (about 0.85). However, across different experiments and instrument types/setups, the correlation decreases by more than 15% (to about 0.70). We further investigated the accuracy of current predictors of peptide fragmentation spectra and found that they are more accurate than the ad-hoc models generally used by search engines (e.g. SEQUEST) and, surprisingly, approaching the empirical upper limit set by the average across-experiment spectral reproducibility (especially for charge +1 and charge +2 precursor ions). These results provide evidence that, in terms of accuracy of modeling, predicted peptide fragmentation spectra provide a viable alternative to spectral libraries for peptide identification, with a higher coverage of peptides and lower storage requirements. Furthermore, using five data sets of proteome digests by two different proteases, we find that PeptideART (a data-driven machine learning approach) is generally more accurate than MassAnalyzer (an approach based on a kinetic model for peptide fragmentation) in predicting fragmentation spectra, but that both models are significantly more accurate than the ad-hoc models. Availability: PeptideART is freely available at www.informatics.indiana.edu/predrag. PMID:21175207

  5. Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes.

    PubMed

    Doytchinova, Irini A; Walshe, Valerie A; Jones, Nicola A; Gloster, Simone E; Borrow, Persephone; Flower, Darren R

    2004-06-15

    The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.

  6. Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes.

    PubMed

    Doytchinova, Irini A; Walshe, Valerie A; Jones, Nicola A; Gloster, Simone E; Borrow, Persephone; Flower, Darren R

    2004-06-15

    The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions. PMID:15187128

  7. Computer-based prediction of mitochondria-targeting peptides.

    PubMed

    Martelli, Pier Luigi; Savojardo, Castrense; Fariselli, Piero; Tasco, Gianluca; Casadio, Rita

    2015-01-01

    Computational methods are invaluable when protein sequences, directly derived from genomic data, need functional and structural annotation. Subcellular localization is a feature necessary for understanding the protein role and the compartment where the mature protein is active and very difficult to characterize experimentally. Mitochondrial proteins encoded on the cytosolic ribosomes carry specific patterns in the precursor sequence from where it is possible to recognize a peptide targeting the protein to its final destination. Here we discuss to which extent it is feasible to develop computational methods for detecting mitochondrial targeting peptides in the precursor sequences and benchmark our and other methods on the human mitochondrial proteins endowed with experimentally characterized targeting peptides. Furthermore, we illustrate our newly implemented web server and its usage on the whole human proteome in order to infer mitochondrial targeting peptides, their cleavage sites, and whether the targeting peptide regions contain or not arginine-rich recurrent motifs. By this, we add some other 2,800 human proteins to the 124 ones already experimentally annotated with a mitochondrial targeting peptide. PMID:25631024

  8. Method of identity analyte-binding peptides

    DOEpatents

    Kauvar, Lawrence M.

    1990-01-01

    A method for affinity chromatography or adsorption of a designated analyte utilizes a paralog as the affinity partner. The immobilized paralog can be used in purification or analysis of the analyte; the paralog can also be used as a substitute for antibody in an immunoassay. The paralog is identified by screening candidate peptide sequences of 4-20 amino acids for specific affinity to the analyte.

  9. Method of identity analyte-binding peptides

    DOEpatents

    Kauvar, L.M.

    1990-10-16

    A method for affinity chromatography or adsorption of a designated analyte utilizes a paralog as the affinity partner. The immobilized paralog can be used in purification or analysis of the analyte; the paralog can also be used as a substitute for antibody in an immunoassay. The paralog is identified by screening candidate peptide sequences of 4--20 amino acids for specific affinity to the analyte. 5 figs.

  10. Extending the coverage of spectral libraries: a neighbor-based approach to predicting intensities of peptide fragmentation spectra.

    PubMed

    Ji, Chao; Arnold, Randy J; Sokoloski, Kevin J; Hardy, Richard W; Tang, Haixu; Radivojac, Predrag

    2013-03-01

    Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well-studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor-based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K-nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20-60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.

  11. Development of Antimicrobial Peptide Prediction Tool for Aquaculture Industries.

    PubMed

    Gautam, Aditi; Sharma, Asuda; Jaiswal, Sarika; Fatma, Samar; Arora, Vasu; Iquebal, M A; Nandi, S; Sundaray, J K; Jayasankar, P; Rai, Anil; Kumar, Dinesh

    2016-09-01

    Microbial diseases in fish, plant, animal and human are rising constantly; thus, discovery of their antidote is imperative. The use of antibiotic in aquaculture further compounds the problem by development of resistance and consequent consumer health risk by bio-magnification. Antimicrobial peptides (AMPs) have been highly promising as natural alternative to chemical antibiotics. Though AMPs are molecules of innate immune defense of all advance eukaryotic organisms, fish being heavily dependent on their innate immune defense has been a good source of AMPs with much wider applicability. Machine learning-based prediction method using wet laboratory-validated fish AMP can accelerate the AMP discovery using available fish genomic and proteomic data. Earlier AMP prediction servers are based on multi-phyla/species data, and we report here the world's first AMP prediction server in fishes. It is freely accessible at http://webapp.cabgrid.res.in/fishamp/ . A total of 151 AMPs related to fish collected from various databases and published literature were taken for this study. For model development and prediction, N-terminus residues, C-terminus residues and full sequences were considered. Best models were with kernels polynomial-2, linear and radial basis function with accuracy of 97, 99 and 97 %, respectively. We found that performance of support vector machine-based models is superior to artificial neural network. This in silico approach can drastically reduce the time and cost of AMP discovery. This accelerated discovery of lead AMP molecules having potential wider applications in diverse area like fish and human health as substitute of antibiotics, immunomodulator, antitumor, vaccine adjuvant and inactivator, and also for packaged food can be of much importance for industries.

  12. Development of Antimicrobial Peptide Prediction Tool for Aquaculture Industries.

    PubMed

    Gautam, Aditi; Sharma, Asuda; Jaiswal, Sarika; Fatma, Samar; Arora, Vasu; Iquebal, M A; Nandi, S; Sundaray, J K; Jayasankar, P; Rai, Anil; Kumar, Dinesh

    2016-09-01

    Microbial diseases in fish, plant, animal and human are rising constantly; thus, discovery of their antidote is imperative. The use of antibiotic in aquaculture further compounds the problem by development of resistance and consequent consumer health risk by bio-magnification. Antimicrobial peptides (AMPs) have been highly promising as natural alternative to chemical antibiotics. Though AMPs are molecules of innate immune defense of all advance eukaryotic organisms, fish being heavily dependent on their innate immune defense has been a good source of AMPs with much wider applicability. Machine learning-based prediction method using wet laboratory-validated fish AMP can accelerate the AMP discovery using available fish genomic and proteomic data. Earlier AMP prediction servers are based on multi-phyla/species data, and we report here the world's first AMP prediction server in fishes. It is freely accessible at http://webapp.cabgrid.res.in/fishamp/ . A total of 151 AMPs related to fish collected from various databases and published literature were taken for this study. For model development and prediction, N-terminus residues, C-terminus residues and full sequences were considered. Best models were with kernels polynomial-2, linear and radial basis function with accuracy of 97, 99 and 97 %, respectively. We found that performance of support vector machine-based models is superior to artificial neural network. This in silico approach can drastically reduce the time and cost of AMP discovery. This accelerated discovery of lead AMP molecules having potential wider applications in diverse area like fish and human health as substitute of antibiotics, immunomodulator, antitumor, vaccine adjuvant and inactivator, and also for packaged food can be of much importance for industries. PMID:27141850

  13. AntiAngioPred: A Server for Prediction of Anti-Angiogenic Peptides.

    PubMed

    Ettayapuram Ramaprasad, Azhagiya Singam; Singh, Sandeep; Gajendra P S, Raghava; Venkatesan, Subramanian

    2015-01-01

    The process of angiogenesis is a vital step towards the formation of malignant tumors. Anti-angiogenic peptides are therefore promising candidates in the treatment of cancer. In this study, we have collected anti-angiogenic peptides from the literature and analyzed the residue preference in these peptides. Residues like Cys, Pro, Ser, Arg, Trp, Thr and Gly are preferred while Ala, Asp, Ile, Leu, Val and Phe are not preferred in these peptides. There is a positional preference of Ser, Pro, Trp and Cys in the N terminal region and Cys, Gly and Arg in the C terminal region of anti-angiogenic peptides. Motif analysis suggests the motifs "CG-G", "TC", "SC", "SP-S", etc., which are highly prominent in anti-angiogenic peptides. Based on the primary analysis, we developed prediction models using different machine learning based methods. The maximum accuracy and MCC for amino acid composition based model is 80.9% and 0.62 respectively. The performance of the models on independent dataset is also reasonable. Based on the above study, we have developed a user-friendly web server named "AntiAngioPred" for the prediction of anti-angiogenic peptides. AntiAngioPred web server is freely accessible at http://clri.res.in/subramanian/tools/antiangiopred/index.html (mirror site: http://crdd.osdd.net/raghava/antiangiopred/). PMID:26335203

  14. Prediction of peptides binding to MHC class I and II alleles by temporal motif mining

    PubMed Central

    2013-01-01

    Background MHC (Major Histocompatibility Complex) is a key player in the immune response of most vertebrates. The computational prediction of whether a given antigenic peptide will bind to a specific MHC allele is important in the development of vaccines for emerging pathogens, the creation of possibilities for controlling immune response, and for the applications of immunotherapy. One of the problems that make this computational prediction difficult is the detection of the binding core region in peptides, coupled with the presence of bulges and loops causing variations in the total sequence length. Most machine learning methods require the sequences to be of the same length to successfully discover the binding motifs, ignoring the length variance in both motif mining and prediction steps. In order to overcome this limitation, we propose the use of time-based motif mining methods that work position-independently. Results The prediction method was tested on a benchmark set of 28 different alleles for MHC class I and 27 different alleles for MHC class II. The obtained results are comparable to the state of the art methods for both MHC classes, surpassing the published results for some alleles. The average prediction AUC values are 0.897 for class I, and 0.858 for class II. Conclusions Temporal motif mining using partial periodic patterns can capture information about the sequences well enough to predict the binding of the peptides and is comparable to state of the art methods in the literature. Unlike neural networks or matrix based predictors, our proposed method does not depend on peptide length and can work with both short and long fragments. This advantage allows better use of the available training data and the prediction of peptides of uncommon lengths. PMID:23368521

  15. Prediction of Surface and pH-Specific Binding of Peptides to Metal and Oxide Nanoparticles

    NASA Astrophysics Data System (ADS)

    Heinz, Hendrik; Lin, Tzu-Jen; Emami, Fateme Sadat; Ramezani-Dakhel, Hadi; Naik, Rajesh; Knecht, Marc; Perry, Carole C.; Huang, Yu

    2015-03-01

    The mechanism of specific peptide adsorption onto metallic and oxidic nanostructures has been elucidated in atomic resolution using novel force fields and surface models in comparison to measurements. As an example, variations in peptide adsorption on Pd and Pt nanoparticles depending on shape, size, and location of peptides on specific bounding facets are explained. Accurate computational predictions of reaction rates in C-C coupling reactions using particle models derived from HE-XRD and PDF data illustrate the utility of computational methods for the rational design of new catalysts. On oxidic nanoparticles such as silica and apatites, it is revealed how changes in pH lead to similarity scores of attracted peptides lower than 20%, supported by appropriate model surfaces and data from adsorption isotherms. The results demonstrate how new computational methods can support the design of nanoparticle carriers for drug release and the understanding of calcification mechanisms in the human body.

  16. Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

    PubMed

    Liu, Yong; Munteanu, Cristian R; Fernández Blanco, Enrique; Tan, Zhiliang; Santos Del Riego, Antonino; Pazos, Alejandro

    2015-11-01

    The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model that is able to predict new nucleotide binding peptides, using only the amino acid sequence. Thus, the methodology uses a Star graph molecular descriptor of the peptide sequences and the Machine Learning technique for the best classifier. The best model represents a Random Forest classifier based on two features of the embedded and non-embedded graphs. The performance of the model is excellent, considering similar models in the field, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.938 and true positive rate (TPR) of 0.886 (test subset). The prediction of new nucleotide binding peptides with this model could be useful for drug target studies in drug development.

  17. Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

    PubMed

    Liu, Yong; Munteanu, Cristian R; Fernández Blanco, Enrique; Tan, Zhiliang; Santos Del Riego, Antonino; Pazos, Alejandro

    2015-11-01

    The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model that is able to predict new nucleotide binding peptides, using only the amino acid sequence. Thus, the methodology uses a Star graph molecular descriptor of the peptide sequences and the Machine Learning technique for the best classifier. The best model represents a Random Forest classifier based on two features of the embedded and non-embedded graphs. The performance of the model is excellent, considering similar models in the field, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.938 and true positive rate (TPR) of 0.886 (test subset). The prediction of new nucleotide binding peptides with this model could be useful for drug target studies in drug development. PMID:27491034

  18. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGESBeta

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; et al

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  19. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    SciTech Connect

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

  20. Predictive spark timing method

    SciTech Connect

    Tang, D.L.; Chang, M.F.; Sultan, M.C.

    1990-01-09

    This patent describes a method of determining spark time in a spark timing system of an internal combustion engine having a plurality of cylinders and a spark period for each cylinder in which a spark occurs. It comprises: generating at least one crankshaft position reference pulse for each spark firing event, the reference pulse nearest the next spark being set to occur within a same cylinder event as the next spark; measuring at least two reference periods between recent reference pulses; calculating the spark timing synchronously with crankshaft position by performing the calculation upon receipt of the reference pulse nearest the next spark; predicting the engine speed for the next spark period from at least two reference periods including the most recent reference period; and based on the predicted speed, calculating a spark time measured from the the reference pulse nearest the next spark.

  1. Motor degradation prediction methods

    SciTech Connect

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.

    1996-12-01

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor`s duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures.

  2. Prediction of Peptide and Protein Propensity for Amyloid Formation.

    PubMed

    Família, Carlos; Dennison, Sarah R; Quintas, Alexandre; Phoenix, David A

    2015-01-01

    Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation. PMID:26241652

  3. Prediction of Peptide and Protein Propensity for Amyloid Formation.

    PubMed

    Família, Carlos; Dennison, Sarah R; Quintas, Alexandre; Phoenix, David A

    2015-01-01

    Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation.

  4. sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides

    PubMed Central

    Luo, Heng; Ye, Hao; Ng, Hui Wen; Sakkiah, Sugunadevi; Mendrick, Donna L.; Hong, Huixiao

    2016-01-01

    Understanding the binding between human leukocyte antigens (HLAs) and peptides is important to understand the functioning of the immune system. Since it is time-consuming and costly to measure the binding between large numbers of HLAs and peptides, computational methods including machine learning models and network approaches have been developed to predict HLA-peptide binding. However, there are several limitations for the existing methods. We developed a network-based algorithm called sNebula to address these limitations. We curated qualitative Class I HLA-peptide binding data and demonstrated the prediction performance of sNebula on this dataset using leave-one-out cross-validation and five-fold cross-validations. This algorithm can predict not only peptides of different lengths and different types of HLAs, but also the peptides or HLAs that have no existing binding data. We believe sNebula is an effective method to predict HLA-peptide binding and thus improve our understanding of the immune system. PMID:27558848

  5. sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides.

    PubMed

    Luo, Heng; Ye, Hao; Ng, Hui Wen; Sakkiah, Sugunadevi; Mendrick, Donna L; Hong, Huixiao

    2016-01-01

    Understanding the binding between human leukocyte antigens (HLAs) and peptides is important to understand the functioning of the immune system. Since it is time-consuming and costly to measure the binding between large numbers of HLAs and peptides, computational methods including machine learning models and network approaches have been developed to predict HLA-peptide binding. However, there are several limitations for the existing methods. We developed a network-based algorithm called sNebula to address these limitations. We curated qualitative Class I HLA-peptide binding data and demonstrated the prediction performance of sNebula on this dataset using leave-one-out cross-validation and five-fold cross-validations. This algorithm can predict not only peptides of different lengths and different types of HLAs, but also the peptides or HLAs that have no existing binding data. We believe sNebula is an effective method to predict HLA-peptide binding and thus improve our understanding of the immune system. PMID:27558848

  6. New method of iodine labelling of peptide hormones

    SciTech Connect

    Escher, E.

    1984-01-01

    Usually peptide hormones and related compounds are radioactively labelled with iodine on tyrosine residues of the peptide. However many peptide hormones do not contain tyrosine or the iodinated tyrosine interferes with the biological properties. In order to circumvent these and other problems, a general method is proposed which allows the introduction of iodine into the para-position of phenylalanine with a modified Sandmeyer procedure. This last-step modification together with HPLC purification permits the obtention of carrier-free and metabolically stable labelled products with maximal specific activity possible. The model has been carried out on several peptide-models like angiotensin II, endorphine and head activator peptide.

  7. Quantitative online prediction of peptide binding to the major histocompatibility complex.

    PubMed

    Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Zygouri, Christianna; Flower, Darren R

    2004-01-01

    With its implications for vaccine discovery, the accurate prediction of T cell epitopes is one of the key aspirations of computational vaccinology. We have developed a robust multivariate statistical method, based on partial least squares, for the quantitative prediction of peptide binding to major histocompatibility complexes (MHC), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available via a World Wide Web server. We call this server MHCPred. Access to the server is freely available from the URL: http://www.jenner.ac.uk/MHCPred. We have exemplified our method with a model for peptides binding to the common human MHC molecule HLA-B*3501. PMID:14629978

  8. Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins.

    PubMed

    Sarkar, Debasree; Patra, Piya; Ghosh, Abhirupa; Saha, Sudipto

    2016-01-01

    A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins-MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators. PMID

  9. Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins

    PubMed Central

    Sarkar, Debasree; Patra, Piya; Ghosh, Abhirupa; Saha, Sudipto

    2016-01-01

    A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins—MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators. PMID

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

    PubMed

    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

  11. Cotton functionalized with peptides: characterization and synthetic methods.

    PubMed

    Orlandin, Andrea; Formaggio, Fernando; Toffoletti, Antonio; Peggion, Cristina

    2014-07-01

    Three approaches for the chemical ligation of peptides to cotton fibers are described and compared. This investigation was encouraged by the need to create peptide-decorated natural textiles, furnished with useful properties (e.g. antimicrobial activity). IR absorption spectroscopy is proved to be an easy and fast method to check the covalent anchorage of a peptide to cotton, whereas for a quantitative determination, a UV absorption method was employed. We also analyzed the usefulness of electron paramagnetic resonance spectroscopy to characterize our peptide-cotton conjugates.

  12. Prediction of antimicrobial peptides based on the adaptive neuro-fuzzy inference system application.

    PubMed

    Fernandes, Fabiano C; Rigden, Daniel J; Franco, Octavio L

    2012-01-01

    Antimicrobial peptides (AMPs) are widely distributed defense molecules and represent a promising alternative for solving the problem of antibiotic resistance. Nevertheless, the experimental time required to screen putative AMPs makes computational simulations based on peptide sequence analysis and/or molecular modeling extremely attractive. Artificial intelligence methods acting as simulation and prediction tools are of great importance in helping to efficiently discover and design novel AMPs. In the present study, state-of-the-art published outcomes using different prediction methods and databases were compared to an adaptive neuro-fuzzy inference system (ANFIS) model. Data from our study showed that ANFIS obtained an accuracy of 96.7% and a Matthew's Correlation Coefficient (MCC) of0.936, which proved it to be an efficient model for pattern recognition in antimicrobial peptide prediction. Furthermore, a lower number of input parameters were needed for the ANFIS model, improving the speed and ease of prediction. In summary, due to the fuzzy nature ofAMP physicochemical properties, the ANFIS approach presented here can provide an efficient solution for screening putative AMP sequences and for exploration of properties characteristic of AMPs. PMID:23193592

  13. Method for synthesizing peptides with saccharide linked enzyme polymer conjugates

    DOEpatents

    Callstrom, M.R.; Bednarski, M.D.; Gruber, P.R.

    1997-06-17

    A method is disclosed for synthesizing peptides using water soluble enzyme polymer conjugates. The method comprises catalyzing the peptide synthesis with enzyme which has been covalently bonded to a polymer through at least three linkers which linkers have three or more hydroxyl groups. The enzyme is conjugated at lysines or arginines. 19 figs.

  14. Method for synthesizing peptides with saccharide linked enzyme polymer conjugates

    DOEpatents

    Callstrom, Matthew R.; Bednarski, Mark D.; Gruber, Patrick R.

    1997-01-01

    A method is disclosed for synthesizing peptides using water soluble enzyme polymer conjugates. The method comprises catalyzing the peptide synthesis with enzyme which has been covalently bonded to a polymer through at least three linkers which linkers have three or more hydroxyl groups. The enzyme is conjugated at lysines or arginines.

  15. Prediction method abstracts

    SciTech Connect

    1994-12-31

    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  16. Prediction of binding modes between protein L-isoaspartyl (D-aspartyl) O-methyltransferase and peptide substrates including isomerized aspartic acid residues using in silico analytic methods for the substrate screening.

    PubMed

    Oda, Akifumi; Noji, Ikuhiko; Fukuyoshi, Shuichi; Takahashi, Ohgi

    2015-12-10

    Because the aspartic acid (Asp) residues in proteins are occasionally isomerized in the human body, not only l-α-Asp but also l-β-Asp, D-α-Asp and D-β-Asp are found in human proteins. In these isomerized aspartic acids, the proportion of D-β-Asp is the largest and the proportions of l-β-Asp and D-α-Asp found in human proteins are comparatively small. To explain the proportions of aspartic acid isomers, the possibility of an enzyme able to repair l-β-Asp and D-α-Asp is frequently considered. The protein L-isoaspartyl (D-aspartyl) O-methyltransferase (PIMT) is considered one of the possible repair enzymes for l-β-Asp and D-α-Asp. Human PIMT is an enzyme that recognizes both l-β-Asp and D-α-Asp, and catalyzes the methylation of their side chains. In this study, the binding modes between PIMT and peptide substrates containing l-β-Asp or D-α-Asp residues were investigated using computational protein-ligand docking and molecular dynamics simulations. The results indicate that carboxyl groups of both l-β-Asp and D-α-Asp were recognized in similar modes by PIMT and that the C-terminal regions of substrate peptides were located in similar positions on PIMT for both the l-β-Asp and D-α-Asp peptides. In contrast, for peptides containing l-α-Asp or D-β-Asp residues, which are not substrates of PIMT, the computationally constructed binding modes between PIMT and peptides greatly differed from those between PIMT and substrates. In the nonsubstrate peptides, not inter- but intra-molecular hydrogen bonds were observed, and the conformations of peptides were more rigid than those of substrates. Thus, the in silico analytical methods were able to distinguish substrates from nonsubstrates and the computational methods are expected to complement experimental analytical methods.

  17. New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

    PubMed

    Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

    2004-11-21

    Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred). PMID:15534705

  18. CS-AMPPred: An Updated SVM Model for Antimicrobial Activity Prediction in Cysteine-Stabilized Peptides

    PubMed Central

    Porto, William F.; Pires, Állan S.; Franco, Octavio L.

    2012-01-01

    The antimicrobial peptides (AMP) have been proposed as an alternative to control resistant pathogens. However, due to multifunctional properties of several AMP classes, until now there has been no way to perform efficient AMP identification, except through in vitro and in vivo tests. Nevertheless, an indication of activity can be provided by prediction methods. In order to contribute to the AMP prediction field, the CS-AMPPred (Cysteine-Stabilized Antimicrobial Peptides Predictor) is presented here, consisting of an updated version of the Support Vector Machine (SVM) model for antimicrobial activity prediction in cysteine-stabilized peptides. The CS-AMPPred is based on five sequence descriptors: indexes of (i) α-helix and (ii) loop formation; and averages of (iii) net charge, (iv) hydrophobicity and (v) flexibility. CS-AMPPred was based on 310 cysteine-stabilized AMPs and 310 sequences extracted from PDB. The polynomial kernel achieves the best accuracy on 5-fold cross validation (85.81%), while the radial and linear kernels achieve 84.19%. Testing in a blind data set, the polynomial and radial kernels achieve an accuracy of 90.00%, while the linear model achieves 89.33%. The three models reach higher accuracies than previously described methods. A standalone version of CS-AMPPred is available for download at and runs on any Linux machine. PMID:23240023

  19. The quantitative prediction of HLA-B*2705 peptide binding affinities using Support Vector Regression to gain insights into its role for the Spondyloarthropathies.

    PubMed

    Uslan, Volkan; Seker, Huseyin

    2015-01-01

    Computational methods are increasingly utilised in many immunoinformatics problems such as the prediction of binding affinity of peptides. The peptides could provide valuable insight into the drug design and development such as vaccines. Moreover, they can be used to diagnose diseases. The presence of human class I MHC allele HLA-B*2705 is one of the strong hypothesis that would lead spondyloarthropathies. In this paper, Support Vector Regression is used in order to predict binding affinity of peptides with the aid of experimentally determined peptide-MHC binding affinities of 222 peptides to HLA-B*2705 to get more insight into this problematic disease. The results yield a high correlation coefficient as much as 0.65 and the SVR-based predictive models can be considered as a useful tool in order to predict the binding affinities for newly discovered peptides.

  20. A combined prediction strategy increases identification of peptides bound with high affinity and stability to porcine MHC class I molecules SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01.

    PubMed

    Pedersen, Lasse Eggers; Rasmussen, Michael; Harndahl, Mikkel; Nielsen, Morten; Buus, Søren; Jungersen, Gregers

    2016-02-01

    Affinity and stability of peptides bound by major histocompatibility complex (MHC) class I molecules are important factors in presentation of peptides to cytotoxic T lymphocytes (CTLs). In silico prediction methods of peptide-MHC binding followed by experimental analysis of peptide-MHC interactions constitute an attractive protocol to select target peptides from the vast pool of viral proteome peptides. We have earlier reported the peptide binding motif of the porcine MHC-I molecules SLA-1*04:01 and SLA-2*04:01, identified by an ELISA affinity-based positional scanning combinatorial peptide library (PSCPL) approach. Here, we report the peptide binding motif of SLA-3*04:01 and combine two prediction methods and analysis of both peptide binding affinity and stability of peptide-MHC complexes to improve rational peptide selection. Using a peptide prediction strategy combining PSCPL binding matrices and in silico prediction algorithms (NetMHCpan), peptide ligands from a repository of 8900 peptides were predicted for binding to SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01 and validated by affinity and stability assays. From the pool of predicted peptides for SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01, a total of 71, 28, and 38% were binders with affinities below 500 nM, respectively. Comparison of peptide-SLA binding affinity and complex stability showed that peptides of high affinity generally, but not always, produce complexes of high stability. In conclusion, we demonstrate how state-of-the-art prediction and in vitro immunology tools in combination can be used for accurate selection of peptides for MHC class I binding, hence providing an expansion of the field of peptide-MHC analysis also to include pigs as a livestock experimental model.

  1. Chloroplast transit peptide prediction: a peek inside the black box

    PubMed Central

    Schein, Andrew I.; Kissinger, Jessica C.; Ungar, Lyle H.

    2001-01-01

    Previous work in predicting protein localization to the chloroplast organelle in plants led to the development of an artificial neural network-based approach capable of remarkable accuracy in its prediction (ChloroP). A common criticism against such neural network models is that it is difficult to interpret the criteria that are used in making predictions. We address this concern with several new prediction methods that base predictions explicitly on the abundance of different amino acid types in the N-terminal region of the protein. Our successful prediction accuracy suggests that ChloroP uses little positional information in its decision-making; an unexpected result given the elaborate ChloroP input scheme. By removing positional information, our simpler methods allow us to identify those amino acids that are useful for successful prediction. The identification of important sequence features, such as amino acid content, is advantageous if one of the goals of localization predictors is to gain an understanding of the biological process of chloroplast localization. Our most accurate predictor combines principal component analysis and logistic regression. Web-based prediction using this method is available online at http://apicoplast.cis.upenn.edu/pclr/. PMID:11504890

  2. Predicting most probable conformations of a given peptide sequence in the random coil state.

    PubMed

    Bayrak, Cigdem Sevim; Erman, Burak

    2012-11-01

    In this work, we present a computational scheme for finding high probability conformations of peptides. The scheme calculates the probability of a given conformation of the given peptide sequence using the probability distribution of torsion states. Dependence of the states of a residue on the states of its first neighbors along the chain is considered. Prior probabilities of torsion states are obtained from a coil library. Posterior probabilities are calculated by the matrix multiplication Rotational Isomeric States Model of polymer theory. The conformation of a peptide with highest probability is determined by using a hidden Markov model Viterbi algorithm. First, the probability distribution of the torsion states of the residues is obtained. Using the highest probability torsion state, one can generate, step by step, states with lower probabilities. To validate the method, the highest probability state of residues in a given sequence is calculated and compared with probabilities obtained from the Coil Databank. Predictions based on the method are 32% better than predictions based on the most probable states of residues. The ensemble of "n" high probability conformations of a given protein is also determined using the Viterbi algorithm with multistep backtracking. PMID:22955874

  3. Prediction of calcite morphology from computational and experimental studies of mutations of a de novo-designed peptide.

    PubMed

    Schrier, Sarah B; Sayeg, Marianna K; Gray, Jeffrey J

    2011-09-20

    Many organisms use macromolecules, often proteins or peptides, to control the growth of inorganic crystals into complex materials. The ability to model peptide-mineral interactions accurately could allow for the design of novel peptides to produce materials with desired properties. Here, we tested a computational algorithm developed to predict the structure of peptides on mineral surfaces. Using this algorithm, we analyzed energetic and structural differences between a 16-residue peptide (bap4) designed to interact with a calcite growth plane and single- and double-point mutations of the charged residues. Currently, no experimental method is available to resolve the structures of proteins on solid surfaces, which precludes benchmarking for computational models. Therefore, to test the models, we chemically synthesized each peptide and analyzed its effects on calcite crystal growth. Whereas bap4 affected the crystal growth by producing heavily stepped corners and edges, point mutants had variable influences on morphology. Calculated residue-specific binding energies correlated with experimental observations; point mutations of residues predicted to be crucial to surface interactions produced morphologies most similar to unmodified calcite. These results suggest that peptide conformation plays a role in mineral interactions and that the computational model supplies valid energetic and structural data that can provide information about expected crystal morphology.

  4. Pan-Specific Prediction of Peptide-MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity.

    PubMed

    Rasmussen, Michael; Fenoy, Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; Nielsen, Morten; Buus, Søren

    2016-08-15

    Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan. PMID:27402703

  5. Improved Methods for the Enrichment and Analysis of Glycated Peptides

    SciTech Connect

    Zhang, Qibin; Schepmoes, Athena A; Brock, Jonathan W; Wu, Si; Moore, Ronald J; Purvine, Samuel O; Baynes, John; Smith, Richard D; Metz, Thomas O

    2008-12-15

    Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an on-line wash of column-bound glycated peptides using 50 mM ammonium acetate. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (≥3) precursor-ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activation after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. In general, acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor-ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number glycated peptides identified by LC-MS/MS.

  6. A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities

    PubMed Central

    Ghosh, Amit; Nilmeier, Jerome; Weaver, Daniel; Adams, Paul D.; Keasling, Jay D.; Mukhopadhyay, Aindrila; Petzold, Christopher J.; Martín, Héctor García

    2014-01-01

    The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, 13C Metabolic Flux Analysis (13C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during 13C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of 13C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based 13C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species. PMID:25188426

  7. SMALL CYSTEINE-RICH PEPTIDES RESEMBLING ANTIMICROBIAL PEPTIDES HAVE BEEN UNDER-PREDICTED IN PLANTS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multicellular organisms produce small cysteine-rich anti-microbial peptides as an innate defense against pathogens. While defensins, a well-known class of such peptides, are common among eukaryotes, there are classes restricted to the plant kingdom. These include thionins, lipid transfer proteins,...

  8. Signal-CF: a subsite-coupled and window-fusing approach for predicting signal peptides.

    PubMed

    Chou, Kuo-Chen; Shen, Hong-Bin

    2007-06-01

    We have developed an automated method for predicting signal peptide sequences and their cleavage sites in eukaryotic and bacterial protein sequences. It is a 2-layer predictor: the 1st-layer prediction engine is to identify a query protein as secretory or non-secretory; if it is secretory, the process will be automatically continued with the 2nd-layer prediction engine to further identify the cleavage site of its signal peptide. The new predictor is called Signal-CF, where C stands for "coupling" and F for "fusion", meaning that Signal-CF is formed by incorporating the subsite coupling effects along a protein sequence and by fusing the results derived from many width-different scaled windows through a voting system. Signal-CF is featured by high success prediction rates with short computational time, and hence is particularly useful for the analysis of large-scale datasets. Signal-CF is freely available as a web-server at http://chou.med.harvard.edu/bioinf/Signal-CF/ or http://202.120.37.186/bioinf/Signal-CF/.

  9. MetaMHCpan, A Meta Approach for Pan-Specific MHC Peptide Binding Prediction.

    PubMed

    Xu, Yichang; Luo, Cheng; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-01-01

    Recent computational approaches in bioinformatics can achieve high performance, by which they can be a powerful support for performing real biological experiments, making biologists pay more attention to bioinformatics than before. In immunology, predicting peptides which can bind to MHC alleles is an important task, being tackled by many computational approaches. However, this situation causes a serious problem for immunologists to select the appropriate method to be used in bioinformatics. To overcome this problem, we develop an ensemble prediction-based Web server, which we call MetaMHCpan, consisting of two parts: MetaMHCIpan and MetaMHCIIpan, for predicting peptides which can bind MHC-I and MHC-II, respectively. MetaMHCIpan and MetaMHCIIpan use two (MHC2SKpan and LApan) and four (TEPITOPEpan, MHC2SKpan, LApan, and MHC2MIL) existing predictors, respectively. MetaMHCpan is available at http://datamining-iip.fudan.edu.cn/MetaMHCpan/index.php/pages/view/info . PMID:27076335

  10. Enrichment of phosphorylated peptides and proteins by selective precipitation methods.

    PubMed

    Rainer, Matthias; Bonn, Günther K

    2015-01-01

    Protein phosphorylation is one of the most prominent post-translational modifications involved in the regulation of cellular processes. Fundamental understanding of biological processes requires appropriate bioanalytical methods for selectively enriching phosphorylated peptides and proteins. Most of the commonly applied enrichment approaches include chromatographic materials including Fe(3+)-immobilized metal-ion affinity chromatography or metal oxides. In the last years, the introduction of several non-chromatographic isolation technologies has increasingly attracted the interest of many scientists. Such approaches are based on the selective precipitation of phosphorylated peptides and proteins by applying various metal cations. The excellent performance of precipitation-based enrichment methods can be explained by the absence of any stationary phase, resin or sorbent, which usually leads to unspecific binding. This review provides an overview of recently published methods for the selective precipitation of phosphorylated peptides and proteins. PMID:25587840

  11. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

    PubMed Central

    Kang, Juanjuan; Ru, Beibei; Zhou, Peng

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community. PMID:27610387

  12. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides.

    PubMed

    He, Bifang; Kang, Juanjuan; Ru, Beibei; Ding, Hui; Zhou, Peng; Huang, Jian

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community. PMID:27610387

  13. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

    PubMed Central

    Kang, Juanjuan; Ru, Beibei; Zhou, Peng

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community.

  14. A Novel Peptide Binding Prediction Approach for HLA-DR Molecule Based on Sequence and Structural Information.

    PubMed

    Li, Zhao; Zhao, Yilei; Pan, Gaofeng; Tang, Jijun; Guo, Fei

    2016-01-01

    MHC molecule plays a key role in immunology, and the molecule binding reaction with peptide is an important prerequisite for T cell immunity induced. MHC II molecules do not have conserved residues, so they appear as open grooves. As a consequence, this will increase the difficulty in predicting MHC II molecules binding peptides. In this paper, we aim to propose a novel prediction method for MHC II molecules binding peptides. First, we calculate sequence similarity and structural similarity between different MHC II molecules. Then, we reorder pseudosequences according to descending similarity values and use a weight calculation formula to calculate new pocket profiles. Finally, we use three scoring functions to predict binding cores and evaluate the accuracy of prediction to judge performance of each scoring function. In the experiment, we set a parameter α in the weight formula. By changing α value, we can observe different performances of each scoring function. We compare our method with the best function to some popular prediction methods and ultimately find that our method outperforms them in identifying binding cores of HLA-DR molecules. PMID:27340658

  15. Activity Prediction and Molecular Mechanism of Bovine Blood Derived Angiotensin I-Converting Enzyme Inhibitory Peptides

    PubMed Central

    Zhang, Ting; Nie, Shaoping; Liu, Boqun; Yu, Yiding; Zhang, Yan; Liu, Jingbo

    2015-01-01

    Development of angiotensin I-converting enzyme (ACE, EC 3.4.15.1) inhibitory peptides from food protein is under extensive research as alternative for the prevention of hypertension. However, it is difficult to identify peptides released from food sources. To accelerate the progress of peptide identification, a three layer back propagation neural network model was established to predict the ACE-inhibitory activity of pentapeptides derived from bovine hemoglobin by simulated enzyme digestion. The pentapeptide WTQRF has the best predicted value with experimental IC50 23.93 μM. The potential molecular mechanism of the WTQRF / ACE interaction was investigated by flexible docking. PMID:25768442

  16. Activity prediction and molecular mechanism of bovine blood derived angiotensin I-converting enzyme inhibitory peptides.

    PubMed

    Zhang, Ting; Nie, Shaoping; Liu, Boqun; Yu, Yiding; Zhang, Yan; Liu, Jingbo

    2015-01-01

    Development of angiotensin I-converting enzyme (ACE, EC 3.4.15.1) inhibitory peptides from food protein is under extensive research as alternative for the prevention of hypertension. However, it is difficult to identify peptides released from food sources. To accelerate the progress of peptide identification, a three layer back propagation neural network model was established to predict the ACE-inhibitory activity of pentapeptides derived from bovine hemoglobin by simulated enzyme digestion. The pentapeptide WTQRF has the best predicted value with experimental IC50 23.93 μM. The potential molecular mechanism of the WTQRF / ACE interaction was investigated by flexible docking. PMID:25768442

  17. Prediction of Scylla olivacea (Crustacea; Brachyura) peptide hormones using publicly accessible transcriptome shotgun assembly (TSA) sequences.

    PubMed

    Christie, Andrew E

    2016-05-01

    The aquaculture of crabs from the genus Scylla is of increasing economic importance for many Southeast Asian countries. Expansion of Scylla farming has led to increased efforts to understand the physiology and behavior of these crabs, and as such, there are growing molecular resources for them. Here, publicly accessible Scylla olivacea transcriptomic data were mined for putative peptide-encoding transcripts; the proteins deduced from the identified sequences were then used to predict the structures of mature peptide hormones. Forty-nine pre/preprohormone-encoding transcripts were identified, allowing for the prediction of 187 distinct mature peptides. The identified peptides included isoforms of adipokinetic hormone-corazonin-like peptide, allatostatin A, allatostatin B, allatostatin C, bursicon β, CCHamide, corazonin, crustacean cardioactive peptide, crustacean hyperglycemic hormone/molt-inhibiting hormone, diuretic hormone 31, eclosion hormone, FMRFamide-like peptide, HIGSLYRamide, insulin-like peptide, intocin, leucokinin, myosuppressin, neuroparsin, neuropeptide F, orcokinin, pigment dispersing hormone, pyrokinin, red pigment concentrating hormone, RYamide, short neuropeptide F, SIFamide and tachykinin-related peptide, all well-known neuropeptide families. Surprisingly, the tissue used to generate the transcriptome mined here is reported to be testis. Whether or not the testis samples had neural contamination is unknown. However, if the peptides are truly produced by this reproductive organ, it could have far reaching consequences for the study of crustacean endocrinology, particularly in the area of reproductive control. Regardless, this peptidome is the largest thus far predicted for any brachyuran (true crab) species, and will serve as a foundation for future studies of peptidergic control in members of the commercially important genus Scylla.

  18. Prediction of Antimicrobial Activity of Synthetic Peptides by a Decision Tree Model

    PubMed Central

    Lira, Felipe; Perez, Pedro S.; Baranauskas, José A.

    2013-01-01

    Antimicrobial resistance is a persistent problem in the public health sphere. However, recent attempts to find effective substitutes to combat infections have been directed at identifying natural antimicrobial peptides in order to circumvent resistance to commercial antibiotics. This study describes the development of synthetic peptides with antimicrobial activity, created in silico by site-directed mutation modeling using wild-type peptides as scaffolds for these mutations. Fragments of antimicrobial peptides were used for modeling with molecular modeling computational tools. To analyze these peptides, a decision tree model, which indicated the action range of peptides on the types of microorganisms on which they can exercise biological activity, was created. The decision tree model was processed using physicochemistry properties from known antimicrobial peptides available at the Antimicrobial Peptide Database (APD). The two most promising peptides were synthesized, and antimicrobial assays showed inhibitory activity against Gram-positive and Gram-negative bacteria. Colossomin C and colossomin D were the most inhibitory peptides at 5 μg/ml against Staphylococcus aureus and Escherichia coli. The methods described in this work and the results obtained are useful for the identification and development of new compounds with antimicrobial activity through the use of computational tools. PMID:23455341

  19. Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide-HLA Interactions.

    PubMed

    Bassani-Sternberg, Michal; Gfeller, David

    2016-09-15

    Ag presentation on HLA molecules plays a central role in infectious diseases and tumor immunology. To date, large-scale identification of (neo-)Ags from DNA sequencing data has mainly relied on predictions. In parallel, mass spectrometry analysis of HLA peptidome is increasingly performed to directly detect peptides presented on HLA molecules. In this study, we use a novel unsupervised approach to assign mass spectrometry-based HLA peptidomics data to their cognate HLA molecules. We show that incorporation of deconvoluted HLA peptidomics data in ligand prediction algorithms can improve their accuracy for HLA alleles with few ligands in existing databases. The results of our computational analysis of large datasets of naturally processed HLA peptides, together with experimental validation and protein structure analysis, further reveal how HLA-binding motifs change with peptide length and predict new cooperative effects between distant residues in HLA-B07:02 ligands. PMID:27511729

  20. Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide-HLA Interactions.

    PubMed

    Bassani-Sternberg, Michal; Gfeller, David

    2016-09-15

    Ag presentation on HLA molecules plays a central role in infectious diseases and tumor immunology. To date, large-scale identification of (neo-)Ags from DNA sequencing data has mainly relied on predictions. In parallel, mass spectrometry analysis of HLA peptidome is increasingly performed to directly detect peptides presented on HLA molecules. In this study, we use a novel unsupervised approach to assign mass spectrometry-based HLA peptidomics data to their cognate HLA molecules. We show that incorporation of deconvoluted HLA peptidomics data in ligand prediction algorithms can improve their accuracy for HLA alleles with few ligands in existing databases. The results of our computational analysis of large datasets of naturally processed HLA peptides, together with experimental validation and protein structure analysis, further reveal how HLA-binding motifs change with peptide length and predict new cooperative effects between distant residues in HLA-B07:02 ligands.

  1. A sequence-based computational approach to predicting PDZ domain-peptide interactions.

    PubMed

    Nakariyakul, Songyot; Liu, Zhi-Ping; Chen, Luonan

    2014-01-01

    The PDZ domain is one of the most ubiquitous protein domains that is involved in coordinating signaling complex formation and protein networking by reversibly interacting with multiple binding partners. It has been linked to many devastating diseases such as avian influenza, Fraser syndrome, Usher syndrome and Dejerine-Sottas neuropathy. Understanding the selectivity of PDZ domains can help elucidate how defects in PDZ proteins and their binding partners lead to human diseases. Since experimental methods to determine the interaction specificity of the PDZ domains are expensive and labor intensive, an accurate computational method is thus needed. Our developed support vector machine-based predictor using dipeptide composition is shown to qualitatively predict PDZ domain-peptide interaction with a high accuracy rate. Furthermore, since most of the dipeptide compositions are redundant and irrelevant, we propose a new hybrid feature selection technique to select only a subset of these compositions for interaction prediction. The experimental results show that only approximately 25% of dipeptide features are needed and that our method improves the prediction results significantly. The selected dipeptide features are also analyzed and shown to play important roles in specificity patterns of PDZ domains. Our method is based only on primary sequence information, and it can be used for the research of drug target and drug design in identifying PDZ domain-ligand interactions. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai. PMID:23608946

  2. A simple and effective method for producing nonrandom peptide libraries using cotton as a carrier in continuous flow peptide synthesizers.

    PubMed

    Mutulis, Felikss; Tysk, Marcus; Mutule, Ilze; Wikberg, Jarl E S

    2003-01-01

    A method has been developed for generating nonrandom peptide libraries on cotton. Disks of cotton fabric were chemically modified to enable peptide synthesis. Incorporation of a 6-aminocaproic acid residue handle on the cellulose turned out to be advantageous. Disks were labeled with silver ink, stacked one on top of another in a continuous flow peptide synthesizer column, and simultaneously subjected to automated synthesis procedures. Depending on the sequences to be synthesized, the automatic synthesis procedure was stopped, and the disks were removed from the column, sorted, and reapplied to subsequent synthesis steps. In this way, individual peptides could be easily prepared in milligram quantities on each of the cotton disks.

  3. Binding Site Prediction of Proteins with Organic Compounds or Peptides Using GALAXY Web Servers.

    PubMed

    Heo, Lim; Lee, Hasup; Baek, Minkyung; Seok, Chaok

    2016-01-01

    We introduce two GALAXY web servers called GalaxySite and GalaxyPepDock that predict protein complex structures with small organic compounds and peptides, respectively. GalaxySite predicts ligands that may bind the input protein and generates complex structures of the protein with the predicted ligands from the protein structure given as input or predicted from the input sequence. GalaxyPepDock takes a protein structure and a peptide sequence as input and predicts structures for the protein-peptide complex. Both GalaxySite and GalaxyPepDock rely on available experimentally resolved structures of protein-ligand complexes evolutionarily related to the target. With the continuously increasing size of the protein structure database, the probability of finding related proteins in the database is increasing. The servers further relax the complex structures to refine the structural aspects that are missing in the available structures or that are not compatible with the given protein by optimizing physicochemical interactions. GalaxyPepDock allows conformational change of the protein receptor induced by peptide binding. The atomistic interactions with ligands predicted by the GALAXY servers may offer important clues for designing new molecules or proteins with desired binding properties. PMID:27094284

  4. dPABBs: A Novel in silico Approach for Predicting and Designing Anti-biofilm Peptides

    PubMed Central

    Sharma, Arun; Gupta, Pooja; Kumar, Rakesh; Bhardwaj, Anshu

    2016-01-01

    Increasingly, biofilms are being recognised for their causative role in persistent infections (like cystic fibrosis, otitis media, diabetic foot ulcers) and nosocomial diseases (biofilm-infected vascular catheters, implants and prosthetics). Given the clinical relevance of biofilms and their recalcitrance to conventional antibiotics, it is imperative that alternative therapeutics are proactively sought. We have developed dPABBs, a web server that facilitates the prediction and design of anti-biofilm peptides. The six SVM and Weka models implemented on dPABBs were observed to identify anti-biofilm peptides on the basis of their whole amino acid composition, selected residue features and the positional preference of the residues (maximum accuracy, sensitivity, specificity and MCC of 95.24%, 92.50%, 97.73% and 0.91, respectively, on the training datasets). On the N-terminus, it was seen that either of the cationic polar residues, R and K, is present at all five positions in case of the anti-biofilm peptides, whereas in the QS peptides, the uncharged polar residue S is preponderant at the first (also anionic polar residues D, E), third and fifth positions. Positive predictions were also obtained for 29 FDA-approved peptide drugs and ten antimicrobial peptides in clinical development, indicating at their possible repurposing for anti-biofilm therapy. dPABBs is freely accessible on: http://ab-openlab.csir.res.in/abp/antibiofilm/. PMID:26912180

  5. Relevance of PET for pretherapeutic prediction of doses in peptide receptor radionuclide therapy.

    PubMed

    Blaickner, Matthias; Baum, Richard P

    2014-01-01

    Personalized dosimetry in radionuclide therapy has gained much attention in recent years. This attention has also an impact on peptide receptor radionuclide therapy (PRRT). This article reviews the PET-based imaging techniques that can be used for pretherapeutic prediction of doses in PRRT. More specifically the usage of (86)Y, (90)Y, (68)Ga, and (44)Sc are discussed: their characteristics for PET acquisition, the available peptides for labeling, the specifics of the imaging protocols, and the experiences gained from phantom and clinical studies. These techniques are evaluated with regard to their usefulness for dosimetry predictions in PRRT, and future perspectives are discussed.

  6. Dissociation of POMC Peptides after Self-Injury Predicts Responses To Centrally Acting Opiate Blockers.

    ERIC Educational Resources Information Center

    Sandman, Curt A.; Hetrick, William; Taylor, Derek V.; Chicz-DeMet, Aleksandra

    1997-01-01

    This study investigated whether blood plasma levels of pro-opiomelanocortin-derived (POMC) peptides, beta-endorphin-like activity, adrenocorticotrophic hormone, and adrenal cortisol immediately after self injurious behavior (SIB) episodes predicted subsequent response to an opiate blocker in 10 patients with mental retardation. Results suggest…

  7. Predicted class-I aminoacyl tRNA synthetase-like proteins in non-ribosomal peptide synthesis

    PubMed Central

    2010-01-01

    Background Recent studies point to a great diversity of non-ribosomal peptide synthesis systems with major roles in amino acid and co-factor biosynthesis, secondary metabolism, and post-translational modifications of proteins by peptide tags. The least studied of these systems are those utilizing tRNAs or aminoacyl-tRNA synthetases (AAtRS) in non-ribosomal peptide ligation. Results Here we describe novel examples of AAtRS related proteins that are likely to be involved in the synthesis of widely distributed peptide-derived metabolites. Using sensitive sequence profile methods we show that the cyclodipeptide synthases (CDPSs) are members of the HUP class of Rossmannoid domains and are likely to be highly derived versions of the class-I AAtRS catalytic domains. We also identify the first eukaryotic CDPSs in fungi and in animals; they might be involved in immune response in the latter organisms. We also identify a paralogous version of the methionyl-tRNA synthetase, which is widespread in bacteria, and present evidence using contextual information that it might function independently of protein synthesis as a peptide ligase in the formation of a peptide- derived secondary metabolite. This metabolite is likely to be heavily modified through multiple reactions catalyzed by a metal-binding cupin domain and a lysine N6 monooxygenase that are strictly associated with this paralogous methionyl-tRNA synthetase (MtRS). We further identify an analogous system wherein the MtRS has been replaced by more typical peptide ligases with the ATP-grasp or modular condensation-domains. Conclusions The prevalence of these predicted biosynthetic pathways in phylogenetically distant, pathogenic or symbiotic bacteria suggests that metabolites synthesized by them might participate in interactions with the host. More generally, these findings point to a complete spectrum of recruitment of AAtRS to various non-ribosomal biosynthetic pathways, ranging from the conventional AAtRS, through

  8. Utility and limitations of a peptide reactivity assay to predict fragrance allergens in vitro.

    PubMed

    Natsch, A; Gfeller, H; Rothaupt, M; Ellis, G

    2007-10-01

    A key step in the skin sensitization process is the formation of a covalent adduct between the skin sensitizer and endogenous proteins and/or peptides in the skin. A published peptide depletion assay was used to relate the in vitro reactivity of fragrance molecules to LLNA data. Using the classical assay, 22 of 28 tested moderate to strong sensitizers were positive. The prediction of weak sensitizers proved to be more difficult with only 50% of weak sensitizers giving a positive response, but for some compounds this could also be due to false-positive results from the LLNA. LC-MS analysis yielded the expected mass of the peptide adducts in several cases, whereas in other cases putative oxidation reactions led to adducts of unexpected molecular weight. Several moderately sensitizing aldehydes were correctly predicted by the depletion assay, but no adducts were found and the depletion appears to be due to an oxidation of the parent peptide catalyzed by the test compound. Finally, alternative test peptides derived from a physiological reactive protein with enhanced sensitivity for weak Michael acceptors were found, further increasing the sensitivity of the assay.

  9. Semi-Supervised Prediction of SH2-Peptide Interactions from Imbalanced High-Throughput Data

    PubMed Central

    Kundu, Kousik; Costa, Fabrizio; Huber, Michael; Reth, Michael; Backofen, Rolf

    2013-01-01

    Src homology 2 (SH2) domains are the largest family of the peptide-recognition modules (PRMs) that bind to phosphotyrosine containing peptides. Knowledge about binding partners of SH2-domains is key for a deeper understanding of different cellular processes. Given the high binding specificity of SH2, in-silico ligand peptide prediction is of great interest. Currently however, only a few approaches have been published for the prediction of SH2-peptide interactions. Their main shortcomings range from limited coverage, to restrictive modeling assumptions (they are mainly based on position specific scoring matrices and do not take into consideration complex amino acids inter-dependencies) and high computational complexity. We propose a simple yet effective machine learning approach for a large set of known human SH2 domains. We used comprehensive data from micro-array and peptide-array experiments on 51 human SH2 domains. In order to deal with the high data imbalance problem and the high signal-to-noise ration, we casted the problem in a semi-supervised setting. We report competitive predictive performance w.r.t. state-of-the-art. Specifically we obtain 0.83 AUC ROC and 0.93 AUC PR in comparison to 0.71 AUC ROC and 0.87 AUC PR previously achieved by the position specific scoring matrices (PSSMs) based SMALI approach. Our work provides three main contributions. First, we showed that better models can be obtained when the information on the non-interacting peptides (negative examples) is also used. Second, we improve performance when considering high order correlations between the ligand positions employing regularization techniques to effectively avoid overfitting issues. Third, we developed an approach to tackle the data imbalance problem using a semi-supervised strategy. Finally, we performed a genome-wide prediction of human SH2-peptide binding, uncovering several findings of biological relevance. We make our models and genome-wide predictions, for all the 51 SH2

  10. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.

    PubMed

    Lundegaard, Claus; Lamberth, Kasper; Harndahl, Mikkel; Buus, Søren; Lund, Ole; Nielsen, Morten

    2008-07-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8-11 for all 122 alleles. artificial neural network predictions are given as actual IC(50) values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75-80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.

  11. Predictive sensor method and apparatus

    NASA Technical Reports Server (NTRS)

    Cambridge, Vivien J.; Koger, Thomas L.

    1993-01-01

    A microprocessor and electronics package employing predictive methodology was developed to accelerate the response time of slowly responding hydrogen sensors. The system developed improved sensor response time from approximately 90 seconds to 8.5 seconds. The microprocessor works in real-time providing accurate hydrogen concentration corrected for fluctuations in sensor output resulting from changes in atmospheric pressure and temperature. Following the successful development of the hydrogen sensor system, the system and predictive methodology was adapted to a commercial medical thermometer probe. Results of the experiment indicate that, with some customization of hardware and software, response time improvements are possible for medical thermometers as well as other slowly responding sensors.

  12. Diversity of Monomers in Nonribosomal Peptides: towards the Prediction of Origin and Biological Activity ▿ †

    PubMed Central

    Caboche, Ségolène; Leclère, Valérie; Pupin, Maude; Kucherov, Gregory; Jacques, Philippe

    2010-01-01

    Nonribosomal peptides (NRPs) are molecules produced by microorganisms that have a broad spectrum of biological activities and pharmaceutical applications (e.g., antibiotic, immunomodulating, and antitumor activities). One particularity of the NRPs is the biodiversity of their monomers, extending far beyond the 20 proteogenic amino acid residues. Norine, a comprehensive database of NRPs, allowed us to review for the first time the main characteristics of the NRPs and especially their monomer biodiversity. Our analysis highlighted a significant similarity relationship between NRPs synthesized by bacteria and those isolated from metazoa, especially from sponges, supporting the hypothesis that some NRPs isolated from sponges are actually synthesized by symbiotic bacteria rather than by the sponges themselves. A comparison of peptide monomeric compositions as a function of biological activity showed that some monomers are specific to a class of activities. An analysis of the monomer compositions of peptide products predicted from genomic information (metagenomics and high-throughput genome sequencing) or of new peptides detected by mass spectrometry analysis applied to a culture supernatant can provide indications of the origin of a peptide and/or its biological activity. PMID:20693331

  13. Methods and kits for predicting a response to an erythropoietic agent

    DOEpatents

    Merchant, Michael L.; Klein, Jon B.; Brier, Michael E.; Gaweda, Adam E.

    2015-06-16

    Methods for predicting a response to an erythropoietic agent in a subject include providing a biological sample from the subject, and determining an amount in the sample of at least one peptide selected from the group consisting of SEQ ID NOS: 1-17. If there is a measurable difference in the amount of the at least one peptide in the sample, when compared to a control level of the same peptide, the subject is then predicted to have a good response or a poor response to the erythropoietic agent. Kits for predicting a response to an erythropoietic agent are further provided and include one or more antibodies, or fragments thereof, that specifically recognize a peptide of SEQ ID NOS: 1-17.

  14. Determination of diffusion coefficients of peptides and prediction of permeability through a porous membrane.

    PubMed

    Hosoya, Osamu; Chono, Sumio; Saso, Yuko; Juni, Kazuhiko; Morimoto, Kazuhiro; Seki, Toshinobu

    2004-12-01

    The diffusion coefficient (D) of peptide and protein drugs needs to be determined to examine the permeability through biological barriers and to optimize delivery systems. In this study, the D values of fluorescein isothiocyanate (FITC)-labelled dextrans (FDs) and peptides were determined and the permeability through a porous membrane was discussed. The observed D values of FDs and peptides, except in the case of insulin, were similar to those calculated based on a relationship previously reported between the molecular weight and D of lower-molecular-weight compounds, although the molecular weight range was completely different. The observed D value of insulin was between the calculated values for the insulin monomer and hexamer. The permeability of poly-lysine and insulin through the membrane was determined and the observed values were compared with predicted values by using the relationship between molecular weight and D and an equation based on the Renkin function. The observed permeability of insulin through the membrane was between that of the predicted permeability for the insulin monomer and hexamer. For the permeation of insulin, the determination of D was useful for estimating the permeability because of the irregular relationship between molecular weight and D. The methodology used in this study will be useful for a more quantitative evaluation of the absorption of peptide and protein drugs applied to mucous membranes.

  15. Prediction of Antimicrobial Peptides Based on Sequence Alignment and Support Vector Machine-Pairwise Algorithm Utilizing LZ-Complexity

    PubMed Central

    Shahrudin, Shahriza

    2015-01-01

    This study concerns an attempt to establish a new method for predicting antimicrobial peptides (AMPs) which are important to the immune system. Recently, researchers are interested in designing alternative drugs based on AMPs because they have found that a large number of bacterial strains have become resistant to available antibiotics. However, researchers have encountered obstacles in the AMPs designing process as experiments to extract AMPs from protein sequences are costly and require a long set-up time. Therefore, a computational tool for AMPs prediction is needed to resolve this problem. In this study, an integrated algorithm is newly introduced to predict AMPs by integrating sequence alignment and support vector machine- (SVM-) LZ complexity pairwise algorithm. It was observed that, when all sequences in the training set are used, the sensitivity of the proposed algorithm is 95.28% in jackknife test and 87.59% in independent test, while the sensitivity obtained for jackknife test and independent test is 88.74% and 78.70%, respectively, when only the sequences that has less than 70% similarity are used. Applying the proposed algorithm may allow researchers to effectively predict AMPs from unknown protein peptide sequences with higher sensitivity. PMID:25802839

  16. Free energies of solvation for peptides and polypeptides using SCRF methods

    NASA Astrophysics Data System (ADS)

    Alemán, Carlos; Ishiki, Hamilton Mitsugu; Armelin, Elaine A.; Abrahão Junior, Odonírio; Galembeck, Sergio E.

    1998-07-01

    The effects of the aqueous solvent in the conformational preferences of peptides and homopeptides have been investigated using two different and widely used self-consistent reaction-field models. The free energies of solvation were predicted using the polarizable continuum model developed by Tomasi and co-workers and adapted to semi-empirical hamiltonians by Orozco and Luque, and the solvation model developed by Cramer and Truhlar. The set of compounds investigated is constituted by five dipeptides with different chemical nature and structural properties as well as by two homopeptides in which the size of the polypeptidic chain was varied. Results provided by the different methods are compared and discussed.

  17. Protein Residue Contacts and Prediction Methods

    PubMed Central

    Adhikari, Badri

    2016-01-01

    In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch. In this chapter, we briefly discuss many elements of protein residue–residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. PMID:27115648

  18. Enabling the Discovery and Virtual Screening of Potent and Safe Antimicrobial Peptides. Simultaneous Prediction of Antibacterial Activity and Cytotoxicity.

    PubMed

    Kleandrova, Valeria V; Ruso, Juan M; Speck-Planche, Alejandro; Dias Soeiro Cordeiro, M Natália

    2016-08-01

    Antimicrobial peptides (AMPs) represent promising alternatives to fight against bacterial pathogens. However, cellular toxicity remains one of the main concerns in the early development of peptide-based drugs. This work introduces the first multitasking (mtk) computational model focused on performing simultaneous predictions of antibacterial activities, and cytotoxicities of peptides. The model was created from a data set containing 3592 cases, and it displayed accuracy higher than 96% for classifying/predicting peptides in both training and prediction (test) sets. The technique known as alanine scanning was computationally applied to illustrate the calculation of the quantitative contributions of the amino acids (in their respective positions of the sequence) to the biological effects of a defined peptide. A small library formed by 10 peptides was generated, where peptides were designed by considering the interpretations of the different descriptors in the mtk-computational model. All the peptides were predicted to exhibit high antibacterial activities against multiple bacterial strains, and low cytotoxicity against various cell types. The present mtk-computational model can be considered a very useful tool to support high throughput research for the discovery of potent and safe AMPs.

  19. Enabling the Discovery and Virtual Screening of Potent and Safe Antimicrobial Peptides. Simultaneous Prediction of Antibacterial Activity and Cytotoxicity.

    PubMed

    Kleandrova, Valeria V; Ruso, Juan M; Speck-Planche, Alejandro; Dias Soeiro Cordeiro, M Natália

    2016-08-01

    Antimicrobial peptides (AMPs) represent promising alternatives to fight against bacterial pathogens. However, cellular toxicity remains one of the main concerns in the early development of peptide-based drugs. This work introduces the first multitasking (mtk) computational model focused on performing simultaneous predictions of antibacterial activities, and cytotoxicities of peptides. The model was created from a data set containing 3592 cases, and it displayed accuracy higher than 96% for classifying/predicting peptides in both training and prediction (test) sets. The technique known as alanine scanning was computationally applied to illustrate the calculation of the quantitative contributions of the amino acids (in their respective positions of the sequence) to the biological effects of a defined peptide. A small library formed by 10 peptides was generated, where peptides were designed by considering the interpretations of the different descriptors in the mtk-computational model. All the peptides were predicted to exhibit high antibacterial activities against multiple bacterial strains, and low cytotoxicity against various cell types. The present mtk-computational model can be considered a very useful tool to support high throughput research for the discovery of potent and safe AMPs. PMID:27280735

  20. Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides

    PubMed Central

    Schanstra, Joost P.; Alkhalaf, Alaa; Argiles, Angel; Bakker, Stephan J.L.; Beige, Joachim; Bilo, Henk J.G.; Chatzikyrkou, Christos; Dakna, Mohammed; Dawson, Jesse; Delles, Christian; Haller, Hermann; Haubitz, Marion; Husi, Holger; Jankowski, Joachim; Jerums, George; Kleefstra, Nanne; Kuznetsova, Tatiana; Maahs, David M.; Menne, Jan; Mullen, William; Ortiz, Alberto; Persson, Frederik; Rossing, Peter; Ruggenenti, Piero; Rychlik, Ivan; Serra, Andreas L.; Siwy, Justyna; Snell-Bergeon, Janet; Spasovski, Goce; Staessen, Jan A.; Vlahou, Antonia; Mischak, Harald; Vanholder, Raymond

    2015-01-01

    Progressive CKD is generally detected at a late stage by a sustained decline in eGFR and/or the presence of significant albuminuria. With the aim of early and improved risk stratification of patients with CKD, we studied urinary peptides in a large cross-sectional multicenter cohort of 1990 individuals, including 522 with follow-up data, using proteome analysis. We validated that a previously established multipeptide urinary biomarker classifier performed significantly better in detecting and predicting progression of CKD than the current clinical standard, urinary albumin. The classifier was also more sensitive for identifying patients with rapidly progressing CKD. Compared with the combination of baseline eGFR and albuminuria (area under the curve [AUC]=0.758), the addition of the multipeptide biomarker classifier significantly improved CKD risk prediction (AUC=0.831) as assessed by the net reclassification index (0.303±−0.065; P<0.001) and integrated discrimination improvement (0.058±0.014; P<0.001). Correlation of individual urinary peptides with CKD stage and progression showed that the peptides that associated with CKD, irrespective of CKD stage or CKD progression, were either fragments of the major circulating proteins, suggesting failure of the glomerular filtration barrier sieving properties, or different collagen fragments, suggesting accumulation of intrarenal extracellular matrix. Furthermore, protein fragments associated with progression of CKD originated mostly from proteins related to inflammation and tissue repair. Results of this study suggest that urinary proteome analysis might significantly improve the current state of the art of CKD detection and outcome prediction and that identification of the urinary peptides allows insight into various ongoing pathophysiologic processes in CKD. PMID:25589610

  1. Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides.

    PubMed

    Schanstra, Joost P; Zürbig, Petra; Alkhalaf, Alaa; Argiles, Angel; Bakker, Stephan J L; Beige, Joachim; Bilo, Henk J G; Chatzikyrkou, Christos; Dakna, Mohammed; Dawson, Jesse; Delles, Christian; Haller, Hermann; Haubitz, Marion; Husi, Holger; Jankowski, Joachim; Jerums, George; Kleefstra, Nanne; Kuznetsova, Tatiana; Maahs, David M; Menne, Jan; Mullen, William; Ortiz, Alberto; Persson, Frederik; Rossing, Peter; Ruggenenti, Piero; Rychlik, Ivan; Serra, Andreas L; Siwy, Justyna; Snell-Bergeon, Janet; Spasovski, Goce; Staessen, Jan A; Vlahou, Antonia; Mischak, Harald; Vanholder, Raymond

    2015-08-01

    Progressive CKD is generally detected at a late stage by a sustained decline in eGFR and/or the presence of significant albuminuria. With the aim of early and improved risk stratification of patients with CKD, we studied urinary peptides in a large cross-sectional multicenter cohort of 1990 individuals, including 522 with follow-up data, using proteome analysis. We validated that a previously established multipeptide urinary biomarker classifier performed significantly better in detecting and predicting progression of CKD than the current clinical standard, urinary albumin. The classifier was also more sensitive for identifying patients with rapidly progressing CKD. Compared with the combination of baseline eGFR and albuminuria (area under the curve [AUC]=0.758), the addition of the multipeptide biomarker classifier significantly improved CKD risk prediction (AUC=0.831) as assessed by the net reclassification index (0.303±-0.065; P<0.001) and integrated discrimination improvement (0.058±0.014; P<0.001). Correlation of individual urinary peptides with CKD stage and progression showed that the peptides that associated with CKD, irrespective of CKD stage or CKD progression, were either fragments of the major circulating proteins, suggesting failure of the glomerular filtration barrier sieving properties, or different collagen fragments, suggesting accumulation of intrarenal extracellular matrix. Furthermore, protein fragments associated with progression of CKD originated mostly from proteins related to inflammation and tissue repair. Results of this study suggest that urinary proteome analysis might significantly improve the current state of the art of CKD detection and outcome prediction and that identification of the urinary peptides allows insight into various ongoing pathophysiologic processes in CKD. PMID:25589610

  2. Clinical Value of Natriuretic Peptides in Predicting Time to Dialysis in Stage 4 and 5 Chronic Kidney Disease Patients

    PubMed Central

    Sundqvist, Sofia; Larson, Thomas; Cauliez, Bruno; Bauer, Fabrice; Dumont, Audrey; Le Roy, Frank; Hanoy, Mélanie; Fréguin-Bouilland, Caroline; Godin, Michel

    2016-01-01

    Background Anticipating the time to renal replacement therapy (RRT) in chronic kidney disease (CKD) patients is an important but challenging issue. Natriuretic peptides are biomarkers of ventricular dysfunction related to poor outcome in CKD. We comparatively investigated the value of B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) as prognostic markers for the risk of RRT in stage 4 and 5 CKD patients, and in foretelling all-cause mortality and major cardiovascular events within a 5-year follow-up period. Methods Baseline plasma BNP (Triage, Biosite) and NT-proBNP (Elecsys, Roche) were measured at inclusion. Forty-three patients were followed-up during 5 years. Kaplan-Meier analysis, with log-rank testing and hazard ratios (HR), were calculated to evaluate survival without RRT, cardiovascular events or mortality. The independent prognostic value of the biomarkers was estimated in separate Cox multivariate analysis, including estimated glomerular filtration rate (eGFR), creatininemia and comorbidities. Results During the first 12-month follow-up period, 16 patients started RRT. NT-proBNP concentration was higher in patients who reached endpoint (3221 ng/L vs 777 ng/L, p = 0.02). NT-proBNP concentration > 1345 ng/L proved significant predictive value on survival analysis for cardiovascular events (p = 0.04) and dialysis within 60 months follow-up (p = 0.008). BNP concentration > 140 ng/L was an independent predictor of RRT after 12 months follow-up (p<0.005), and of significant predictive value for initiation of dialysis within 60 months follow-up. Conclusions Our results indicate a prognostic value for BNP and NT-proBNP in predicting RRT in stage 4 and 5 CKD patients, regarding both short- and long-term periods. NT-proBNP also proved a value in predicting cardiovascular events. Natriuretic peptides could be useful predictive biomarkers for therapeutic guidance in CKD. PMID:27548064

  3. Signal-BNF: a Bayesian network fusing approach to predict signal peptides.

    PubMed

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells.

  4. Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

    PubMed Central

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells. PMID:23118510

  5. Prediction of anticancer peptides against MCF-7 breast cancer cells from the peptidomes of Achatina fulica mucus fractions

    PubMed Central

    E-kobon, Teerasak; Thongararm, Pennapa; Roytrakul, Sittiruk; Meesuk, Ladda; Chumnanpuen, Pramote

    2015-01-01

    Several reports have shown antimicrobial and anticancer activities of mucous glycoproteins extracted from the giant African snail Achatina fulica. Anticancer properties of the snail mucous peptides remain incompletely revealed. The aim of this study was to predict anticancer peptides from A. fulica mucus. Two of HPLC-separated mucous fractions (F2 and F5) showed in vitro cytotoxicity against the breast cancer cell line (MCF-7) and normal epithelium cell line (Vero). According to the mass spectrometric analysis, 404 and 424 peptides from the F2 and F5 fractions were identified. Our comprehensive bioinformatics workflow predicted 16 putative cationic and amphipathic anticancer peptides with diverse structures from these two peptidome data. These peptides would be promising molecules for new anti-breast cancer drug development. PMID:26862373

  6. Cyanine-based probe\\tag-peptide pair fluorescence protein imaging and fluorescence protein imaging methods

    DOEpatents

    Mayer-Cumblidge, M. Uljana; Cao, Haishi

    2013-01-15

    A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

  7. Oriented Circular Dichroism: A Method to Characterize Membrane-Active Peptides in Oriented Lipid Bilayers.

    PubMed

    Bürck, Jochen; Wadhwani, Parvesh; Fanghänel, Susanne; Ulrich, Anne S

    2016-02-16

    The structures of membrane-bound polypeptides are intimately related to their functions and may change dramatically with the lipid environment. Circular dichroism (CD) is a rapid analytical method that requires relatively low amounts of material and no labeling. Conventional CD is routinely used to monitor the secondary structure of peptides and proteins in solution, for example, in the presence of ligands and other binding partners. In the case of membrane-active peptides and transmembrane proteins, these measurements can be applied to, and remain limited to, samples containing detergent micelles or small sonicated lipid vesicles. Such traditional CD analysis reveals only secondary structures. With the help of an oriented circular dichroism (OCD) setup, however, based on the preparation of macroscopically oriented lipid bilayers, it is possible to address the membrane alignment of a peptide in addition to its conformation. This approach has been mostly used for α-helical peptides so far, but other structural elements are conceivable as well. OCD analysis relies on Moffitt's theory, which predicts that the electronic transition dipole moments of the backbone amide bonds in helical polypeptides are polarized either parallel or perpendicular to the helix axis. The interaction of the electric field vector of the circularly polarized light with these transitions results in an OCD spectrum of a membrane-bound α-helical peptide, which exhibits a characteristic line shape and reflects the angle between the helix axis and the bilayer normal. For parallel alignment of a peptide helix with respect to the membrane surface (S-state), the corresponding "fingerprint" CD band around 208 nm will exhibit maximum negative amplitude. If the helix changes its alignment via an obliquely tilted (T-state) to a fully inserted transmembrane orientation (I-state), the ellipticity at 208 nm decreases and the value approaches zero due to the decreased interactions between the field and the

  8. Protein structure prediction using hybrid AI methods

    SciTech Connect

    Guan, X.; Mural, R.J.; Uberbacher, E.C.

    1993-11-01

    This paper describes a new approach for predicting protein structures based on Artificial Intelligence methods and genetic algorithms. We combine nearest neighbor searching algorithms, neural networks, heuristic rules and genetic algorithms to form an integrated system to predict protein structures from their primary amino acid sequences. First we describe our methods and how they are integrated, and then apply our methods to several protein sequences. The results are very close to the real structures obtained by crystallography. Parallel genetic algorithms are also implemented.

  9. In silico prediction of peptide binding affinity to class I mouse major histocompatibility complexes: a comparative molecular similarity index analysis (CoMSIA) study.

    PubMed

    Hattotuwagama, Channa K; Doytchinova, Irini A; Flower, Darren R

    2005-01-01

    Current methods for the in silico identification of T cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate prediction of peptide-major histocompatibility complex (MHC) affinity. A three-dimensional quantitative structure-activity relationship (3D-QSAR) for the prediction of peptide binding to class I MHC molecules was established using the comparative molecular similarity index analysis (CoMSIA) method. Three MHC alleles were studied: H2-D(b), H2-K(b), and H2-K(k). Models were produced for each allele. Each model consisted of five physicochemical descriptors-steric bulk, electrostatic potentials, hydrophobic interactions, and hydrogen-bond donor and hydrogen-bond acceptor abilities. The models have an acceptable level of predictivity: cross-validation leave-one-out statistical terms q2 and SEP (standard error of prediction) ranged between 0.490 and 0.679 and between 0.525 and 0.889, respectively. The non-cross-validated statistical terms r2 and SEE (standard error of estimate) ranged between 0.913 and 0.979 and between 0.167 and 0.248, respectively. The use of coefficient contour maps, which indicate favored and disfavored areas for each position of the MHC-bound peptides, allowed the binding specificity of each allele to be identified, visualized, and understood. The present study demonstrates the effectiveness of CoMSIA as a method for studying peptide-MHC interactions. The peptides used in this study are available on the Internet (http://www.jenner.ac.uk/AntiJen). The partial least-squares method is available commercially in the SYBYL molecular modeling software package. PMID:16180918

  10. THE PREDICTIVE POWER OF OHL'S PRECURSOR METHOD

    SciTech Connect

    Du, Z. L.; Wang, H. N.; Li, R.

    2009-12-15

    Using linear regression techniques and correlation analysis, the predictive power of Ohl's method is shown to satisfy one of the following relationships. Either a successful prediction of cycle amplitude can be obtained if the correlation between the minimum aa geomagnetic index in the declining phase of a solar cycle and the sunspot maximum of the succeeding cycle becomes stronger, or the prediction error exceeds the expected prediction error if the correlation becomes weaker. The correlation coefficient has a declining secular variation, which leads to a weakening trend in predictive power, as well as a 44 year periodicity that may explain why the prediction method did not work well for solar cycle 23. As this finding only emerged twice in the {approx}100 year period studied, this 44 year periodicity may occur with a degree of uncertainty and may therefore need to be checked in the future. Two quantities, namely a prediction parameter and the prediction index, are proposed to analyze predictive power. Using the above properties, the success probability of a prediction result can be analyzed in advance.

  11. Bioinformatic prediction of arthropod/nematode-like peptides in non-arthropod, non-nematode members of the Ecdysozoa.

    PubMed

    Christie, Andrew E; Nolan, Daniel H; Garcia, Zachery A; McCoole, Matthew D; Harmon, Sarah M; Congdon-Jones, Benjamin; Ohno, Paul; Hartline, Niko; Congdon, Clare Bates; Baer, Kevin N; Lenz, Petra H

    2011-02-01

    The Onychophora, Priapulida and Tardigrada, along with the Arthropoda, Nematoda and several other small phyla, form the superphylum Ecdysozoa. Numerous peptidomic studies have been undertaken for both the arthropods and nematodes, resulting in the identification of many peptides from each group. In contrast, little is known about the peptides used as paracrines/hormones by species from the other ecdysozoan taxa. Here, transcriptome mining and bioinformatic peptide prediction were used to identify peptides in members of the Onychophora, Priapulida and Tardigrada, the only non-arthropod, non-nematode members of the Ecdysozoa for which there are publicly accessible expressed sequence tags (ESTs). The extant ESTs for each phylum were queried using 106 arthropod/nematode peptide precursors. Transcripts encoding calcitonin-like diuretic hormone and pigment-dispersing hormone (PDH) were identified for the onychophoran Peripatopsis sedgwicki, with transcripts encoding C-type allatostatin (C-AST) and FMRFamide-like peptide identified for the priapulid Priapulus caudatus. For the Tardigrada, transcripts encoding members of the A-type allatostatin, C-AST, insect kinin, orcokinin, PDH and tachykinin-related peptide families were identified, all but one from Hypsibius dujardini (the exception being a Milnesium tardigradum orcokinin-encoding transcript). The proteins deduced from these ESTs resulted in the prediction of 48 novel peptides, six onychophoran, eight priapulid and 34 tardigrade, which are the first described from these phyla.

  12. Bioinformatic prediction of arthropod/nematode-like peptides in non-arthropod, non-nematode members of the Ecdysozoa.

    PubMed

    Christie, Andrew E; Nolan, Daniel H; Garcia, Zachery A; McCoole, Matthew D; Harmon, Sarah M; Congdon-Jones, Benjamin; Ohno, Paul; Hartline, Niko; Congdon, Clare Bates; Baer, Kevin N; Lenz, Petra H

    2011-02-01

    The Onychophora, Priapulida and Tardigrada, along with the Arthropoda, Nematoda and several other small phyla, form the superphylum Ecdysozoa. Numerous peptidomic studies have been undertaken for both the arthropods and nematodes, resulting in the identification of many peptides from each group. In contrast, little is known about the peptides used as paracrines/hormones by species from the other ecdysozoan taxa. Here, transcriptome mining and bioinformatic peptide prediction were used to identify peptides in members of the Onychophora, Priapulida and Tardigrada, the only non-arthropod, non-nematode members of the Ecdysozoa for which there are publicly accessible expressed sequence tags (ESTs). The extant ESTs for each phylum were queried using 106 arthropod/nematode peptide precursors. Transcripts encoding calcitonin-like diuretic hormone and pigment-dispersing hormone (PDH) were identified for the onychophoran Peripatopsis sedgwicki, with transcripts encoding C-type allatostatin (C-AST) and FMRFamide-like peptide identified for the priapulid Priapulus caudatus. For the Tardigrada, transcripts encoding members of the A-type allatostatin, C-AST, insect kinin, orcokinin, PDH and tachykinin-related peptide families were identified, all but one from Hypsibius dujardini (the exception being a Milnesium tardigradum orcokinin-encoding transcript). The proteins deduced from these ESTs resulted in the prediction of 48 novel peptides, six onychophoran, eight priapulid and 34 tardigrade, which are the first described from these phyla. PMID:21074533

  13. A continuous peptide epitope reacting with pandemic influenza AH1N1 predicted by bioinformatic approaches.

    PubMed

    Carrillo-Vazquez, Jonathan P; Correa-Basurto, José; García-Machorro, Jazmin; Campos-Rodríguez, Rafael; Moreau, Violaine; Rosas-Trigueros, Jorge L; Reyes-López, Cesar A; Rojas-López, Marlon; Zamorano-Carrillo, Absalom

    2015-09-01

    Computational identification of potential epitopes with an immunogenic capacity challenges immunological research. Several methods show considerable success, and together with experimental studies, the efficiency of the algorithms to identify potential peptides with biological activity has improved. Herein, an epitope was designed by combining bioinformatics, docking, and molecular dynamics simulations. The hemagglutinin protein of the H1N1 influenza pandemic strain served as a template, owing to the interest of obtaining a scheme of immunization. Afterward, we performed enzyme-linked immunosorbent assay (ELISA) using the epitope to analyze if any antibodies in human sera before and after the influenza outbreak in 2009 recognize this peptide. Also, a plaque reduction neutralization test induced by virus-neutralizing antibodies and the IgG determination showed the biological activity of this computationally designed peptide. The results of the ELISAs demonstrated that the serum of both prepandemic and pandemic recognized the epitope. Moreover, the plaque reduction neutralization test evidenced the capacity of the designed peptide to neutralize influenza virus in Madin-Darby canine cells.

  14. A continuous peptide epitope reacting with pandemic influenza AH1N1 predicted by bioinformatic approaches.

    PubMed

    Carrillo-Vazquez, Jonathan P; Correa-Basurto, José; García-Machorro, Jazmin; Campos-Rodríguez, Rafael; Moreau, Violaine; Rosas-Trigueros, Jorge L; Reyes-López, Cesar A; Rojas-López, Marlon; Zamorano-Carrillo, Absalom

    2015-09-01

    Computational identification of potential epitopes with an immunogenic capacity challenges immunological research. Several methods show considerable success, and together with experimental studies, the efficiency of the algorithms to identify potential peptides with biological activity has improved. Herein, an epitope was designed by combining bioinformatics, docking, and molecular dynamics simulations. The hemagglutinin protein of the H1N1 influenza pandemic strain served as a template, owing to the interest of obtaining a scheme of immunization. Afterward, we performed enzyme-linked immunosorbent assay (ELISA) using the epitope to analyze if any antibodies in human sera before and after the influenza outbreak in 2009 recognize this peptide. Also, a plaque reduction neutralization test induced by virus-neutralizing antibodies and the IgG determination showed the biological activity of this computationally designed peptide. The results of the ELISAs demonstrated that the serum of both prepandemic and pandemic recognized the epitope. Moreover, the plaque reduction neutralization test evidenced the capacity of the designed peptide to neutralize influenza virus in Madin-Darby canine cells. PMID:25788327

  15. In Silico Prediction of Neuropeptides/Peptide Hormone Transcripts in the Cheilostome Bryozoan Bugula neritina

    PubMed Central

    Zhang, Gen; He, Li-Sheng; Qian, Pei-Yuan

    2016-01-01

    The bryozoan Bugula neritina has a biphasic life cycle that consists of a planktonic larval stage and a sessile juvenile/adult stage. The transition between these two stages is crucial for the development and recruitment of B. neritina. Metamorphosis in B. neritina is mediated by both the nervous system and the release of developmental signals. However, no research has been conducted to investigate the expression of neuropeptides (NP)/peptide hormones in B. neritina larvae. Here, we report a comprehensive study of the NP/peptide hormones in the marine bryozoan B. neritina based on in silico identification methods. We recovered 22 transcripts encompassing 11 NP/peptide hormone precursor transcript sequences. The transcript sequences of the 11 isolated NP precursors were validated by cDNA cloning using gene-specific primers. We also examined the expression of three peptide hormone precursor transcripts (BnFDSIG, BnILP1, BnGPB) in the coronate larvae of B. neritina, demonstrating their distinct expression patterns in the larvae. Overall, our findings serve as an important foundation for subsequent investigations of the peptidergic control of bryozoan larval behavior and settlement. PMID:27537380

  16. In Silico Prediction of Neuropeptides/Peptide Hormone Transcripts in the Cheilostome Bryozoan Bugula neritina.

    PubMed

    Wong, Yue Him; Yu, Li; Zhang, Gen; He, Li-Sheng; Qian, Pei-Yuan

    2016-01-01

    The bryozoan Bugula neritina has a biphasic life cycle that consists of a planktonic larval stage and a sessile juvenile/adult stage. The transition between these two stages is crucial for the development and recruitment of B. neritina. Metamorphosis in B. neritina is mediated by both the nervous system and the release of developmental signals. However, no research has been conducted to investigate the expression of neuropeptides (NP)/peptide hormones in B. neritina larvae. Here, we report a comprehensive study of the NP/peptide hormones in the marine bryozoan B. neritina based on in silico identification methods. We recovered 22 transcripts encompassing 11 NP/peptide hormone precursor transcript sequences. The transcript sequences of the 11 isolated NP precursors were validated by cDNA cloning using gene-specific primers. We also examined the expression of three peptide hormone precursor transcripts (BnFDSIG, BnILP1, BnGPB) in the coronate larvae of B. neritina, demonstrating their distinct expression patterns in the larvae. Overall, our findings serve as an important foundation for subsequent investigations of the peptidergic control of bryozoan larval behavior and settlement. PMID:27537380

  17. A method for the 32P labeling of peptides or peptide nucleic acid oligomers

    NASA Technical Reports Server (NTRS)

    Kozlov, I. A.; Nielsen, P. E.; Orgel, L. E.; Bada, J. L. (Principal Investigator)

    1998-01-01

    A novel approach to the radioactive labeling of peptides and PNA oligomers is described. It is based on the conjugation of a deoxynucleoside 3'-phosphate with the terminal amine of the substrate, followed by phosphorylation of the 5'-hydroxyl group of the nucleotide using T4 polynucleotide kinase and [gamma-32P]ATP.

  18. Analysis and Prediction of the Critical Regions of Antimicrobial Peptides Based on Conditional Random Fields

    PubMed Central

    Chang, Kuan Y.; Lin, Tung-pei; Shih, Ling-Yi; Wang, Chien-Kuo

    2015-01-01

    Antimicrobial peptides (AMPs) are potent drug candidates against microbes such as bacteria, fungi, parasites, and viruses. The size of AMPs ranges from less than ten to hundreds of amino acids. Often only a few amino acids or the critical regions of antimicrobial proteins matter the functionality. Accurately predicting the AMP critical regions could benefit the experimental designs. However, no extensive analyses have been done specifically on the AMP critical regions and computational modeling on them is either non-existent or settled to other problems. With a focus on the AMP critical regions, we thus develop a computational model AMPcore by introducing a state-of-the-art machine learning method, conditional random fields. We generate a comprehensive dataset of 798 AMPs cores and a low similarity dataset of 510 representative AMP cores. AMPcore could reach a maximal accuracy of 90% and 0.79 Matthew’s correlation coefficient on the comprehensive dataset and a maximal accuracy of 83% and 0.66 MCC on the low similarity dataset. Our analyses of AMP cores follow what we know about AMPs: High in glycine and lysine, but low in aspartic acid, glutamic acid, and methionine; the abundance of α-helical structures; the dominance of positive net charges; the peculiarity of amphipathicity. Two amphipathic sequence motifs within the AMP cores, an amphipathic α-helix and an amphipathic π-helix, are revealed. In addition, a short sequence motif at the N-terminal boundary of AMP cores is reported for the first time: arginine at the P(-1) coupling with glycine at the P1 of AMP cores occurs the most, which might link to microbial cell adhesion. PMID:25803302

  19. PChopper: high throughput peptide prediction for MRM/SRM transition design

    PubMed Central

    2011-01-01

    Background The use of selective reaction monitoring (SRM) based LC-MS/MS analysis for the quantification of phosphorylation stoichiometry has been rapidly increasing. At the same time, the number of sites that can be monitored in a single LC-MS/MS experiment is also increasing. The manual processes associated with running these experiments have highlighted the need for computational assistance to quickly design MRM/SRM candidates. Results PChopper has been developed to predict peptides that can be produced via enzymatic protein digest; this includes single enzyme digests, and combinations of enzymes. It also allows digests to be simulated in 'batch' mode and can combine information from these simulated digests to suggest the most appropriate enzyme(s) to use. PChopper also allows users to define the characteristic of their target peptides, and can automatically identify phosphorylation sites that may be of interest. Two application end points are available for interacting with the system; the first is a web based graphical tool, and the second is an API endpoint based on HTTP REST. Conclusions Service oriented architecture was used to rapidly develop a system that can consume and expose several services. A graphical tool was built to provide an easy to follow workflow that allows scientists to quickly and easily identify the enzymes required to produce multiple peptides in parallel via enzymatic digests in a high throughput manner. PMID:21838934

  20. Folding peptides and proteins with all-atom physics: methods and applications

    NASA Astrophysics Data System (ADS)

    Shell, M. Scott

    2008-03-01

    Computational methods offer powerful tools for investigating proteins and peptides at the molecular-level; however, it has proven challenging to reproduce the long time scale folding processes of these molecules at a level that is both faithful to the atomic driving forces and attainable with modern commodity cluster computing. Alternatively, the past decade has seen significant progress in using bioinformatics-based approaches to infer the three dimensional native structures of proteins, drawing upon extensive knowledge databases of known protein structures [1]. These methods work remarkably well when a homologous protein can be found to provide a structural template for a candidate sequence. However, in cases where homology to database proteins is low, where the folding pathway is of interest, or where conformational flexibility is substantial---as in many emerging protein and peptide technologies---bioinformatics methods perform poorly. There is therefore great interest in seeing purely physics-based approaches succeed. We discuss a purely physics-based, database-free folding method, relying on proper thermal sampling (replica exchange molecular dynamics) and molecular potential energy functions. In order to surmount the tremendous computational demands of all-atom folding simulations, our approach implements a conformational search strategy based on a putative protein folding mechanism called zipping and assembly [2-4]. That is, we explicitly seek out potential folding pathways inferred from short simulations, and iteratively pursue all such routes by coaxing a polypeptide chain along them. The method is called the Zipping and Assembly Method (ZAM) and it works in two parts: (1) the full polypeptide chain is broken into small fragments that are first simulated independently and then successively re-assembled into larger segments with further sampling, and (2) consistently stable structure in fragments is detected and locked into place, in order to avoid re

  1. Quantum chemical calculations predict biological function: the case of T cell receptor interaction with a peptide/MHC class I

    PubMed Central

    Antipas, Georgios S. E.; Germenis, Anastasios E.

    2015-01-01

    A combination of atomic correlation statistics and quantum chemical calculations are shown to predict biological function. In the present study, various antigenic peptide-Major Histocompatibility Complex (pMHC) ligands with near-identical stereochemistries, in complexation with the same T cell receptor (TCR), were found to consistently induce distinctly different quantum chemical behavior, directly dependent on the peptide's electron spin density and intrinsically expressed by the protonation state of the peptide's N-terminus. Furthermore, the cumulative coordination difference of any variant in respect to the native peptide was found to accurately reflect peptide biological function and immerges as the physical observable which is directly related to the immunological end-effect of pMHC-TCR interaction. PMID:25713797

  2. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  3. Computational Prediction of Immunodominant Epitopes on Outer Membrane Protein (Omp) H of Pasteurella multocida Toward Designing of a Peptide Vaccine.

    PubMed

    Ganguly, Bhaskar

    2016-01-01

    Contemporary vaccine design necessitates discrimination between the immunogenic and non-immunogenic components within a pathogen. To successfully target a humoral immune response, the vaccine antigen should contain not only B-cell epitopes but abounding Th-cell agretopes and MHC-II binding regions as well. No single computational method is available that allows the identification of such regions on antigens with good reliability. A consensus approach based on several prediction methods can be adopted to overcome this problem.Targeting the outer membrane protein (Omp) H as a candidate, a comprehensive work flow is described for the computational identification of immunodominant epitopes toward the designing of a peptide vaccine against Pasteurella multocida. PMID:27076289

  4. Peptide YY and ghrelin predict craving and risk for relapse in abstinent smokers.

    PubMed

    al'Absi, Mustafa; Lemieux, Andrine; Nakajima, Motohiro

    2014-11-01

    Appetite hormones are directly involved in regulating satiety, energy expenditure, and food intake, and accumulating evidence suggests their involvement in regulating reward and craving for drugs. This study investigated the ability of peptide YY (PYY) and ghrelin during the initial 24-48 h of a smoking cessation attempt to predict smoking relapse at 4 weeks. Multiple regression analysis indicated that increased PYY was associated with decreased reported craving and increased positive affect. Cox proportional hazard models showed that higher ghrelin levels predicted increased risk of smoking relapse (hazard ratio=2.06, 95% CI=1.30-3.27). These results indicate that circulating PYY may have buffering effects during the early stages of cessation while ghrelin may confer increased risk of smoking relapse. Further investigation of the links between these hormones and nicotine dependence is warranted.

  5. MHCPred: A server for quantitative prediction of peptide-MHC binding.

    PubMed

    Guan, Pingping; Doytchinova, Irini A; Zygouri, Christianna; Flower, Darren R

    2003-07-01

    Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-based multivariate statistical approach to the quantitative prediction of peptide binding to major histocom- patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401 and HLA-DRB*0701). MHCPred is available from the URL: http://www.jenner.ac.uk/MHCPred. PMID:12824380

  6. Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment.

    PubMed

    Carrasco Pro, S; Zimic, M; Nielsen, M

    2014-02-01

    Major histocompatibility complex (MHC) molecules play a key role in cell-mediated immune responses presenting bounded peptides for recognition by the immune system cells. Several in silico methods have been developed to predict the binding affinity of a given peptide to a specific MHC molecule. One of the current state-of-the-art methods for MHC class I is NetMHCpan, which has a core ingredient for the representation of the MHC class I molecule using a pseudo-sequence representation of the binding cleft amino acid environment. New and large MHC-peptide-binding data sets are constantly being made available, and also new structures of MHC class I molecules with a bound peptide have been published. In order to test if the NetMHCpan method can be improved by integrating this novel information, we created new pseudo-sequence definitions for the MHC-binding cleft environment from sequence and structural analyses of different MHC data sets including human leukocyte antigen (HLA), non-human primates (chimpanzee, macaque and gorilla) and other animal alleles (cattle, mouse and swine). From these constructs, we showed that by focusing on MHC sequence positions found to be polymorphic across the MHC molecules used to train the method, the NetMHCpan method achieved a significant increase in the predictive performance, in particular, of non-human MHCs. This study hence showed that an improved performance of MHC-binding methods can be achieved not only by the accumulation of more MHC-peptide-binding data but also by a refined definition of the MHC-binding environment including information from non-human species. PMID:24447175

  7. Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection.

    PubMed

    Valdivia-Olarte, Hugo; Requena, David; Ramirez, Manuel; Saravia, Luis E; Izquierdo, Ray; Falconi-Agapito, Francesca; Zavaleta, Milagros; Best, Iván; Fernández-Díaz, Manolo; Zimic, Mirko

    2015-01-01

    Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken.

  8. Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection

    PubMed Central

    Valdivia-Olarte, Hugo; Requena, David; Ramirez, Manuel; Saravia, Luis E; Izquierdo, Ray; Falconi-Agapito, Francesca; Zavaleta, Milagros; Best, Iván; Fernández-Díaz, Manolo; Zimic, Mirko

    2015-01-01

    Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken. PMID:26664030

  9. B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies

    PubMed Central

    Sinner, Moritz F.; Stepas, Katherine A.; Moser, Carlee B.; Krijthe, Bouwe P.; Aspelund, Thor; Sotoodehnia, Nona; Fontes, João D.; Janssens, A. Cecile J.W.; Kronmal, Richard A.; Magnani, Jared W.; Witteman, Jacqueline C.; Chamberlain, Alanna M.; Lubitz, Steven A.; Schnabel, Renate B.; Vasan, Ramachandran S.; Wang, Thomas J.; Agarwal, Sunil K.; McManus, David D.; Franco, Oscar H.; Yin, Xiaoyan; Larson, Martin G.; Burke, Gregory L.; Launer, Lenore J.; Hofman, Albert; Levy, Daniel; Gottdiener, John S.; Kääb, Stefan; Couper, David; Harris, Tamara B.; Astor, Brad C.; Ballantyne, Christie M.; Hoogeveen, Ron C.; Arai, Andrew E.; Soliman, Elsayed Z.; Ellinor, Patrick T.; Stricker, Bruno H.C.; Gudnason, Vilmundur; Heckbert, Susan R.; Pencina, Michael J.; Benjamin, Emelia J.; Alonso, Alvaro

    2014-01-01

    Aims B-type natriuretic peptide (BNP) and C-reactive protein (CRP) predict atrial fibrillation (AF) risk. However, their risk stratification abilities in the broad community remain uncertain. We sought to improve risk stratification for AF using biomarker information. Methods and results We ascertained AF incidence in 18 556 Whites and African Americans from the Atherosclerosis Risk in Communities Study (ARIC, n=10 675), Cardiovascular Health Study (CHS, n = 5043), and Framingham Heart Study (FHS, n = 2838), followed for 5 years (prediction horizon). We added BNP (ARIC/CHS: N-terminal pro-B-type natriuretic peptide; FHS: BNP), CRP, or both to a previously reported AF risk score, and assessed model calibration and predictive ability [C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI)]. We replicated models in two independent European cohorts: Age, Gene/Environment Susceptibility Reykjavik Study (AGES), n = 4467; Rotterdam Study (RS), n = 3203. B-type natriuretic peptide and CRP were significantly associated with AF incidence (n = 1186): hazard ratio per 1-SD ln-transformed biomarker 1.66 [95% confidence interval (CI), 1.56–1.76], P < 0.0001 and 1.18 (95% CI, 1.11–1.25), P < 0.0001, respectively. Model calibration was sufficient (BNP, χ2 = 17.0; CRP, χ2 = 10.5; BNP and CRP, χ2 = 13.1). B-type natriuretic peptide improved the C-statistic from 0.765 to 0.790, yielded an IDI of 0.027 (95% CI, 0.022–0.032), a relative IDI of 41.5%, and a continuous NRI of 0.389 (95% CI, 0.322–0.455). The predictive ability of CRP was limited (C-statistic increment 0.003). B-type natriuretic peptide consistently improved prediction in AGES and RS. Conclusion B-type natriuretic peptide, not CRP, substantially improved AF risk prediction beyond clinical factors in an independently replicated, heterogeneous population. B-type natriuretic peptide may serve as a benchmark to evaluate novel putative AF risk biomarkers. PMID:25037055

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

    PubMed Central

    Kundu, Kousik; Costa, Fabrizio; Backofen, Rolf

    2013-01-01

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

  11. Cephalometric methods of prediction in orthognathic surgery.

    PubMed

    Kolokitha, Olga-Elpis; Topouzelis, Nikolaos

    2011-09-01

    Over the past decade the growing number of adult patients seeking for orthodontic treatment made orthognathic surgery popular. Surgical and orthodontic techniques have developed to the point where combined orthodontic and surgical treatment is now feasible to manage dentofacial deformity problems very satisfactorily. The prediction of orthognathic treatment outcome is an important part of orthognathic planning and the process of patient' inform consent. The predicted results must be presented to the patients prior to treatment in order to assess the treatment's feasibility, optimize case management and increase patient understanding and acceptance of the recommended treatment. Cephalometrics is a routine part of the diagnosis and treatment planning process and also allows the clinician to evaluate changes following orthognathic surgery. Traditionally cephalometry has been employed manually; nowadays computerized cephalometric systems are very popular. Cephalometric prediction in orthognathic surgery can be done manually or by computers, using several currently available software programs, alone or in combination with video images. Both manual and computerized cephalometric prediction methods are two-dimensional and cannot fully describe three-dimensional phenomena. Today, three-dimensional prediction methods are available, such as three-dimensional computerized tomography (3DCT), 3D magnetic resonance imaging (3DMRI) and surface scan/cone-beam CT. The aim of this article is to present and discuss the different methods of cephalometric prediction of the orthognathic surgery outcome.

  12. Effectiveness of computational methods in haplotype prediction.

    PubMed

    Xu, Chun-Fang; Lewis, Karen; Cantone, Kathryn L; Khan, Parveen; Donnelly, Christine; White, Nicola; Crocker, Nikki; Boyd, Pete R; Zaykin, Dmitri V; Purvis, Ian J

    2002-02-01

    Haplotype analysis has been used for narrowing down the location of disease-susceptibility genes and for investigating many population processes. Computational algorithms have been developed to estimate haplotype frequencies and to predict haplotype phases from genotype data for unrelated individuals. However, the accuracy of such computational methods needs to be evaluated before their applications can be advocated. We have experimentally determined the haplotypes at two loci, the N-acetyltransferase 2 gene ( NAT2, 850 bp, n=81) and a 140-kb region on chromosome X ( n=77), each consisting of five single nucleotide polymorphisms (SNPs). We empirically evaluated and compared the accuracy of the subtraction method, the expectation-maximization (EM) method, and the PHASE method in haplotype frequency estimation and in haplotype phase prediction. Where there was near complete linkage disequilibrium (LD) between SNPs (the NAT2 gene), all three methods provided effective and accurate estimates for haplotype frequencies and individual haplotype phases. For a genomic region in which marked LD was not maintained (the chromosome X locus), the computational methods were adequate in estimating overall haplotype frequencies. However, none of the methods was accurate in predicting individual haplotype phases. The EM and the PHASE methods provided better estimates for overall haplotype frequencies than the subtraction method for both genomic regions.

  13. A novel method to measure HLA-DM-susceptibility of peptides bound to MHC class II molecules based on peptide binding competition assay and differential IC(50) determination.

    PubMed

    Yin, Liusong; Stern, Lawrence J

    2014-04-01

    HLA-DM (DM) functions as a peptide editor that mediates the exchange of peptides loaded onto MHCII molecules by accelerating peptide dissociation and association kinetics. The relative DM-susceptibility of peptides bound to MHCII molecules correlates with antigen presentation and immunodominance hierarchy, and measurement of DM-susceptibility has been a key effort in this field. Current assays of DM-susceptibility, based on differential peptide dissociation rates measured for individually labeled peptides over a long time base, are difficult and cumbersome. Here, we present a novel method to measure DM-susceptibility based on peptide binding competition assays performed in the presence and absence of DM, reported as a delta-IC(50) (change in 50% inhibition concentration) value. We simulated binding competition reactions of peptides with various intrinsic and DM-catalyzed kinetic parameters and found that under a wide range of conditions the delta-IC(50) value is highly correlated with DM-susceptibility as measured in off-rate assay. We confirmed experimentally that DM-susceptibility measured by delta-IC(50) is comparable to that measured by traditional off-rate assay for peptides with known DM-susceptibility hierarchy. The major advantage of this method is that it allows simple, fast and high throughput measurement of DM-susceptibility for a large set of unlabeled peptides in studies of the mechanism of DM action and for identification of CD4+ T cell epitopes.

  14. Chemical methods for producing disulfide bonds in peptides and proteins to study folding regulation.

    PubMed

    Okumura, Masaki; Shimamoto, Shigeru; Hidaka, Yuji

    2014-04-01

    Disulfide bonds play a critical role in the folding of secretory and membrane proteins. Oxidative folding reactions of disulfide bond-containing proteins typically require several hours or days, and numerous misbridged disulfide isomers are often observed as intermediates. The rate-determining step in refolding is thought to be the disulfide-exchange reaction from nonnative to native disulfide bonds in folding intermediates, which often precipitate during the refolding process because of their hydrophobic properties. To overcome this, chemical additives or a disulfide catalyst, protein disulfide isomerase (PDI), are generally used in refolding experiments to regulate disulfide-coupled peptide and protein folding. This unit describes such methods in the context of the thermodynamic and kinetic control of peptide and protein folding, including (1) regulation of disulfide-coupled peptides and protein folding assisted by chemical additives, (2) reductive unfolding of disulfide-containing peptides and proteins, and (3) regulation of disulfide-coupled peptide and protein folding using PDI.

  15. Novel method to identify the optimal antimicrobial peptide in a combination matrix, using anoplin as an example.

    PubMed

    Munk, J K; Ritz, C; Fliedner, F P; Frimodt-Møller, N; Hansen, P R

    2014-01-01

    Microbial resistance is an increasing health concern and a true danger to human well-being. A worldwide search for new compounds is ongoing, and antimicrobial peptides are promising lead candidates for tomorrow's antibiotics. The decapeptide anoplin (GLLKRIKTLL-NH2) is an especially interesting candidate because of its small size as well as its antimicrobial and nonhemolytic properties. Optimization of the properties of an antimicrobial peptide such as anoplin requires multidimensional searching in a complex chemical space. Typically, such optimization is performed by labor-intensive and costly trial-and-error methods. In this study, we show the benefit of fractional factorial design for identification of the optimal antimicrobial peptide in a combination matrix. We synthesized and analyzed a training set of 12 anoplin analogs, representative of 64 analogs in total. Using MIC, hemolysis, and high-performance liquid chromatography retention time data, we constructed analysis-of-variance models that describe the relationship between these properties and the structural characteristics of the analogs. We show that the mathematical models derived from the training set data can be used to predict the properties of other analogs in the chemical space. Hence, this method provides an efficient means of identification of the optimal peptide in the searched chemical space.

  16. Self-assembling peptide amphiphiles and related methods for growth factor delivery

    DOEpatents

    Stupp, Samuel I.; Donners, Jack J. J. M.; Silva, Gabriel A.; Behanna, Heather A.; Anthony, Shawn G.

    2009-06-09

    Amphiphilic peptide compounds comprising one or more epitope sequences for binding interaction with one or more corresponding growth factors, micellar assemblies of such compounds and related methods of use.

  17. Self-assembling peptide amphiphiles and related methods for growth factor delivery

    DOEpatents

    Stupp, Samuel I.; Donners, Jack J. J. M.; Silva, Gabriel A.; Behanna, Heather A.; Anthony, Shawn G.

    2012-03-20

    Amphiphilic peptide compounds comprising one or more epitope sequences for binding interaction with one or more corresponding growth factors, micellar assemblies of such compounds and related methods of use.

  18. Self-assembling peptide amphiphiles and related methods for growth factor delivery

    DOEpatents

    Stupp, Samuel I; Donners, Jack J.J.M.; Silva, Gabriel A; Behanna, Heather A; Anthony, Shawn G

    2013-11-12

    Amphiphilic peptide compounds comprising one or more epitope sequences for binding interaction with one or more corresponding growth factors, micellar assemblies of such compounds and related methods of use.

  19. Novel hyperspectral prediction method and apparatus

    NASA Astrophysics Data System (ADS)

    Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

    2009-05-01

    Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

  20. A peptide N-terminal protection strategy for comprehensive glycoproteome analysis using hydrazide chemistry based method.

    PubMed

    Huang, Junfeng; Qin, Hongqiang; Sun, Zhen; Huang, Guang; Mao, Jiawei; Cheng, Kai; Zhang, Zhang; Wan, Hao; Yao, Yating; Dong, Jing; Zhu, Jun; Wang, Fangjun; Ye, Mingliang; Zou, Hanfa

    2015-05-11

    Enrichment of glycopeptides by hydrazide chemistry (HC) is a popular method for glycoproteomics analysis. However, possible side reactions of peptide backbones during the glycan oxidation in this method have not been comprehensively studied. Here, we developed a proteomics approach to locate such side reactions and found several types of the side reactions that could seriously compromise the performance of glycoproteomics analysis. Particularly, the HC method failed to identify N-terminal Ser/Thr glycopeptides because the oxidation of vicinal amino alcohol on these peptides generates aldehyde groups and after they are covalently coupled to HC beads, these peptides cannot be released by PNGase F for identification. To overcome this drawback, we apply a peptide N-terminal protection strategy in which primary amine groups on peptides are chemically blocked via dimethyl labeling, thus the vicinal amino alcohols on peptide N-termini are eliminated. Our results showed that this strategy successfully prevented the oxidation of peptide N-termini and significantly improved the coverage of glycoproteome.

  1. A peptide N-terminal protection strategy for comprehensive glycoproteome analysis using hydrazide chemistry based method

    PubMed Central

    Huang, Junfeng; Qin, Hongqiang; Sun, Zhen; Huang, Guang; Mao, Jiawei; Cheng, Kai; Zhang, Zhang; Wan, Hao; Yao, Yating; Dong, Jing; Zhu, Jun; Wang, Fangjun; Ye, Mingliang; Zou, Hanfa

    2015-01-01

    Enrichment of glycopeptides by hydrazide chemistry (HC) is a popular method for glycoproteomics analysis. However, possible side reactions of peptide backbones during the glycan oxidation in this method have not been comprehensively studied. Here, we developed a proteomics approach to locate such side reactions and found several types of the side reactions that could seriously compromise the performance of glycoproteomics analysis. Particularly, the HC method failed to identify N-terminal Ser/Thr glycopeptides because the oxidation of vicinal amino alcohol on these peptides generates aldehyde groups and after they are covalently coupled to HC beads, these peptides cannot be released by PNGase F for identification. To overcome this drawback, we apply a peptide N-terminal protection strategy in which primary amine groups on peptides are chemically blocked via dimethyl labeling, thus the vicinal amino alcohols on peptide N-termini are eliminated. Our results showed that this strategy successfully prevented the oxidation of peptide N-termini and significantly improved the coverage of glycoproteome. PMID:25959593

  2. The investigation of the secondary structures of various peptide sequences of β-casein by the multicanonical simulation method

    NASA Astrophysics Data System (ADS)

    Yaşar, F.; Çelik, S.; Köksel, H.

    2006-05-01

    The structural properties of Arginine-Glutamic acid-Leucine-Glutamic acid-Glutamic acid-Leucine-Asparagine-Valine-Proline-Glycine (RELEELNVPG, in one letter code), Glutamic acid-Glutamic acid-Glutamine-Glutamine-Glutamine-Threonine-Glutamic acid (EEQQQTE) and Glutamic acid-Aspartic acid-Glutamic acid-Leucine-Glutamine-Aspartic acid-Lysine-Isoleucine (EDELQDKI) peptide sequences of β-casein were studied by three-dimensional molecular modeling. In this work, the three-dimensional conformations of each peptide from their primary sequences were obtained by multicanonical simulations. With using major advantage of this simulation technique, Ramachandran plots were prepared and analysed to predict the relative occurrence probabilities of β-turn, γ-turn and helical structures. Structural predictions of these sequences of β-casein molecule indicate the presence of high level of helical structures and βIII-turns. The occurrence probabilities of inverse and classical β-turns were low. The probability of helical structure of each sequence significantly decreased when the temperature increased. Our results show these peptides have highly helical structure and better agreement with the results of spectroscopic techniques and other prediction methods.

  3. Model for Vaccine Design by Prediction of B-Epitopes of IEDB Given Perturbations in Peptide Sequence, In Vivo Process, Experimental Techniques, and Source or Host Organisms

    PubMed Central

    González-Díaz, Humberto; Pérez-Montoto, Lázaro G.; Ubeira, Florencio M.

    2014-01-01

    Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design. PMID:24741624

  4. Predicting the composition of red wine blends using an array of multicomponent Peptide-based sensors.

    PubMed

    Ghanem, Eman; Hopfer, Helene; Navarro, Andrea; Ritzer, Maxwell S; Mahmood, Lina; Fredell, Morgan; Cubley, Ashley; Bolen, Jessica; Fattah, Rabia; Teasdale, Katherine; Lieu, Linh; Chua, Tedmund; Marini, Federico; Heymann, Hildegarde; Anslyn, Eric V

    2015-01-01

    Differential sensing using synthetic receptors as mimics of the mammalian senses of taste and smell is a powerful approach for the analysis of complex mixtures. Herein, we report on the effectiveness of a cross-reactive, supramolecular, peptide-based sensing array in differentiating and predicting the composition of red wine blends. Fifteen blends of Cabernet Sauvignon, Merlot and Cabernet Franc, in addition to the mono varietals, were used in this investigation. Linear Discriminant Analysis (LDA) showed a clear differentiation of blends based on tannin concentration and composition where certain mono varietals like Cabernet Sauvignon seemed to contribute less to the overall characteristics of the blend. Partial Least Squares (PLS) Regression and cross validation were used to build a predictive model for the responses of the receptors to eleven binary blends and the three mono varietals. The optimized model was later used to predict the percentage of each mono varietal in an independent test set composted of four tri-blends with a 15% average error. A partial least square regression model using the mouth-feel and taste descriptive sensory attributes of the wine blends revealed a strong correlation of the receptors to perceived astringency, which is indicative of selective binding to polyphenols in wine. PMID:26007178

  5. Prediction of the effect on antihyperglycaemic action of sitagliptin by plasma active form glucagon-like peptide-1

    PubMed Central

    Kushiyama, Akifumi; Kikuchi, Takako; Tanaka, Kentaro; Tahara, Tazu; Takao, Toshiko; Onishi, Yukiko; Yoshida, Yoko; Kawazu, Shoji; Iwamoto, Yasuhiko

    2016-01-01

    AIM: To investigate whether active glucagon-like peptide-1 (GLP-1) is a prediction Factor of Effect of sitagliptin on patients with type 2 diabetes mellitus (GLP-1 FEST:UMIN000010645). METHODS: Seventy-six patients with type 2 diabetes, who had insufficient glycemic control [Hemoglobin A1c (HbA1c) ≥ 7%] in spite of treatment with metformin and/or sulfonylurea, were included in the investigation. Patients were divided into three groups by tertiles of fasting plasma active GLP-1 level, before the administration of 50 mg sitagliptin. RESULTS: At baseline, body mass index, serum UA, insulin and HOMA-IR were higher in the high active GLP-1 group than in the other two groups. The high active GLP-1 group did not show any decline of HbA1c (7.6% ± 1.4% to 7.5% ± 1.5%), whereas the middle and low groups indicated significant decline of HbA1c (7.4 ± 0.7 to 6.8 ± 0.6 and 7.4 ± 1.2 to 6.9 ± 1.3, respectively) during six months. Only the low and middle groups showed a significant increment of active GLP-1, C-peptide level, a decreased log and proinsulin/insulin ratio after administration. In logistic analysis, the low or middle group is a significant explanatory variable for an HbA1c decrease of ≥ 0.5%, and its odds ratio is 4.5 (1.40-17.6) (P = 0.01) against the high active GLP-1 group. This remains independent when adjusted for HbA1c level before administration, patients’ medical history, medications, insulin secretion and insulin resistance. CONCLUSION: Plasma fasting active GLP-1 is an independent predictive marker for the efficacy of dipeptidyl peptidase 4 inhibitor sitagliptin. PMID:27326345

  6. A Method for Selective Enrichment and Analysis of Nitrotyrosine-Containing Peptides in Complex Proteome Samples

    SciTech Connect

    Zhang, Qibin; Qian, Weijun; Knyushko, Tanya V.; Clauss, Therese RW; Purvine, Samuel O.; Moore, Ronald J.; Sacksteder, Colette A.; Chin, Mark H.; Smith, Desmond J.; Camp, David G.; Bigelow, Diana J.; Smith, Richard D.

    2007-06-01

    Elevated levels of protein tyrosine nitration have been found in various neurodegenerative diseases and aging related pathologies; however, the lack of an efficient enrichment method has prevented the analysis of this important low level protein modification. We have developed an efficient method for specific enrichment of nitrotyrosine containing peptides that permits nitrotyrosine peptides and specific nitration sites to be unambiguously identified with LC-MS/MS. The method is based on the derivatization of nitrotyrosine into free sulfhydryl groups followed by high efficiency enrichment of sulfhydryl-containing peptides with thiopropyl sepharose beads. The derivatization process starts with acetylation with acetic anhydride to block all primary amines, followed by reduction of nitrotyrosine to aminotyrosine, then derivatization of aminotyrosine with N-Succinimidyl S-Acetylthioacetate (SATA), and finally deprotecting of S-acetyl on SATA to form free sulfhydryl groups. This method was evaluated using nitrotyrosine containing peptides, in-vitro nitrated human histone 1.2, and bovine serum albumin (BSA). 91% and 62% of the identified peptides from enriched histone and BSA samples were nitrotyrosine derivatized peptides, respectively, suggesting relative high specificity of the enrichment method. The application of this method to in-vitro nitrated mouse brain homogenate resulted in 35% of identified peptides containing nitrotyrosine (compared to only 5.9% observed from the global analysis of unenriched sample), and a total of 150 unique nitrated peptides covering 102 proteins were identified with a false discovery rate estimated at 3.3% from duplicate LC-MS/MS analyses of a single enriched sample.

  7. Quantitative Evaluation of Peptide-Material Interactions by a Force Mapping Method: Guidelines for Surface Modification.

    PubMed

    Mochizuki, Masahito; Oguchi, Masahiro; Kim, Seong-Oh; Jackman, Joshua A; Ogawa, Tetsu; Lkhamsuren, Ganchimeg; Cho, Nam-Joon; Hayashi, Tomohiro

    2015-07-28

    Peptide coatings on material surfaces have demonstrated wide application across materials science and biotechnology, facilitating the development of nanobio interfaces through surface modification. A guiding motivation in the field is to engineer peptides with a high and selective binding affinity to target materials. Herein, we introduce a quantitative force mapping method in order to evaluate the binding affinity of peptides to various hydrophilic oxide materials by atomic force microscopy (AFM). Statistical analysis of adhesion forces and probabilities obtained on substrates with a materials contrast enabled us to simultaneously compare the peptide binding affinity to different materials. On the basis of the experimental results and corresponding theoretical analysis, we discuss the role of various interfacial forces in modulating the strength of peptide attachment to hydrophilic oxide solid supports as well as to gold. The results emphasize the precision and robustness of our approach to evaluating the adhesion strength of peptides to solid supports, thereby offering guidelines to improve the design and fabrication of peptide-coated materials.

  8. B-Type Natriuretic Peptide Levels Predict Ventricular Arrhythmia Post Left Ventricular Assist Device Implantation.

    PubMed

    Hellman, Yaron; Malik, Adnan S; Lin, Hongbo; Shen, Changyu; Wang, I-Wen; Wozniak, Thomas C; Hashmi, Zubair A; Pickrell, Jeanette; Jani, Milena; Caccamo, Marco A; Gradus-Pizlo, Irmina; Hadi, Azam

    2015-12-01

    B-type natriuretic peptide (BNP) levels have been shown to predict ventricular arrhythmia (VA) and sudden death in patients with heart failure. We sought to determine whether BNP levels before left ventricular assist device (LVAD) implantation can predict VA post LVAD implantation in advanced heart failure patients. We conducted a retrospective study consisting of patients who underwent LVAD implantation in our institution during the period of May 2009-March 2013. The study was limited to patients receiving a HeartMate II or HeartWare LVAD. Acute myocardial infarction patients were excluded. We compared between the patients who developed VA within 15 days post LVAD implantation to the patients without VA. A total of 85 patients underwent LVAD implantation during the study period. Eleven patients were excluded (five acute MI, four without BNP measurements, and two discharged earlier than 13 days post LVAD implantation). The incidence of VA was 31%, with 91% ventricular tachycardia (VT) and 9% ventricular fibrillation. BNP remained the single most powerful predictor of VA even after adjustment for other borderline significant factors in a multivariate logistic regression model (P < 0.05). BNP levels are a strong predictor of VA post LVAD implantation, surpassing previously described risk factors such as age and VT in the past. PMID:25864448

  9. Mode matches in hydrophobic free energy eigenfunctions predict peptide-protein interactions.

    PubMed

    Mandell, A J; Owens, M J; Selz, K A; Morgan, W N; Shlesinger, M F; Nemeroff, C B

    1998-08-01

    The dominant statistical hydrophobic free energy inverse frequencies amino acid wavelengths as hydrophobic modes, of neurotensin (NT), cholescystokinin (CCK), the human dopamine D2 receptor [(DA)D2], and the human dopamine transporter (DAT) were determined using orthogonal decomposition of the autocovariance matrices of their amino acid sequences as hydrophobic free energy equivalents in kcal/mol. The leading eigenvalues-associated eigenvectors were convolved with the original series to construct eigenfunctions. Eigenfunctions were further analyzed using discrete trigonometric wavelet and all poles, maximum entropy power spectral transformations. This yielded clean representations of the dominant hydrophobic free energy modes, most of which are otherwise lost in the smoothing of hydropathy plots or contaminated by end effects and multimodality in conventional Fourier transformations. Mode matches were found between NT and (DA)D2 and between CCK and DAT, but not the converse. These mode matches successfully predicted the nonlinear kinetic interactions of NT-(DA)D2 in contrast with CCK-(DA) D2 on 3H-spiperone binding to (DA) D2, and by CCK-DAT but not NT-DAT on [N-methyl-3H]-WIN 35,428 binding to DAT in (DA)D2 and DAT cDNA stably transfected cell lines without known NT or CCK receptors. Computation of the dominant modes of hydrophobic free energy eigenfunctions may help predict functionally relevant peptide-membrane protein interactions, even across neurotransmitter families. PMID:9664843

  10. BactPepDB: a database of predicted peptides from a exhaustive survey of complete prokaryote genomes

    PubMed Central

    Rey, Julien; Deschavanne, Patrick; Tuffery, Pierre

    2014-01-01

    With the recent progress in complete genome sequencing, mining the increasing amount of genomic information available should in theory provide the means to discover new classes of peptides. However, annotation pipelines often do not consider small reading frames likely to be expressed. BactPepDB, available online at http://bactpepdb.rpbs.univ-paris-diderot.fr, is a database that aims at providing an exhaustive re-annotation of all complete prokaryotic genomes—chromosomal and plasmid DNA—available in RefSeq for coding sequences ranging between 10 and 80 amino acids. The identified peptides are classified as (i) previously identified in RefSeq, (ii) entity-overlapping (intragenic) or intergenic, and (iii) potential pseudogenes—intergenic sequences corresponding to a portion of a previously annotated larger gene. Additional information is related to homologs within order, predicted signal sequence, transmembrane segments, disulfide bonds, secondary structure, and the existence of a related 3D structure in the Protein Databank. As a result, BactPepDB provides insights about candidate peptides, and provides information about their conservation, together with some of their expected biological/structural features. The BactPepDB interface allows to search for candidate peptides in the database, or to search for peptides similar to a query, according to the multiple properties predicted or related to genomic localization. Database URL: http://www.yeastgenome.org/ PMID:25377257

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-07-01

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

  13. Immunologic methods for quantitative estimation of small peptides and their application to bradykinin.

    PubMed

    Anumula, K R; Schulz, R; Back, N

    1990-12-31

    A simple strategy was developed for the immunologic quantitative determination of small, biologically active peptides utilizing bradykinin (BK) as the model peptide prototype. Methods were developed for the preparation of a peptide-carrier complex suitable for immunization and for immobilization of peptides onto the plastic surface of enzyme-linked immunosorbent assay (ELISA) plates. An avidin-bound biotinylated peptide complex was used for raising peptide antibodies with high titers (1:4000) in the rabbit. The peptide BK was coupled to synthetic polymeric carriers poly-D-lysine (PL) and poly-D-lysine-succinylated (PLS) via the BK carboxy and amino terminus, respectively, with the aid of a water soluble carbodiimide. These carriers with antigen peptide side chains as well as avidin-biotinyl-peptide complexes were efficient surface immobilizing reagents for microwell plastic plates used in the detection of kinins by ELISA. Monoclonal antibodies reacted competitively with kinins in plates coated with either PL-BK or PLS-BK. In contrast, rabbit (polyclonal) antibodies reacted specifically in the plates coated with PLS-BK but only a non-specific reaction could be obtained with the PL-BK coated plates (i.e., could not be displaced with BK). Based on results using synthetic BK analogues, the carboxy terminal half of the BK molecule appears to be the stronger antigenic determinant in both mouse and rabbit systems. The polyclonal antibodies demonstrated a greater affinity to bradykinin compared to the monoclonal antibodies. Their use improved the sensitivity of the ELISA for kinin determination by one order of magnitude. Kinin levels determined in plasma tryptic digests by ELISA with the polyclonal antibodies and PLS-BK system were in agreement with published values.

  14. Improved 2-nitrobenzenesulfenyl method: optimization of the protocol and improved enrichment for labeled peptides.

    PubMed

    Matsuo, Ei-Ichi; Toda, Chikako; Watanabe, Makoto; Iida, Tetsuo; Masuda, Taro; Minohata, Toshikazu; Ando, Eiji; Tsunasawa, Susumu; Nishimura, Osamu

    2006-01-01

    We have developed the NBS (2-nitrobenzenesulfenyl) method, a quantitative proteome analysis method utilizing stable isotope labeling followed by mass spectrometry. The potential of this method was reported previously, and the procedure has now been further optimized. Here, we describe a procedure utilizing urea or guanidine hydrochloride as a protein denaturant, in conjunction with an improved chromatographic enrichment method for the NBS-labeled peptides using a phenyl resin column. By using this new protocol, both sample loss throughout the protocol and the elution of unwanted unlabeled peptides can be minimized, improving the efficiency of the analysis significantly.

  15. Airframe Noise Prediction Using the Sngr Method

    NASA Astrophysics Data System (ADS)

    Chen, Rongqian; Wu, Yizhao; Xia, Jian

    In this paper, the Stochastic Noise Generation and Radiation method (SNGR) is used to predict airframe noise. The SNGR method combines a stochastic model with Computational Fluid Dynamics (CFD), and it can give acceptable noise results while the computation cost is relatively low. In the method, the time-averaged mean flow field is firstly obtained by solving Reynolds Averaged Navier-Stokes equations (RANS), and a stochastic velocity is generated based on the obtained information. Then the turbulent field is used to generate the source for the Acoustic Perturbation Equations (APEs) that simulate the noise propagation. For numerical methods, timeaveraged RANS equations are solved by finite volume method, and the turbulent model is K - ɛ model; APEs are solved by finite difference method, and the numerical scheme is the Dispersion-Relation-Preserving (DRP) scheme, with explicit optimized 5-stage Rung-Kutta scheme time step. In order to test the APE solver, propagation of a Gaussian pulse in a uniform mean flow is firstly simulated and compared with the analytical solution. Then, using the method, the trailing edge noise of NACA0012 airfoil is calculated. The results are compared with reference data, and good agreements are demonstrated.

  16. Computational predictive methods for fracture and fatigue

    NASA Astrophysics Data System (ADS)

    Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

    1994-09-01

    The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

  17. Computational predictive methods for fracture and fatigue

    NASA Technical Reports Server (NTRS)

    Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

    1994-01-01

    The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

  18. Quantum chemical calculations predict biological function: The case of T cell receptor interaction with a peptide/MHC class I

    NASA Astrophysics Data System (ADS)

    Antipas, Georgios S. E.; Germenis, Anastasios

    2015-02-01

    A combination of atomic correlation statistics and quantum chemical calculations are shown to predict biological function. In the present study, various antigenic peptide-Major Histocompatibility Complex (pMHC) ligands with near-identical stereochemistries, in complexation with the same T cell receptor (TCR), were found to consistently induce distinctly different quantum chemical behavior, directly dependent on the peptide’s electron spin density and intrinsically expressed by the protonation state of the peptide’s N-terminus. Furthermore, the cumulative coordination difference of any variant in respect to the native peptide was found to accurately reflect peptide biological function and immerges as the physical observable which is directly related to the immunological end-effect of pMHC-TCR interaction.

  19. A novel conformational B-cell epitope prediction method based on mimotope and patch analysis.

    PubMed

    Sun, Pingping; Qi, Jialiang; Zhao, Yizhu; Huang, Yanxin; Yang, Guifu; Ma, Zhiqiang; Li, Yuxin

    2016-04-01

    A B-cell epitope is a group of residues on the surface of an antigen that stimulates humoral immune responses. Identifying B-cell epitopes is important for effective vaccine design. Predicting epitopes by experimental methods is expensive in terms of time, cost and effort; therefore, computational methods that have a low cost and high speed are widely used to predict B-cell epitopes. Recently, epitope prediction based on random peptide library screening has been viewed as a promising method. Some novel software and web-based servers have been proposed that have succeeded in some test cases. Herein, we propose a novel epitope prediction method based on amino acid pairs and patch analysis. The method first divides antigen surfaces into overlapping patches based on both radius (R) and number (N), then predict epitopes based on Amino Acid Pairs (AAPs) from mimotopes and the surface patch. The proposed method yields a mean sensitivity of 0.53, specificity of 0.77, ACC of 0.75 and F-measure of 0.45 for 39 test cases. Compared with mimotope-based methods, patch-based methods and two other prediction methods, the sensitivity of the new method offers a certain improvement. Our findings demonstrate that this proposed method was successful for patch and AAPs analysis and allowed for conformational B-cell epitope prediction. PMID:26804644

  20. B-type natriuretic peptide to predict ductus intervention in infants <28 weeks.

    PubMed

    Czernik, Christoph; Lemmer, Julia; Metze, Boris; Koehne, Petra S; Mueller, Christian; Obladen, Michael

    2008-09-01

    Patent ductus arteriosus (PDA) is frequent in neonates with gestational age of less than 28 wk. Clinical and echocardiographic signs define hemodynamic significance of PDA, but do not reveal the need for PDA intervention in the first days of life. B-type natriuretic peptide (BNP) has been proposed as a screening tool for PDA in preterm infants. To determine whether BNP can predict the need for PDA intervention, plasma BNP was measured by chemiluminescence immunoassay in 67 preterm infants <28 wk (median 26) on the second day of life in a prospective blinded study. PDA intervention was based on specified clinical and echocardiographic findings. Twenty-four patients (intervention group) received treatment for PDA and 43 patients (controls) remained without intervention. BNP concentrations were higher in the intervention (median 1069 pg/mL) than in the control group (247 pg/mL, p < 0.001). BNP correlated positively with ductal size (R = 0.46, p < 0.001) and atrial/aortic root ratio (R = 0.54, p < 0.001). In conclusion, plasma BNP proved to be a good predictor for ductus intervention (area under the curve: 0.86) with the best cutoff at 550 pg/mL on the second day of life in ventilated infants less than 28 wk gestation (sensitivity: 83%; specificity: 86%).

  1. PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides.

    PubMed

    Thévenet, Pierre; Shen, Yimin; Maupetit, Julien; Guyon, Frédéric; Derreumaux, Philippe; Tufféry, Pierre

    2012-07-01

    In the context of the renewed interest of peptides as therapeutics, it is important to have an on-line resource for 3D structure prediction of peptides with well-defined structures in aqueous solution. We present an updated version of PEP-FOLD allowing the treatment of both linear and disulphide bonded cyclic peptides with 9-36 amino acids. The server makes possible to define disulphide bonds and any residue-residue proximity under the guidance of the biologists. Using a benchmark of 34 cyclic peptides with one, two and three disulphide bonds, the best PEP-FOLD models deviate by an average RMS of 2.75 Å from the full NMR structures. Using a benchmark of 37 linear peptides, PEP-FOLD locates lowest-energy conformations deviating by 3 Å RMS from the NMR rigid cores. The evolution of PEP-FOLD comes as a new on-line service to supersede the previous server. The server is available at: http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.

  2. PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex

    PubMed Central

    Lamiable, Alexis; Thévenet, Pierre; Rey, Julien; Vavrusa, Marek; Derreumaux, Philippe; Tufféry, Pierre

    2016-01-01

    Structure determination of linear peptides of 5–50 amino acids in aqueous solution and interacting with proteins is a key aspect in structural biology. PEP-FOLD3 is a novel computational framework, that allows both (i) de novo free or biased prediction for linear peptides between 5 and 50 amino acids, and (ii) the generation of native-like conformations of peptides interacting with a protein when the interaction site is known in advance. PEP-FOLD3 is fast, and usually returns solutions in a few minutes. Testing PEP-FOLD3 on 56 peptides in aqueous solution led to experimental-like conformations for 80% of the targets. Using a benchmark of 61 peptide–protein targets starting from the unbound form of the protein receptor, PEP-FOLD3 was able to generate peptide poses deviating on average by 3.3Å from the experimental conformation and return a native-like pose in the first 10 clusters for 52% of the targets. PEP-FOLD3 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD3. PMID:27131374

  3. Prediction and Analysis of Quorum Sensing Peptides Based on Sequence Features

    PubMed Central

    Rajput, Akanksha; Gupta, Amit Kumar; Kumar, Manoj

    2015-01-01

    Quorum sensing peptides (QSPs) are the signaling molecules used by the Gram-positive bacteria in orchestrating cell-to-cell communication. In spite of their enormous importance in signaling process, their detailed bioinformatics analysis is lacking. In this study, QSPs and non-QSPs were examined according to their amino acid composition, residues position, motifs and physicochemical properties. Compositional analysis concludes that QSPs are enriched with aromatic residues like Trp, Tyr and Phe. At the N-terminal, Ser was a dominant residue at maximum positions, namely, first, second, third and fifth while Phe was a preferred residue at first, third and fifth positions from the C-terminal. A few motifs from QSPs were also extracted. Physicochemical properties like aromaticity, molecular weight and secondary structure were found to be distinguishing features of QSPs. Exploiting above properties, we have developed a Support Vector Machine (SVM) based predictive model. During 10-fold cross-validation, SVM achieves maximum accuracy of 93.00%, Mathew’s correlation coefficient (MCC) of 0.86 and Receiver operating characteristic (ROC) of 0.98 on the training/testing dataset (T200p+200n). Developed models performed equally well on the validation dataset (V20p+20n). The server also integrates several useful analysis tools like “QSMotifScan”, “ProtFrag”, “MutGen” and “PhysicoProp”. Our analysis reveals important characteristics of QSPs and on the basis of these unique features, we have developed a prediction algorithm “QSPpred” (freely available at: http://crdd.osdd.net/servers/qsppred). PMID:25781990

  4. Supplemental activation method for high-efficiency electron-transfer dissociation of doubly protonated peptide precursors.

    PubMed

    Swaney, Danielle L; McAlister, Graeme C; Wirtala, Matthew; Schwartz, Jae C; Syka, John E P; Coon, Joshua J

    2007-01-15

    Electron-transfer dissociation (ETD) delivers the unique attributes of electron capture dissociation to mass spectrometers that utilize radio frequency trapping-type devices (e.g., quadrupole ion traps). The method has generated significant interest because of its compatibility with chromatography and its ability to: (1) preserve traditionally labile post-translational modifications (PTMs) and (2) randomly cleave the backbone bonds of highly charged peptide and protein precursor ions. ETD, however, has shown limited applicability to doubly protonated peptide precursors, [M + 2H]2+, the charge and type of peptide most frequently encountered in "bottom-up" proteomics. Here we describe a supplemental collisional activation (CAD) method that targets the nondissociated (intact) electron-transfer (ET) product species ([M + 2H]+*) to improve ETD efficiency for doubly protonated peptides (ETcaD). A systematic study of supplementary activation conditions revealed that low-energy CAD of the ET product population leads to the near-exclusive generation of c- and z-type fragment ions with relatively high efficiency (77 +/- 8%). Compared to those formed directly via ETD, the fragment ions were found to comprise increased relative amounts of the odd-electron c-type ions (c+*) and the even-electron z-type ions (z+). A large-scale analysis of 755 doubly charged tryptic peptides was conducted to compare the method (ETcaD) to ion trap CAD and ETD. ETcaD produced a median sequence coverage of 89%-a significant improvement over ETD (63%) and ion trap CAD (77%).

  5. Predicting Three-Dimensional Conformations of Peptides Constructed of Only Glycine, Alanine, Aspartic Acid, and Valine

    NASA Astrophysics Data System (ADS)

    Oda, Akifumi; Fukuyoshi, Shuichi

    2015-06-01

    The GADV hypothesis is a form of the protein world hypothesis, which suggests that life originated from proteins (Lacey et al. 1999; Ikehara 2002; Andras 2006). In the GADV hypothesis, life is thought to have originated from primitive proteins constructed of only glycine, alanine, aspartic acid, and valine ([GADV]-proteins). In this study, the three-dimensional (3D) conformations of randomly generated short [GADV]-peptides were computationally investigated using replica-exchange molecular dynamics (REMD) simulations (Sugita and Okamoto 1999). Because the peptides used in this study consisted of only 20 residues each, they could not form certain 3D structures. However, the conformational tendencies of the peptides were elucidated by analyzing the conformational ensembles generated by REMD simulations. The results indicate that secondary structures can be formed in several randomly generated [GADV]-peptides. A long helical structure was found in one of the hydrophobic peptides, supporting the conjecture of the GADV hypothesis that many peptides aggregated to form peptide multimers with enzymatic activity in the primordial soup. In addition, these results indicate that REMD simulations can be used for the structural investigation of short peptides.

  6. Predicting three-dimensional conformations of peptides constructed of only glycine, alanine, aspartic acid, and valine.

    PubMed

    Oda, Akifumi; Fukuyoshi, Shuichi

    2015-06-01

    The GADV hypothesis is a form of the protein world hypothesis, which suggests that life originated from proteins (Lacey et al. 1999; Ikehara 2002; Andras 2006). In the GADV hypothesis, life is thought to have originated from primitive proteins constructed of only glycine, alanine, aspartic acid, and valine ([GADV]-proteins). In this study, the three-dimensional (3D) conformations of randomly generated short [GADV]-peptides were computationally investigated using replica-exchange molecular dynamics (REMD) simulations (Sugita and Okamoto 1999). Because the peptides used in this study consisted of only 20 residues each, they could not form certain 3D structures. However, the conformational tendencies of the peptides were elucidated by analyzing the conformational ensembles generated by REMD simulations. The results indicate that secondary structures can be formed in several randomly generated [GADV]-peptides. A long helical structure was found in one of the hydrophobic peptides, supporting the conjecture of the GADV hypothesis that many peptides aggregated to form peptide multimers with enzymatic activity in the primordial soup. In addition, these results indicate that REMD simulations can be used for the structural investigation of short peptides.

  7. Antibody Production with Synthetic Peptides.

    PubMed

    Lee, Bao-Shiang; Huang, Jin-Sheng; Jayathilaka, Lasanthi P; Lee, Jenny; Gupta, Shalini

    2016-01-01

    Peptides (usually 10-20 amino acid residues in length) can be used as effectively as proteins in raising antibodies producing both polyclonal and monoclonal antibodies routinely with titers higher than 20,000. Peptide antigens do not function as immunogens unless they are conjugated to proteins. Production of high quality antipeptide antibodies is dependent upon peptide sequence selection, the success of peptide synthesis, peptide-carrier protein conjugation, the humoral immune response in the host animal, the adjuvant used, the peptide dose administered, the injection method, and the purification of the antibody. Peptide sequence selection is probably the most critical step in the production of antipeptide antibodies. Although the process for designing peptide antigens is not exact, several guidelines and computational B-cell epitope prediction methods can help maximize the likelihood of producing antipeptide antibodies that recognize the protein. Antibodies raised by peptides have become essential tools in life science research. Virtually all phospho-specific antibodies are now produced using phosphopeptides as antigens. Typically, 5-20 mg of peptide is enough for antipeptide antibody production. It takes 3 months to produce a polyclonal antipeptide antibody in rabbits that yields ~100 mL of serum which corresponds to ~8-10 mg of the specific antibody after affinity purification using a peptide column. PMID:27515072

  8. Systems and methods for predicting materials properties

    DOEpatents

    Ceder, Gerbrand; Fischer, Chris; Tibbetts, Kevin; Morgan, Dane; Curtarolo, Stefano

    2007-11-06

    Systems and methods for predicting features of materials of interest. Reference data are analyzed to deduce relationships between the input data sets and output data sets. Reference data includes measured values and/or computed values. The deduced relationships can be specified as equations, correspondences, and/or algorithmic processes that produce appropriate output data when suitable input data is used. In some instances, the output data set is a subset of the input data set, and computational results may be refined by optionally iterating the computational procedure. To deduce features of a new material of interest, a computed or measured input property of the material is provided to an equation, correspondence, or algorithmic procedure previously deduced, and an output is obtained. In some instances, the output is iteratively refined. In some instances, new features deduced for the material of interest are added to a database of input and output data for known materials.

  9. A nozzle internal performance prediction method

    NASA Technical Reports Server (NTRS)

    Carlson, John R.

    1992-01-01

    A prediction method was written and incorporated into a three-dimensional Navier-Stokes code (PAB3D) for the calculation of nozzle internal performance. The following quantities are calculated: (1) discharge coefficient; (2) normal, side, and axial thrust ratios; (3) rolling, pitching, and yawing moments; and (4) effective pitch and yaw vector angles. Four different case studies are presented to confirm the applicability of the methodology. Internal and, in most situations, external flow-field regions are required to be modeled. The computed nozzle discharge coefficient matches both the level and the trend of the experimental data within quoted experimental data accuracy (0.5 percent). Moment and force ratios are generally within 1 to 2 percent of the absolute level of experimental data, with the trends of data matched accurately.

  10. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Efendiev, Y. R.; Mohanty, B.

    2014-12-01

    Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily.

  11. Structure of Trichamide, a Cyclic Peptide from the Bloom-Forming Cyanobacterium Trichodesmium erythraeum, Predicted from the Genome Sequence†

    PubMed Central

    Sudek, Sebastian; Haygood, Margo G.; Youssef, Diaa T. A.; Schmidt, Eric W.

    2006-01-01

    A gene cluster for the biosynthesis of a new small cyclic peptide, dubbed trichamide, was discovered in the genome of the global, bloom-forming marine cyanobacterium Trichodesmium erythraeum ISM101 because of striking similarities to the previously characterized patellamide biosynthesis cluster. The tri cluster consists of a precursor peptide gene containing the amino acid sequence for mature trichamide, a putative heterocyclization gene, an oxidase, two proteases, and hypothetical genes. Based upon detailed sequence analysis, a structure was predicted for trichamide and confirmed by Fourier transform mass spectrometry. Trichamide consists of 11 amino acids, including two cysteine-derived thiazole groups, and is cyclized by an N—C terminal amide bond. As the first natural product reported from T. erythraeum, trichamide shows the power of genome mining in the prediction and discovery of new natural products. PMID:16751554

  12. A method to predict circulation control noise

    NASA Astrophysics Data System (ADS)

    Reger, Robert W.

    Underwater vehicles suffer from reduced maneuverability with conventional lifting append-\\ ages due to the low velocity of operation. Circulation control offers a method to increase maneuverability independent of vehicle speed. However, with circulation control comes additional noise sources, which are not well understood. To better understand these noise sources, a modal-based prediction method is developed, potentially offering a quantitative connection between flow structures and far-field noise. This method involves estimation of the velocity field, surface pressure field, and far-field noise, using only non-time-resolved velocity fields and time-resolved probe measurements. Proper orthogonal decomposition, linear stochastic estimation and Kalman smoothing are employed to estimate time-resolved velocity fields. Poisson's equation is used to calculate time-resolved pressure fields from velocity. Curle's analogy is then used to propagate the surface pressure forces to the far field. This method is developed on a direct numerical simulation of a two-dimensional cylinder at a low Reynolds number (150). Since each of the fields to be estimated are also known from the simulation, a means of obtaining the error from using the methodology is provided. The velocity estimation and the simulated velocity match well when the simulated additive measurement noise is low. The pressure field suffers due to a small domain size; however, the surface pressures estimates fare much better. The far-field estimation contains similar frequency content with reduced magnitudes, attributed to the exclusion of the viscous forces in Curle's analogy. In the absence of added noise, the estimation procedure performs quite nicely for this model problem. The method is tested experimentally on a 650,000 chord-Reynolds-number flow over a 2-D, 20% thick, elliptic circulation control airfoil. Slot jet momentum coefficients of 0 and 0.10 are investigated. Particle image velocimetry, unsteady

  13. Minimizing Postsampling Degradation of Peptides by a Thermal Benchtop Tissue Stabilization Method.

    PubMed

    Segerström, Lova; Gustavsson, Jenny; Nylander, Ingrid

    2016-04-01

    Enzymatic degradation is a major concern in peptide analysis. Postmortem metabolism in biological samples entails considerable risk for measurements misrepresentative of true in vivo concentrations. It is therefore vital to find reliable, reproducible, and easy-to-use procedures to inhibit enzymatic activity in fresh tissues before subjecting them to qualitative and quantitative analyses. The aim of this study was to test a benchtop thermal stabilization method to optimize measurement of endogenous opioids in brain tissue. Endogenous opioid peptides are generated from precursor proteins through multiple enzymatic steps that include conversion of one bioactive peptide to another, often with a different function. Ex vivo metabolism may, therefore, lead to erroneous functional interpretations. The efficacy of heat stabilization was systematically evaluated in a number of postmortem handling procedures. Dynorphin B (DYNB), Leu-enkephalin-Arg(6) (LARG), and Met-enkephalin-Arg(6)-Phe(7) (MEAP) were measured by radioimmunoassay in rat hypothalamus, striatum (STR), and cingulate cortex (CCX). Also, simplified extraction protocols for stabilized tissue were tested. Stabilization affected all peptide levels to varying degrees compared to those prepared by standard dissection and tissue handling procedures. Stabilization increased DYNB in hypothalamus, but not STR or CCX, whereas LARG generally decreased. MEAP increased in hypothalamus after all stabilization procedures, whereas for STR and CCX, the effect was dependent on the time point for stabilization. The efficacy of stabilization allowed samples to be left for 2 hours in room temperature (20°C) without changes in peptide levels. This study shows that conductive heat transfer is an easy-to-use and efficient procedure for the preservation of the molecular composition in biological samples. Region- and peptide-specific critical steps were identified and stabilization enabled the optimization of tissue handling and opioid

  14. A multiplex method for the detection of serum antibodies against in silico-predicted tumor antigens.

    PubMed

    Reuschenbach, Miriam; Dörre, Jonathan; Waterboer, Tim; Kopitz, Jürgen; Schneider, Martin; Hoogerbrugge, Nicoline; Jäger, Elke; Kloor, Matthias; von Knebel Doeberitz, Magnus

    2014-12-01

    Humoral immune responses against tumor antigens are studied as indirect markers of antigen exposure and in cancer vaccine studies. An increasing number of tumor antigens potentially translated from mutant genes is identified by advances in genomic sequencing. They represent an interesting source for yet unknown immunogenic epitopes. We here describe a multiplex method using the Luminex technology allowing for the detection of antibodies against multiple in silico-predicted linear neo-antigens in large sets of sera. The approach included 32 synthetic biotinylated peptides comprising a predicted set of frameshift mutation-induced neo-antigens. The antigens were fused to a FLAG epitope to ensure monitoring antigen binding to avidin-linked microspheres in the absence of monoclonal antibodies. Analytical specificity of measured serum antibody reactivity was proven by the detection of immune responses in immunized rabbits and a colorectal cancer patient vaccinated with peptides included in the assay. The measured antibody responses were comparable to peptide ELISA, and inter-assay reproducibility of the multiplex approach was excellent (R (2) > 0.98) for 20 sera tested against all antigens. Our methodic approach represents a valuable platform to monitor antibody responses against predicted antigens. It may be used in individualized cancer vaccine studies, thereby extending the relevance beyond the model system in the presented approach.

  15. Hybrid methods for B-cell epitope prediction.

    PubMed

    Caoili, Salvador Eugenio C

    2014-01-01

    Many computational approaches to B-cell epitope prediction have been published, including combinations of previously proposed methods, which complicates the tasks of further developing such computational approaches and of selecting those most appropriate for practical applications (e.g., the design of novel immunodiagnostics and vaccines). These tasks are considered together herein to clarify their close but often overlooked interrelationship, thereby providing a guide to their performance in mutual support of one another, with emphasis on key physicochemical and biological considerations that are relevant from an applications perspective. This aims to assist investigators in performing either or both tasks, with the overall goals of successfully applying computational tools towards practical ends and of generating informative new data towards iterative improvement of the tools, particularly as regards the design of peptide-based immunogens for eliciting the production of antipeptide antibodies that modulate biological activity of protein targets via functionally relevant cross-reactivity in relation to the phenomena of protein folding and protein disorder.

  16. Methods of Predicting Solid Waste Characteristics.

    ERIC Educational Resources Information Center

    Boyd, Gail B.; Hawkins, Myron B.

    The project summarized by this report involved a preliminary design of a model for estimating and predicting the quantity and composition of solid waste and a determination of its feasibility. The novelty of the prediction model is that it estimates and predicts on the basis of knowledge of materials and quantities before they become a part of the…

  17. Anti-citrullinated peptide antibodies and their value for predicting responses to biologic agents: a review.

    PubMed

    Martin-Mola, Emilio; Balsa, Alejandro; García-Vicuna, Rosario; Gómez-Reino, Juan; González-Gay, Miguel Angel; Sanmartí, Raimon; Loza, Estíbaliz

    2016-08-01

    Anti-citrullinated peptide antibodies (ACPAs) play an important pathogenic role both at the onset and during the disease course. These antibodies precede the clinical appearance of rheumatoid arthritis (RA) and are associated with a less favorable prognosis, both clinically and radiologically. The objective of this work was to conduct a comprehensive review of studies published through September 2015 of ACPAs' role as a predictor of the therapeutic response to the biological agents in RA patients. The review also includes summary of the biology and detection of ACPAs as well as ACPAs in relation to joint disease and CV disease and the possible role of seroconversion. The reviews of studies examining TNF inhibitors and tocilizumab yielded negative results. In the case of rituximab, the data indicated a greater probability of clinical benefit in ACPA(+) patients versus ACPA(-) patients, as has been previously described for rheumatoid factor. Nonetheless, the effect is discreet and heterogeneous. Another drug that may have greater effectiveness in ACPA(+) patients is abatacept. Some studies have suggested that the drug is more efficient in ACPA(+) patients and that those patients show greater drug retention. In a subanalysis of the AMPLE trial, patients with very high ACPA titers who were treated with abatacept had a statistically significant response compared to patients with lower titers. In summary, the available studies suggest that the presence of or high titers of ACPA may predict a better response to rituximab and/or abatacept. Evidence regarding TNFi and tocilizumab is lacking. However, there is a lack of studies with appropriate designs to demonstrate that some drugs are superior to others for ACPA(+) patients. PMID:27271502

  18. Cyanine-based probe\\tag-peptide pair for fluorescence protein imaging and fluorescence protein imaging methods

    DOEpatents

    Mayer-Cumblidge, M. Uljana; Cao, Haishi

    2010-08-17

    A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

  19. An Efficient Method for the In Vitro Production of Azol(in)e-Based Cyclic Peptides**

    PubMed Central

    Houssen, Wael E; Bent, Andrew F; McEwan, Andrew R; Pieiller, Nathalie; Tabudravu, Jioji; Koehnke, Jesko; Mann, Greg; Adaba, Rosemary I; Thomas, Louise; Hawas, Usama W; Liu, Huanting; Schwarz-Linek, Ulrich; Smith, Margaret C M; Naismith, James H; Jaspars, Marcel

    2014-01-01

    Heterocycle-containing cyclic peptides are promising scaffolds for the pharmaceutical industry but their chemical synthesis is very challenging. A new universal method has been devised to prepare these compounds by using a set of engineered marine-derived enzymes and substrates obtained from a family of ribosomally produced and post-translationally modified peptides called the cyanobactins. The substrate precursor peptide is engineered to have a non-native protease cleavage site that can be rapidly cleaved. The other enzymes used are heterocyclases that convert Cys or Cys/Ser/Thr into their corresponding azolines. A macrocycle is formed using a macrocyclase enzyme, followed by oxidation of the azolines to azoles with a specific oxidase. The work is exemplified by the production of 17 macrocycles containing 6–9 residues representing 11 out of the 20 canonical amino acids. PMID:25331823

  20. A Support Vector Machine model for the prediction of proteotypic peptides for accurate mass and time proteomics

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.

    2008-07-01

    Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php

  1. BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

    PubMed

    Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

    2016-10-01

    Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc.

  2. An equation to estimate the difference between theoretically predicted and SDS PAGE-displayed molecular weights for an acidic peptide.

    PubMed

    Guan, Yihong; Zhu, Qinfang; Huang, Delai; Zhao, Shuyi; Jan Lo, Li; Peng, Jinrong

    2015-01-01

    The molecular weight (MW) of a protein can be predicted based on its amino acids (AA) composition. However, in many cases a non-chemically modified protein shows an SDS PAGE-displayed MW larger than its predicted size. Some reports linked this fact to high content of acidic AA in the protein. However, the exact relationship between the acidic AA composition and the SDS PAGE-displayed MW is not established. Zebrafish nucleolar protein Def is composed of 753 AA and shows an SDS PAGE-displayed MW approximately 13 kDa larger than its predicted MW. The first 188 AA in Def is defined by a glutamate-rich region containing ~35.6% of acidic AA. In this report, we analyzed the relationship between the SDS PAGE-displayed MW of thirteen peptides derived from Def and the AA composition in each peptide. We found that the difference between the predicted and SDS PAGE-displayed MW showed a linear correlation with the percentage of acidic AA that fits the equation y = 276.5x - 31.33 (x represents the percentage of acidic AA, 11.4% ≤ x ≤ 51.1%; y represents the average ΔMW per AA). We demonstrated that this equation could be applied to predict the SDS PAGE-displayed MW for thirteen different natural acidic proteins. PMID:26311515

  3. Method For Determining And Modifying Protein/Peptide Solubilty

    DOEpatents

    Waldo, Geoffrey S.

    2005-03-15

    A solubility reporter for measuring a protein's solubility in vivo or in vitro is described. The reporter, which can be used in a single living cell, gives a specific signal suitable for determining whether the cell bears a soluble version of the protein of interest. A pool of random mutants of an arbitrary protein, generated using error-prone in vitro recombination, may also be screened for more soluble versions using the reporter, and these versions may be recombined to yield variants having further-enhanced solubility. The method of the present invention includes "irrational" (random mutagenesis) methods, which do not require a priori knowledge of the three-dimensional structure of the protein of interest. Multiple sequences of mutation/genetic recombination and selection for improved solubility are demonstrated to yield versions of the protein which display enhanced solubility.

  4. Prediction Methods in Solar Sunspots Cycles

    PubMed Central

    Ng, Kim Kwee

    2016-01-01

    An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. PMID:26868269

  5. Prediction Methods in Solar Sunspots Cycles

    NASA Astrophysics Data System (ADS)

    Ng, Kim Kwee

    2016-02-01

    An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle.

  6. Computational Prediction and Experimental Validation of Signal Peptide Cleavage in the Extracellular Proteome of a Natural Microbial Community

    SciTech Connect

    Erickson, Brian K; Mueller, Ryan; Verberkmoes, Nathan C; Shah, Manesh B; Singer, Steven; Thelen, Michael P.; Banfield, Jillian F.; Hettich, Robert {Bob} L

    2010-01-01

    An integrated computational/experimental approach was used to predict and identify signal peptide cleavages among microbial proteins of environmental biofilm communities growing in acid mine drainage (AMD). SignalP-3.0 was employed to computationally query the AMD protein database of >16,000 proteins, which resulted in 1,480 predicted signal peptide cleaved proteins. LC-MS/MS analyses of extracellular (secretome) microbial preparations from different locations and developmental states empirically confirmed 531 of these signal peptide cleaved proteins. The majority of signal-cleavage proteins (58.4%) are annotated to have unknown functions; however, Pfam domain analysis revealed that many may be involved in extracellular functions expected within the AMD system. Examination of the abundances of signal-cleaved proteins across 28 proteomes from biofilms collected over a 4-year period demonstrated a strong correlation with the developmental state of the biofilm. For example, class I cytochromes are abundant in early growth states, whereas cytochrome oxidases from the same organism increase in abundance later in development. These results likely reflect shifts in metabolism that occur as biofilms thicken and communities diversify. In total, these results provide experimental confirmation of proteins that are designed to function in the extreme acidic extracellular environment and will serve as targets for future biochemical analysis.

  7. A Statistical Method for Assessing Peptide Identification Confidence in Accurate Mass and Time Tag Proteomics

    SciTech Connect

    Stanley, Jeffrey R.; Adkins, Joshua N.; Slysz, Gordon W.; Monroe, Matthew E.; Purvine, Samuel O.; Karpievitch, Yuliya V.; Anderson, Gordon A.; Smith, Richard D.; Dabney, Alan R.

    2011-07-15

    High-throughput proteomics is rapidly evolving to require high mass measurement accuracy for a variety of different applications. Increased mass measurement accuracy in bottom-up proteomics specifically allows for an improved ability to distinguish and characterize detected MS features, which may in turn be identified by, e.g., matching to entries in a database for both precursor and fragmentation mass identification methods. Many tools exist with which to score the identification of peptides from LC-MS/MS measurements or to assess matches to an accurate mass and time (AMT) tag database, but these two calculations remain distinctly unrelated. Here we present a statistical method, Statistical Tools for AMT tag Confidence (STAC), which extends our previous work incorporating prior probabilities of correct sequence identification from LC-MS/MS, as well as the quality with which LC-MS features match AMT tags, to evaluate peptide identification confidence. Compared to existing tools, we are able to obtain significantly more high-confidence peptide identifications at a given false discovery rate and additionally assign confidence estimates to individual peptide identifications. Freely available software implementations of STAC are available in both command line and as a Windows graphical application.

  8. Size-exclusion HPLC as a sensitive and calibrationless method for complex peptide mixtures quantification.

    PubMed

    Bodin, Alice; Framboisier, Xavier; Alonso, Dominique; Marc, Ivan; Kapel, Romain

    2015-12-01

    This work describes an original methodology to quantify complex peptide mixtures by size-exclusion high-performance liquid chromatography (SE-HPLC). The methodology was first tested on simulated elutions of peptide mixtures. For this set of experiments, a good estimation of the total peptide concentration was observed (error less than 10 %). Then 30 fractions obtained by ultrafiltration of hydrolysates from two different sources were titrated by Kjeldahl or BCA analysis and analysed by SE-HPLC for an experimental validation of the methodology. Very good matchs between methods were obtained. The linear working range depends on the hydrolysate but is generally between 0.2 and 4gL(-1) (i.e. between 10 and 200μg). Moreover, the presence of organic solvents or salts in samples does not impact the accuracy of the methodology contrary to common quantification methods. Hence, the findings of this study show that total concentration of complex peptide mixture can be efficiently determinate by the proposed methodology using simple SE-HPLC analysis.

  9. Development of a method to quantify the DNA content in cationic peptide-DNA nanoparticles.

    PubMed

    Jain, Arvind K; Yusuf, Helmy; Pattani, Aditya; McCarthy, Helen O; McDonald, Denise M; Kett, Vicky L

    2014-11-01

    Gene therapy has the potential to provide safe and targeted therapies for a variety of diseases. A range of intracellular gene delivery vehicles have been proposed for this purpose. Non-viral vectors are a particularly attractive option and among them cationic peptides have emerged as promising candidates. For the pharmaceutical formulation and application to clinical studies it is necessary to quantify the amount of pDNA condensed with the delivery system. There is a severe deficiency in this area, thus far no methods have been reported specifically for pDNA condensed with cationic peptide to form nanoparticles. The current study seeks to address this and describes the evaluation of a range of disruption agents to extract DNA from nanoparticles formed by condensation with cationic fusogenic peptides RALA and KALA. Only proteinase K exhibited efficient and reproducible results and compatibility with the PicoGreen reagent based quantification assay. Thus we report for the first time a simple and reliable method that can quantify the pDNA content in pDNA cationic peptide nanoparticles.

  10. Intercalation of amino acids and peptides into Mg-Al layered double hydroxide by reconstruction method.

    PubMed

    Nakayama, Hirokazu; Wada, Natsuko; Tsuhako, Mitsutomo

    2004-01-28

    The intercalation of amino acids and some peptides into Mg-Al layered double hydroxide known as hydrotalcite was examined. Although the intercalation by ion-exchange method was unsuccessful, all the amino acids except for Lys and Arg, and peptides examined could be intercalated into the layered double hydroxide by reconstruction method using Mg-Al oxide precursor. The uptake amounts of amino acids and peptides were 0.9-2.7 mmol per 1 g of LDH. Intercalation compounds were examined by using XRD and solid-state NMR. For Gly, Ala, Ser, Thr, Pro, Asn, Gln, Asp, Glu, and aspartame the intercalation accompanied the expansion of interlayer distance of the solid products, whereas the other amino acids and oligoglycine showed no expansion. The intercalation mechanism and release profile in K(2)CO(3) aqueous solution were also investigated. And the cointercalation of amino acids and peptides into Mg-Al LDH and easy release of amino acids from the LDH layer were found.

  11. Fibpredictor: a computational method for rapid prediction of amyloid fibril structures.

    PubMed

    Tabatabaei Ghomi, Hamed; Topp, Elizabeth M; Lill, Markus A

    2016-09-01

    Amyloid fibrils are important in diseases such as Alzheimer's disease and Parkinson's disease, and are also a common instability in peptide and protein drug products. Despite their importance, experimental structures of amyloid fibrils in atomistic detail are rare. To address this limitation, we have developed a novel, rapid computational method to predict amyloid fibril structures (Fibpredictor). The method combines β-sheet model building, β-sheet replication, and symmetry operations with side-chain prediction and statistical scoring functions. When applied to nine amyloid fibrils with experimentally determined structures, the method predicted the correct structures of amyloid fibrils and enriched those among the top-ranked structures. These models can be used as the initial heuristic structures for more complicated computational studies. Fibpredictor is available at http://nanohub.org/resources/fibpredictor .

  12. Fibpredictor: a computational method for rapid prediction of amyloid fibril structures.

    PubMed

    Tabatabaei Ghomi, Hamed; Topp, Elizabeth M; Lill, Markus A

    2016-09-01

    Amyloid fibrils are important in diseases such as Alzheimer's disease and Parkinson's disease, and are also a common instability in peptide and protein drug products. Despite their importance, experimental structures of amyloid fibrils in atomistic detail are rare. To address this limitation, we have developed a novel, rapid computational method to predict amyloid fibril structures (Fibpredictor). The method combines β-sheet model building, β-sheet replication, and symmetry operations with side-chain prediction and statistical scoring functions. When applied to nine amyloid fibrils with experimentally determined structures, the method predicted the correct structures of amyloid fibrils and enriched those among the top-ranked structures. These models can be used as the initial heuristic structures for more complicated computational studies. Fibpredictor is available at http://nanohub.org/resources/fibpredictor . PMID:27502172

  13. A simple three-step method for design and affinity testing of new antisense peptides: an example of erythropoietin.

    PubMed

    Štambuk, Nikola; Manojlović, Zoran; Turčić, Petra; Martinić, Roko; Konjevoda, Paško; Weitner, Tin; Wardega, Piotr; Gabričević, Mario

    2014-01-01

    Antisense peptide technology is a valuable tool for deriving new biologically active molecules and performing peptide-receptor modulation. It is based on the fact that peptides specified by the complementary (antisense) nucleotide sequences often bind to each other with a higher specificity and efficacy. We tested the validity of this concept on the example of human erythropoietin, a well-characterized and pharmacologically relevant hematopoietic growth factor. The purpose of the work was to present and test simple and efficient three-step procedure for the design of an antisense peptide targeting receptor-binding site of human erythropoietin. Firstly, we selected the carboxyl-terminal receptor binding region of the molecule (epitope) as a template for the antisense peptide modeling; Secondly, we designed an antisense peptide using mRNA transcription of the epitope sequence in the 3'→5' direction and computational screening of potential paratope structures with BLAST; Thirdly, we evaluated sense-antisense (epitope-paratope) peptide binding and affinity by means of fluorescence spectroscopy and microscale thermophoresis. Both methods showed similar Kd values of 850 and 816 µM, respectively. The advantages of the methods were: fast screening with a small quantity of the sample needed, and measurements done within the range of physicochemical parameters resembling physiological conditions. Antisense peptides targeting specific erythropoietin region(s) could be used for the development of new immunochemical methods. Selected antisense peptides with optimal affinity are potential lead compounds for the development of novel diagnostic substances, biopharmaceuticals and vaccines. PMID:24865486

  14. High throughput peptide mapping method for analysis of site specific monoclonal antibody oxidation.

    PubMed

    Li, Xiaojuan; Xu, Wei; Wang, Yi; Zhao, Jia; Liu, Yan-Hui; Richardson, Daisy; Li, Huijuan; Shameem, Mohammed; Yang, Xiaoyu

    2016-08-19

    Oxidation of therapeutic monoclonal antibodies (mAbs) often occurs on surface exposed methionine and tryptophan residues during their production in cell culture, purification, and storage, and can potentially impact the binding to their targets. Characterization of site specific oxidation is critical for antibody quality control. Antibody oxidation is commonly determined by peptide mapping/LC-MS methods, which normally require a long (up to 24h) digestion step. The prolonged sample preparation procedure could result in oxidation artifacts of susceptible methionine and tryptophan residues. In this paper, we developed a rapid and simple UV based peptide mapping method that incorporates an 8-min trypsin in-solution digestion protocol for analysis of oxidation. This method is able to determine oxidation levels at specific residues of a mAb based on the peptide UV traces within <1h, from either TBHP treated or UV light stressed samples. This is the simplest and fastest method reported thus far for site specific oxidation analysis, and can be applied for routine or high throughput analysis of mAb oxidation during various stability and degradation studies. By using the UV trace, the method allows more accurate measurement than mass spectrometry and can be potentially implemented as a release assay. It has been successfully used to monitor antibody oxidation in real time stability studies.

  15. High throughput peptide mapping method for analysis of site specific monoclonal antibody oxidation.

    PubMed

    Li, Xiaojuan; Xu, Wei; Wang, Yi; Zhao, Jia; Liu, Yan-Hui; Richardson, Daisy; Li, Huijuan; Shameem, Mohammed; Yang, Xiaoyu

    2016-08-19

    Oxidation of therapeutic monoclonal antibodies (mAbs) often occurs on surface exposed methionine and tryptophan residues during their production in cell culture, purification, and storage, and can potentially impact the binding to their targets. Characterization of site specific oxidation is critical for antibody quality control. Antibody oxidation is commonly determined by peptide mapping/LC-MS methods, which normally require a long (up to 24h) digestion step. The prolonged sample preparation procedure could result in oxidation artifacts of susceptible methionine and tryptophan residues. In this paper, we developed a rapid and simple UV based peptide mapping method that incorporates an 8-min trypsin in-solution digestion protocol for analysis of oxidation. This method is able to determine oxidation levels at specific residues of a mAb based on the peptide UV traces within <1h, from either TBHP treated or UV light stressed samples. This is the simplest and fastest method reported thus far for site specific oxidation analysis, and can be applied for routine or high throughput analysis of mAb oxidation during various stability and degradation studies. By using the UV trace, the method allows more accurate measurement than mass spectrometry and can be potentially implemented as a release assay. It has been successfully used to monitor antibody oxidation in real time stability studies. PMID:27432793

  16. Spectrum-based method to generate good decoy libraries for spectral library searching in peptide identifications.

    PubMed

    Cheng, Chia-Ying; Tsai, Chia-Feng; Chen, Yu-Ju; Sung, Ting-Yi; Hsu, Wen-Lian

    2013-05-01

    As spectral library searching has received increasing attention for peptide identification, constructing good decoy spectra from the target spectra is the key to correctly estimating the false discovery rate in searching against the concatenated target-decoy spectral library. Several methods have been proposed to construct decoy spectral libraries. Most of them construct decoy peptide sequences and then generate theoretical spectra accordingly. In this paper, we propose a method, called precursor-swap, which directly constructs decoy spectral libraries directly at the "spectrum level" without generating decoy peptide sequences by swapping the precursors of two spectra selected according to a very simple rule. Our spectrum-based method does not require additional efforts to deal with ion types (e.g., a, b or c ions), fragment mechanism (e.g., CID, or ETD), or unannotated peaks, but preserves many spectral properties. The precursor-swap method is evaluated on different spectral libraries and the results of obtained decoy ratios show that it is comparable to other methods. Notably, it is efficient in time and memory usage for constructing decoy libraries. A software tool called Precursor-Swap-Decoy-Generation (PSDG) is publicly available for download at http://ms.iis.sinica.edu.tw/PSDG/.

  17. Earthquake prediction: Simple methods for complex phenomena

    NASA Astrophysics Data System (ADS)

    Luen, Bradley

    2010-09-01

    Earthquake predictions are often either based on stochastic models, or tested using stochastic models. Tests of predictions often tacitly assume predictions do not depend on past seismicity, which is false. We construct a naive predictor that, following each large earthquake, predicts another large earthquake will occur nearby soon. Because this "automatic alarm" strategy exploits clustering, it succeeds beyond "chance" according to a test that holds the predictions _xed. Some researchers try to remove clustering from earthquake catalogs and model the remaining events. There have been claims that the declustered catalogs are Poisson on the basis of statistical tests we show to be weak. Better tests show that declustered catalogs are not Poisson. In fact, there is evidence that events in declustered catalogs do not have exchangeable times given the locations, a necessary condition for the Poisson. If seismicity followed a stochastic process, an optimal predictor would turn on an alarm when the conditional intensity is high. The Epidemic-Type Aftershock (ETAS) model is a popular point process model that includes clustering. It has many parameters, but is still a simpli_cation of seismicity. Estimating the model is di_cult, and estimated parameters often give a non-stationary model. Even if the model is ETAS, temporal predictions based on the ETAS conditional intensity are not much better than those of magnitude-dependent automatic (MDA) alarms, a much simpler strategy with only one parameter instead of _ve. For a catalog of Southern Californian seismicity, ETAS predictions again o_er only slight improvement over MDA alarms

  18. Correlation between the compact regions predicted by the average distance map (ADM) and the biologically active sites in atrial natriuretic peptide.

    PubMed

    Kikuchi, T

    1992-10-01

    The prediction of the short-range compact regions of human atrial natriuretic peptide (alpha-hANP), one of the biologically active peptides, has been made by means of the Average Distance Map(ADM). We found out that the location of the predicted short-range compact regions is consistent with the structural units determined by the NMR analysis (Kobayashi et al., 1988). Furthermore, the short-range compact regions correspond well to the biologically active areas of atriopeptin (103-125)-amide (which is homologous peptide to alpha-hANP), detected by the glycine substitution technique (Konishi et al., 1987). The results suggest that a predicted short-range compact region can be regarded as a possible active site in a biologically active peptide.

  19. Potential Method of Predicting Coronal Mass Ejection

    NASA Astrophysics Data System (ADS)

    Imholt, Timothy; Roberts, J. A.; Scott, J. B.; University Of North Texas Team

    2000-10-01

    Coronal Mass Ejections (CME) may be described as a blast of gas and highly charged solar mass fragments ejected into space. These ejections, when directed toward Earth, have many different effects on terrestrial systems ranging from the Aurora Borealis to changes in wireless communications. The importance of an early prediction of these solar events cannot be overlooked. There are several models currently accepted and utilized to predict these events, however, with earlier prediction of both the event and the location on the sun where the event occur allows us to have earlier warnings as to when they will effect man-made systems. A better prediction could perhaps be achieved by utilizing low angular resolution radio telescope arrays to catalog data from the sun at different radio frequencies on a regular basis. Once this data is cataloged a better predictor for these CME's could be found. We propose a model that allows a prediction to be made that appears to be longer than 24 hours.

  20. Potential Method of Predicting Coronal Mass Ejection

    NASA Astrophysics Data System (ADS)

    Imholt, Timothy

    2001-10-01

    Coronal Mass Ejections (CME) may be described as a blast of gas and highly charged solar mass fragments ejected into space. These ejections, when directed toward Earth, have many different effects on terrestrial systems ranging from the Aurora Borealis to changes in wireless communication. The early prediction of these solar events cannot be overlooked. There are several models currently accepted and utilized to predict these events, however, with earlier prediction of both the event and the location on the sun where the event occurs allows us to have earlier warnings as to when they will affect man-made systems. A better prediction could perhaps be achieved by utilizing low angular resolution radio telescope arrays to catalog data from the sun at different radio frequencies on a regular basis. Once this data is cataloged a better predictor for these CME’s could be found. We propose a model that allows a prediction to be made that appears to be longer than 24 hours.

  1. Robust MS quantification method for phospho-peptides using 18O/16O labeling

    PubMed Central

    Andersen, Claus A; Gotta, Stefano; Magnoni, Letizia; Raggiaschi, Roberto; Kremer, Andreas; Terstappen, Georg C

    2009-01-01

    Background Quantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using 18O/16O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-β treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable. Results The presented method assesses, in complete cell lysates, the degree of phosphorylation of specific peptide residues from MS spectra using 18O/16O labeling. The abundance of each observed phospho-peptide from two cell states was estimated from three overlapping isotope contours. The influence of peptide-specific labeling efficiency was removed by performing a label swapped experiment and assuming that the labeling efficiency was unchanged upon label swapping. Different degrees of phosphorylation were reported using the fold change measure which was extended with a confidence interval found to reflect the quality of the underlying spectra. Furthermore a new way of method assessment using simulated data is presented. Using simulated data generated in a manner mimicking real data it was possible to show the method's robustness both with increasing noise levels and with decreasing labeling efficiency. Conclusion The fold change error assessable on simulated data was on average 0.16 (median 0.10) with an error-to-signal ratio and labeling efficiency distributions similar to the ones found in the experimentally observed spectra. Applied to experimentally observed spectra a very good match was found to the model (<10% error for 85% of spectra) with a high degree of robustness, as assessed by data removal. This new method can thus be used for quantitative signal cascade analysis of total cell extracts in a high throughput mode

  2. Zeolites to peptides: Statistical mechanics methods for structure solution and property evaluation

    NASA Astrophysics Data System (ADS)

    Pophale, Ramdas S.

    Methods in statistical mechanics are used to study structure and properties of zeolites and peptides. A Monte Carlo method is applied to solve structure of a newly synthesized zeolite. Understanding the structure of a zeolite could lead to optimization of chemical processes it is involved in. Dielectric constant and elastic modulus are calculated using a molecular dynamics method for a pure silica zeolite with and without the structure directing agent used in its synthesis. These properties are of interest due to the potential use of this zeolite as low dielectric constant material in manufacturing integrated circuits. Results of four methods probing energy landscapes in peptides are compared for four cyclic peptides. Their ability to equilibrate structural properties and their relative speeds are important in their ability to simulate complex structures. A docking study is carried out to probe interactions between two proteins, Cripto and Snail, and E-cadherin promoter. The study supports experimental evidence that Cripto is involved in expression of E-cadherin through a promoter priming mechanism. Finally, the use of computational models in the design of better vaccines is illustrated through an example of Influenza.

  3. Peptide synthesis triggered by comet impacts: A possible method for peptide delivery to the early Earth and icy satellites

    NASA Astrophysics Data System (ADS)

    Sugahara, Haruna; Mimura, Koichi

    2015-09-01

    We performed shock experiments simulating natural comet impacts in an attempt to examine the role that comet impacts play in peptide synthesis. In the present study, we selected a mixture of alanine (DL-alanine), water ice, and silicate (forsterite) to make a starting material for the experiments. The shock experiments were conducted under cryogenic conditions (77 K), and the shock pressure range achieved in the experiments was 4.8-25.8 GPa. The results show that alanine is oligomerized into peptides up to tripeptides due to the impact shock. The synthesized peptides were racemic, indicating that there was no enantioselective synthesis of peptides from racemic amino acids due to the impact shock. We also found that the yield of linear peptides was a magnitude higher than those of cyclic diketopiperazine. Furthermore, we estimated the amount of cometary-derived peptides to the early Earth based on two models (the Lunar Crating model and the Nice model) during the Late Heavy Bombardment (LHB) using our experimental data. The estimation based on the Lunar Crating model gave 3 × 109 mol of dialanine, 4 × 107 mol of trialanine, and 3 × 108 mol of alanine-diketopiperazine. Those based on the Nice model, in which the main impactor of LHB is comets, gave 6 × 1010 mol of dialanine, 1 × 109 mol of trialanine, and 8 × 109 mol of alanine-diketopiperazine. The estimated amounts were comparable to those originating from terrestrial sources (Cleaves, H.J., Aubrey, A.D., Bada, J.L. [2009]. Orig. Life Evol. Biosph. 39, 109-126). Our results indicate that comet impacts played an important role in chemical evolution as a supplier of linear peptides, which are important for further chemical evolution on the early Earth. Our study also highlights the importance of icy satellites, which were formed by comet accumulation, as prime targets for missions searching for extraterrestrial life.

  4. Predictive Role of Intraoperative Serum Brain Natriuretic Peptide for Early Allograft Dysfunction in Living Donor Liver Transplantation.

    PubMed

    Chae, Min Suk; Koo, Jung Min; Park, Chul Soo

    2016-01-01

    BACKGROUND Early allograft dysfunction (EAD) is considered an important complication in liver transplantation. Serum brain natriuretic peptide (BNP) is a marker of cardiac dysfunction related to end-stage liver disease. We investigated the intraoperative change in the serum BNP level and its contribution to EAD after living donor liver transplantation (LDLT). MATERIAL AND METHODS The perioperative data of 104 patients who underwent LDLT were retrospectively reviewed and compared between patients with and without EAD. Serum BNPs were obtained at each phase, and potentially significant factors (P<0.1) were measured by univariate analysis. The intraoperative mean serum BNP level was compared with other predictors using the AUC, and was analyzed for its relationship with EAD by multivariate logistic regression. RESULTS A total of 31 patients (29.8%) developed EAD after LDLT. In all phases, the EAD group showed higher serum BNP levels than the non-EAD group. The serum BNP level at each phase was less accurate than the mean serum BNP level for EAD. The intraoperative mean serum BNP level showed higher predictive accuracy than the Child-Pugh-Turcotte, model for end-stage liver disease (MELD), and D-MELD (donor age × recipient MELD) scores (p<0.05 for all). After multivariate adjustment, intraoperative mean serum BNP level ≥100 pg/mL was identified as an independent risk factor for EAD, along with kidney disease and graft ischemic time. CONCLUSIONS During LDLT, the EAD group showed higher serum BNP levels than the non-EAD group. An intraoperative mean serum BNP level ≥100 pg/mL is independently associated with EAD after LDLT. PMID:27572618

  5. A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics.

    PubMed

    Stanley, Jeffrey R; Adkins, Joshua N; Slysz, Gordon W; Monroe, Matthew E; Purvine, Samuel O; Karpievitch, Yuliya V; Anderson, Gordon A; Smith, Richard D; Dabney, Alan R

    2011-08-15

    Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

  6. NMR methods for studying the structure and dynamics of oncogenic and antihistaminic peptides in biomembranes.

    PubMed

    Sizun, Christina; Aussenac, Fabien; Grelard, Axelle; Dufourc, Erick J

    2004-02-01

    We present several applications of both wide-line and magic angle spinning (MAS) solid-state NMR of bicelles in which are embedded fragments of a tyrosine kinase receptor or enkephalins. The magnetically orientable bicelle membranes are shown to be of particular interest for studying the functional properties of lipids and proteins in a state that is very close to their natural environment. Quadrupolar, dipolar and chemical shielding interactions can be used to determine minute alterations of internal membrane dynamics and the orientation of peptides with respect to the membrane plane. MAS of bicelles can in turn lead to high-resolution proton spectra of hydrated membranes. Using deuterium-proton contrast methods one can then obtain pseudo-high-resolution proton spectra of peptides or proteins embedded in deuterated membranes and determine their atomic 3D structure using quasi-conventional liquid-state NMR methods. PMID:14745798

  7. Predicting Suicide: Issues, Methods and Constraints.

    ERIC Educational Resources Information Center

    Lettieri, Dan J.

    With the proliferation of suicide prevention centers in the United States, the task of rapidly and effectively assessing an individual caller's suicide potential has become an important research problem. However, the social science researcher is often confronted with an ethical problem when the results of his predictive equations can be used to…

  8. Assay of Protein and Peptide Adducts of Cholesterol Ozonolysis Products by Hydrophobic and Click Enrichment Methods

    PubMed Central

    2015-01-01

    Cholesterol undergoes ozonolysis to afford a variety of oxysterol products, including cholesterol-5,6-epoxide (CholEp) and the isomeric aldehydes secosterol A (seco A) and secosterol B (seco B). These oxysterols display numerous important biological activities, including protein adduction; however, much remains to be learned about the identity of the reactive species and the range of proteins modified by these oxysterols. Here, we synthesized alkynyl derivatives of cholesterol-derived oxysterols and employed a straightforward detection method to establish secosterols A and B as the most protein-reactive of the oxysterols tested. Model adduction studies with an amino acid, peptides, and proteins provide evidence for the potential role of secosterol dehydration products in protein adduction. Hydrophobic separation methods—Folch extraction and solid phase extraction (SPE)—were successfully applied to enrich oxysterol-adducted peptide species, and LC-MS/MS analysis of a model peptide–seco adduct revealed a unique fragmentation pattern (neutral loss of 390 Da) for that species. Coupling a hydrophobic enrichment method with proteomic analysis utilizing characteristic fragmentation patterns facilitates the identification of secosterol-modified peptides and proteins in an adducted protein. More broadly, these improved enrichment methods may give insight into the role of oxysterols and ozone exposure in the pathogenesis of a variety of diseases, including atherosclerosis, Alzheimer’s disease, Parkinson’s disease, and asthma. PMID:25185119

  9. Usefulness of ELISA Methods for Assessing LPS Interactions with Proteins and Peptides

    PubMed Central

    Martínez-Sernández, Victoria; Orbegozo-Medina, Ricardo A.; Romarís, Fernanda; Paniagua, Esperanza; Ubeira, Florencio M.

    2016-01-01

    Lipopolysaccharide (LPS), the major constituent of the outer membrane of Gram-negative bacteria, can trigger severe inflammatory responses during bacterial infections, possibly leading to septic shock. One approach to combatting endotoxic shock is to neutralize the most conserved part and major mediator of LPS activity (lipid A) with LPS-binding proteins or peptides. Although several available assays evaluate the biological activity of these molecules on LPS (e.g. inhibition of LPS-induced TNF-α production in macrophages), the development of simple and cost-effective methods that would enable preliminary screening of large numbers of potential candidate molecules is of great interest. Moreover, it would be also desirable that such methods could provide information about the possible biological relevance of the interactions between proteins and LPS, which may enhance or neutralize LPS-induced inflammatory responses. In this study, we designed and evaluated different types of ELISA that could be used to study possible interactions between LPS and any protein or peptide. We also analysed the usefulness and limitations of the different ELISAs. Specifically, we tested the capacity of several proteins and peptides to bind FITC-labeled LPSs from Escherichia coli serotypes O111:B4 and O55:B5 in an indirect ELISA and in two competitive ELISAs including casein hydrolysate (hCAS) and biotinylated polymyxin B (captured by deglycosylated avidin; PMX) as LPS-binding agents in the solid phase. We also examined the influence of pH, detergents and different blocking agents on LPS binding. Our results showed that the competitive hCAS-ELISA performed under mildly acidic conditions can be used as a general method for studying LPS interactions, while the more restrictive PMX-ELISA may help to identify proteins/peptides that are likely to have neutralizing properties in vitro or in vivo. PMID:27249227

  10. Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for human histocompatibility complex HLA-A0201.

    PubMed

    Guan, Pingping; Doytchinova, Irini A; Walshe, Valerie A; Borrow, Persephone; Flower, Darren R

    2005-11-17

    Amino acid descriptors are often used in quantitative structure-activity relationship (QSAR) analysis of proteins and peptides. In the present study, descriptors were used to characterize peptides binding to the human MHC allele HLA-A0201. Two sets of amino acid descriptors were chosen: 93 descriptors taken from the amino acid descriptor database AAindex and the z descriptors defined by Wold and Sandberg. Variable selection techniques (SIMCA, genetic algorithm, and GOLPE) were applied to remove redundant descriptors. Our results indicate that QSAR models generated using five z descriptors had the highest predictivity and explained variance (q2 between 0.6 and 0.7 and r2 between 0.6 and 0.9). Further to the QSAR analysis, 15 peptides were synthesized and tested using a T2 stabilization assay. All peptides bound to HLA-A0201 well, and four peptides were identified as high-affinity binders. PMID:16279801

  11. Prediction of nucleating sequences from amyloidogenic propensities of tau-related peptides.

    PubMed

    Rojas Quijano, Federico A; Morrow, Dana; Wise, Barry M; Brancia, Francesco L; Goux, Warren J

    2006-04-11

    Physical properties, including amyloid morphology, FTIR and CD spectra, enhancement of Congo red absorbance, polymerization rate, critical monomer concentration, free energy of stabilization, hydrophobicity, and the partition coefficient between soluble and amyloid states, were measured for the tau-related peptide Ac-VQIVYK amide (AcPHF6) and its single site mutants Ac-VQIVXK amide (X not equal Cys). Transmission electron microscopy showed that 15 out of the 19 peptides formed amyloid in buffer, with morphologies ranging from straight and twisted filaments to sheets and rolled sheets. Using principal component analysis (PCA), measured properties were treated in a comprehensive manner, and scores along the most significant principal components were used to define individual amino acid amyloidogenic propensities. Quantitative structure-activity modeling (QSAM) showed that residues with greater size and hydrophobicity made the largest contributions to the propensity of peptides to form amyloid. Using individual amino acid propensities, sequences within tau with high amyloid-forming potential were estimated and found to include 226VAVVR230 in the proline-rich region, 275VQIINK280 (PHF6) and 306VQIVYK311 (PHF6) within the microtubule binding region, and 392IVYK395 in the C-tail region of the protein. The results suggest that regions outside the microtubule-binding region may play important roles in tau aggregation kinetics or paired helical filament structure.

  12. Predicted disease susceptibility in a Panamanian amphibian assemblage based on skin peptide defenses.

    PubMed

    Woodhams, Douglas C; Voyles, Jamie; Lips, Karen R; Carey, Cynthia; Rollins-Smith, Louise A

    2006-04-01

    Chytridiomycosis is an emerging infectious disease of amphibians caused by a chytrid fungus, Batrachochytrium dendrobatidis. This panzootic does not equally affect all amphibian species within an assemblage; some populations decline, others persist. Little is known about the factors that affect disease resistance. Differences in behavior, life history, biogeography, or immune function may impact survival. We found that an innate immune defense, antimicrobial skin peptides, varied significantly among species within a rainforest stream amphibian assemblage that has not been exposed to B. dendrobatidis. If exposed, all amphibian species at this central Panamanian site are at risk of population declines. In vitro pathogen growth inhibition by peptides from Panamanian species compared with species with known resistance (Rana pipiens and Xenopus laevis) or susceptibility (Bufo boreas) suggests that of the nine species examined, two species (Centrolene prosoblepon and Phyllomedusa lemur) may demonstrate strong resistance, and the other species will have a higher risk of disease-associated population declines. We found little variation among geographically distinct B. dendrobatidis isolates in sensitivity to an amphibian skin peptide mixture. This supports the hypothesis that B. dendrobatidis is a generalist pathogen and that species possessing an innate immunologic defense at the time of disease emergence are more likely to survive.

  13. Methods for the creation of cyclic Peptide libraries for use in lead discovery.

    PubMed

    Foster, Andrew D; Ingram, James D; Leitch, Eilidh K; Lennard, Katherine R; Osher, Eliot L; Tavassoli, Ali

    2015-06-01

    The identification of initial hits is a crucial stage in the drug discovery process. Although many projects adopt high-throughput screening of small-molecule libraries at this stage, there is significant potential for screening libraries of macromolecules created using chemical biology approaches. Not only can the production of the library be directly interfaced with a cell-based assay, but these libraries also require significantly fewer resources to generate and maintain. In this context, cyclic peptides are increasingly viewed as ideal scaffolds and have proven capability against challenging targets such as protein-protein interactions. Here we discuss a range of methods used for the creation of cyclic peptide libraries and detail examples of their successful implementation.

  14. Current methods for predicting human food effect.

    PubMed

    Lentz, Kimberley A

    2008-06-01

    Food can impact the pharmacokinetics of a drug product through several mechanisms, including but not limited to, enhancement in drug solubility, changes in GI physiology, or direct interaction with the drug. Significant food effects complicate development of new drugs, especially when clinical plans require control and/or monitoring of food intake in relation to dosing. The prediction of whether a drug or drug product will show a human food effect is challenging. In vitro models which consider physical-chemical properties can classify the potential for a compound to demonstrate a positive, negative or no food effect, and may be appropriate for screening compounds at early stages of drug discovery. When comparing various formulations, dissolution tests in biorelevant media can serve as a predictor of human drug performance under fasted and fed conditions. Few in vivo models exist which predict the magnitude of change in pharmacokinetic parameters in humans when dosing in the presence of food, with the dog appearing to be the most studied species for this purpose. Control of gastric pH, as well as the amount and composition of the fed state in dogs are critical parameters to improving the predictability of the dog overall as a food effect model. No single universal model is applicable for all drugs at all stages of drug development. One or more models may be required depending whether the goal is to assess potential for a food effect, determine the magnitude of change in pharmacokinetic parameters in the fed/fasted state, or whether formulation efforts have the ability to mitigate an observed food effect.

  15. Gaussian mixture models as flux prediction method for central receivers

    NASA Astrophysics Data System (ADS)

    Grobler, Annemarie; Gauché, Paul; Smit, Willie

    2016-05-01

    Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.

  16. Axiomatic methods, dopamine and reward prediction error.

    PubMed

    Caplin, Andrew; Dean, Mark

    2008-04-01

    The phasic firing rate of midbrain dopamine neurons has been shown to respond both to the receipt of rewarding stimuli, and the degree to which such stimuli are anticipated by the recipient. This has led to the hypothesis that these neurons encode reward prediction error (RPE)-the difference between how rewarding an event is, and how rewarding it was expected to be. However, the RPE model is one of a number of competing explanations for dopamine activity that have proved hard to disentangle, mainly because they are couched in terms of latent, or unobservable, variables. This article describes techniques for dealing with latent variables common in economics and decision theory, and reviews work that uses these techniques to provide simple, non-parametric tests of the RPE hypothesis, allowing clear differentiation between competing explanations.

  17. Adaptive method for electron bunch profile prediction

    SciTech Connect

    Scheinker, Alexander; Gessner, Spencer

    2015-10-01

    We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.

  18. A survey of the broadband shock associated noise prediction methods

    NASA Technical Reports Server (NTRS)

    Kim, Chan M.; Krejsa, Eugene A.; Khavaran, Abbas

    1992-01-01

    Several different prediction methods to estimate the broadband shock associated noise of a supersonic jet are introduced and compared with experimental data at various test conditions. The nozzle geometries considered for comparison include a convergent and a convergent-divergent nozzle, both axisymmetric. Capabilities and limitations of prediction methods in incorporating the two nozzle geometries, flight effect, and temperature effect are discussed. Predicted noise field shows the best agreement for a convergent nozzle geometry under static conditions. Predicted results for nozzles in flight show larger discrepancies from data and more dependable flight data are required for further comparison. Qualitative effects of jet temperature, as observed in experiment, are reproduced in predicted results.

  19. Computer prediction of peptide maps: assignment of polypeptides to human and mouse mitochondrial DNA genes by analysis of two-dimensional-proteolytic digest gels.

    PubMed

    Wallace, D C; Yang, J H; Ye, J H; Lott, M T; Oliver, N A; McCarthy, J

    1986-04-01

    We have prepared a computer program that predicts complete and partial peptide maps from amino acid sequences. The program fragments amino acid sequences at designated cleavage sites and calculates the molecular weight and relative labeling of each peptide. These data are graphed as log molecular weight of the original protein (X-axis) vs. log molecular weight of the component peptides (Y-axis). The program is interactive, permitting adjustment of a number of graphic parameters and alteration of the position of proteins in the first dimension to accommodate aberrations in protein mobility. The program has been used to predict the V8 protease peptide maps of the 13 open reading frames (ORFs) identified in the human and the mouse mitochondrial DNA (mtDNA) sequences. The results were compared to the V8 protease peptide maps obtained for mouse and human mitochondrially synthesized proteins by two-dimensional proteolytic digest gels. A high correlation was observed between the predicted and observed peptide maps. These results suggest the assignment of several proteins to mtDNA genes.

  20. Method for Predicting Which Customers' Time Deposit Balances Will Increase

    NASA Astrophysics Data System (ADS)

    Ono, Toshiyuki; Yoshikawa, Hiroshi; Morita, Masahiro; Komoda, Norihisa

    This paper proposes a method of predicting which customers' account balances will increase by using data mining to effectively and efficiently promote sales. Prediction by mining all the data in a business is difficult because of much time required to collect, process, and calculate it. The selection of which features are used for prediction is a critical issue. We propose a method of selecting features to improve the accuracy of prediction within practical time limits. It consists of three parts: (1) converting collected features into financial behavior features that reflect customer actions, (2) extracting features affecting increases in account balances from these collected and financial behavior features, and (3) predicting customers whose account balances will increase based on the extracted features. We found the accuracy of prediction in an experiment with our method to be higher than with other conventional methods.

  1. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  2. A Versatile Nonlinear Method for Predictive Modeling

    NASA Technical Reports Server (NTRS)

    Liou, Meng-Sing; Yao, Weigang

    2015-01-01

    As computational fluid dynamics techniques and tools become widely accepted for realworld practice today, it is intriguing to ask: what areas can it be utilized to its potential in the future. Some promising areas include design optimization and exploration of fluid dynamics phenomena (the concept of numerical wind tunnel), in which both have the common feature where some parameters are varied repeatedly and the computation can be costly. We are especially interested in the need for an accurate and efficient approach for handling these applications: (1) capturing complex nonlinear dynamics inherent in a system under consideration and (2) versatility (robustness) to encompass a range of parametric variations. In our previous paper, we proposed to use first-order Taylor expansion collected at numerous sampling points along a trajectory and assembled together via nonlinear weighting functions. The validity and performance of this approach was demonstrated for a number of problems with a vastly different input functions. In this study, we are especially interested in enhancing the method's accuracy; we extend it to include the second-orer Taylor expansion, which however requires a complicated evaluation of Hessian matrices for a system of equations, like in fluid dynamics. We propose a method to avoid these Hessian matrices, while maintaining the accuracy. Results based on the method are presented to confirm its validity.

  3. Urinary C-peptide as a method for monitoring body mass changes in captive bonobos (Pan paniscus).

    PubMed

    Deschner, Tobias; Kratzsch, Jürgen; Hohmann, Gottfried

    2008-11-01

    In recent years methodological improvements have allowed for more precise estimates of nutrient intake in wild primates. However, estimates of energetic condition have remained relatively imprecise due to the difficulties of estimating digestive efficiency and energy expenditure in these animals. In the absence of a reliable intake-expenditure calculation, a method is needed that directly links changes in energetic condition, such as body mass, to physiological changes that can be detected via markers in body excretions such as urine or feces. One promising marker is C-peptide, a metabolic byproduct of insulin synthesis. Here we present the results of a food restriction experiment carried out in a group of captive bonobos (Pan paniscus). We measured changes in food availability and body mass and determined urinary C-peptide levels with the help of a time-resolved fluoroimmunoassay routinely used for measuring C-peptide in human blood. Urinary C-peptide levels decreased during a period of food restriction and increased again when food availability was continuously increased. During this refeeding phase an increase in body mass was significantly correlated with an increase in urinary C-peptide levels. Our results suggest that urinary C-peptide levels are an accurate indicator of individual energy balance. In conclusion, measuring C-peptide in urine is a promising method to quantify the energetic condition of wild apes.

  4. Methods for predicting wax precipitation and deposition

    SciTech Connect

    Weingarten, J.S.; Euchner, J.A.

    1988-02-01

    Removal of wax from wells and flowlines can account for significant additional operating costs. To evaluate these potential costs, the operating conditions that allow waxes to precipitate in the wellbore must be identified, and deposition rates must be estimated to determine the costs associated with removal of wax deposits. Presented in this paper are laboratory and analytic methods that can be used to estimate both the critical operating conditions and the deposition rates. The laboratory tests and analysis presented may be used to characterize any type of oil.

  5. Methods for predicting wax precipitation and deposition

    SciTech Connect

    Weingarten, J.S.; Euchner, J.A.

    1986-01-01

    Removal of wax from wells and flowlines can account for significant additional operating costs. To evaluate these potential costs, two things must be known. First, the operating conditions which allow waxes to precipitate in the wellbore must be identified. Second, deposition rates must be estimated to determine the costs associated with removal of wax deposits. Presented in this paper are laboratory and analytical methods which can be used to estimate both the critical operating conditions and the deposition rates. The laboratory tests and analysis presented may be used to characterize any type of oil.

  6. Screening and selection of synthetic peptides for a novel and optimized endotoxin detection method.

    PubMed

    Mujika, M; Zuzuarregui, A; Sánchez-Gómez, S; Martínez de Tejada, G; Arana, S; Pérez-Lorenzo, E

    2014-09-30

    The current validated endotoxin detection methods, in spite of being highly sensitive, present several drawbacks in terms of reproducibility, handling and cost. Therefore novel approaches are being carried out in the scientific community to overcome these difficulties. Remarkable efforts are focused on the development of endotoxin-specific biosensors. The key feature of these solutions relies on the proper definition of the capture protocol, especially of the bio-receptor or ligand. The aim of the presented work is the screening and selection of a synthetic peptide specifically designed for LPS detection, as well as the optimization of a procedure for its immobilization onto gold substrates for further application to biosensors. PMID:25034430

  7. Natural ligand motifs of closely related HLA-DR4 molecules predict features of rheumatoid arthritis associated peptides.

    PubMed

    Friede, T; Gnau, V; Jung, G; Keilholz, W; Stevanović, S; Rammensee, H G

    1996-06-01

    Rheumatoid arthritis (RA), one of the most common autoimmune disorders, is believed to be mediated via. T lymphocytes and genetic studies have shown that it is strongly associated with HLA-DR4. The DR4 subtypes DR4Dw4, DR4Dw14 and DR4Dw15 represent increased risk factors for RA, whereas DR4Dw10 is not associated with the disorder. Our study determines and compares the natural ligand motifs of these MHC class II molecules and identifies 60 natural ligands. At relative position 4 (P4), only the RA-associated DR4 molecules allow, or even prefer, negatively charged amino acids, but do not allow those which are positively charged (Arg, Lys). In the case of DR4Dw10 the preference for these amino acids is reversed. The results predict features of the putative RA-inducing peptide(s). A remarkable specificity, almost exclusively for negative charges (Asp, Glu), is found at P9 of the DR4Dw15 motif. This specificity can be ascribed to amino acid beta57 of the DR beta chain, and gives an important insight into the beta57-association of another autoimmune disease, insulin-dependent diabetes mellitus type I. PMID:8672555

  8. Predicting peptide vaccine candidates against H1N1 influenza virus through theoretical approaches.

    PubMed

    Bello, Martiniano; Campos-Rodriguez, Rafael; Rojas-Hernandez, Saul; Contis-Montes de Oca, Arturo; Correa-Basurto, José

    2015-05-01

    Identification of potential epitopes that might activate the immune system has been facilitated by the employment of algorithms that use experimental data as templates. However, in order to prove the affinity and the map of interactions between the receptor (major histocompatibility complex, MHC, or T-cell receptor) and the potential epitope, further computational studies are required. Docking and molecular dynamics (MDs) simulations have been an effective source of generating structural information at molecular level in immunology. Herein, in order to provide a detailed understanding of the origins of epitope recognition and to select the best peptide candidate to develop an epitope-based vaccine, docking and MDs simulations in combination with MMGBSA free energy calculations and per-residue free energy decomposition were performed, taking as starting complexes those formed between four designed epitopes (P1-P4) from hemagglutinin (HA) of the H1N1 influenza virus and MHC-II anchored in POPC membrane. Our results revealed that the energetic contributions of individual amino acids within the pMHC-II complexes are mainly dictated by van der Waals interactions and the nonpolar part of solvation energy, whereas the electrostatic interactions corresponding to hydrogen bonds and salt bridges determine the binding specificity, being the most favorable interactions formed between p4 and MHC-II. Then, P1-P4 epitopes were synthesized and tested experimentally to compare theoretical and experimental results. Experimental results show that P4 elicited the highest strong humoral immune response to HA of the H1N1 and may induce antibodies that are cross-reactive to other influenza subtypes, suggesting that it could be a good candidate for the development of a peptide-based vaccine.

  9. Peptide-based method for detection of metastatic transformation in primary tumors of breast cancer.

    PubMed

    Li, Hao; Huang, Yue; Yu, Yue; Li, Weiwei; Yin, Yongmei; Li, Genxi

    2015-09-15

    Detection of metastatic activity before the onset of the actual metastasis can be a promising method to combat metastasis, the foremost cause of death in cancer. Therefore, in this work, we have developed an assay method for the detection of metastatic tumor cells in primary tumor, by using a protein of the metastatic cell signaling as the biomarker. In this assay, a peptide-based probe targeting the marker protein and a sensitive nanoparticle doped graphene nanolabel are combined to enable the detection of metastatic cells. Consequently, the metastatic cells can be specifically detected and discriminated from primary tumor cells. By applying this assay method to clinical samples of primary tumor, a low amount of metastatic activity can be detected in the tumor sites, which may suggest the activity of local metastatic transformation. So, these results may point to the prospect of using the proposed method for controlling metastatic cancer.

  10. Computational methods in sequence and structure prediction

    NASA Astrophysics Data System (ADS)

    Lang, Caiyi

    This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed

  11. Preliminary thoughts on helicopter cabin noise prediction methods

    NASA Astrophysics Data System (ADS)

    Pollard, J. S.

    The problems of predicting helicopter cabin noise are discussed with particular reference to the Lynx helicopter. Available methods such as modal analysis adopted for propeller noise prediction do not cope with the higher frequency discrete tone content of helicopter gear noise, with the airborne and structureborne noise contributions. Statistical energy analysis methods may be the answer but until these are developed, one has to rely on classical noise transmission analysis and transfer function methods.

  12. Overview of Antioxidant Peptides Derived from Marine Resources: The Sources, Characteristic, Purification, and Evaluation Methods.

    PubMed

    Wu, RiBang; Wu, CuiLing; Liu, Dan; Yang, XingHao; Huang, JiaFeng; Zhang, Jiang; Liao, Binqiang; He, HaiLun; Li, Hao

    2015-08-01

    Marine organisms are rich sources of structurally diverse bioactive nitrogenous components. In recent years, numerous bioactive peptides have been identified in a range of marine protein resources, such as antioxidant peptides. Many studies have approved that marine antioxidant peptides have a positive effect on human health and the food industry. Antioxidant activity of peptides can be attributed to free radicals scavenging, inhibition of lipid peroxidation, and metal ion chelating. Moreover, it has also been verified that peptide structure and its amino acid sequence can mainly affect its antioxidant properties. The aim of this review is to summarize kinds of antioxidant peptides from various marine resources. Additionally, the relationship between structure and antioxidant activities of peptides is discussed in this paper. Finally, current technologies used in the preparation, purification, and evaluation of marine-derived antioxidant peptides are also reviewed.

  13. Experimental validation of boundary element methods for noise prediction

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Oswald, Fred B.

    1992-01-01

    Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

  14. Critical evaluation of in silico methods for prediction of coiled-coil domains in proteins.

    PubMed

    Li, Chen; Ching Han Chang, Catherine; Nagel, Jeremy; Porebski, Benjamin T; Hayashida, Morihiro; Akutsu, Tatsuya; Song, Jiangning; Buckle, Ashley M

    2016-03-01

    Coiled-coils refer to a bundle of helices coiled together like strands of a rope. It has been estimated that nearly 3% of protein-encoding regions of genes harbour coiled-coil domains (CCDs). Experimental studies have confirmed that CCDs play a fundamental role in subcellular infrastructure and controlling trafficking of eukaryotic cells. Given the importance of coiled-coils, multiple bioinformatics tools have been developed to facilitate the systematic and high-throughput prediction of CCDs in proteins. In this article, we review and compare 12 sequence-based bioinformatics approaches and tools for coiled-coil prediction. These approaches can be categorized into two classes: coiled-coil detection and coiled-coil oligomeric state prediction. We evaluated and compared these methods in terms of their input/output, algorithm, prediction performance, validation methods and software utility. All the independent testing data sets are available at http://lightning.med.monash.edu/coiledcoil/. In addition, we conducted a case study of nine human polyglutamine (PolyQ) disease-related proteins and predicted CCDs and oligomeric states using various predictors. Prediction results for CCDs were highly variable among different predictors. Only two peptides from two proteins were confirmed to be CCDs by majority voting. Both domains were predicted to form dimeric coiled-coils using oligomeric state prediction. We anticipate that this comprehensive analysis will be an insightful resource for structural biologists with limited prior experience in bioinformatics tools, and for bioinformaticians who are interested in designing novel approaches for coiled-coil and its oligomeric state prediction. PMID:26177815

  15. Probing Alzheimer amyloid peptide aggregation using a cell-free fluorescent protein refolding method.

    PubMed

    Arslan, Pharhad Eli; Chakrabartty, Avijit

    2009-08-01

    Fibrillation of the Alzheimer beta-amyloid peptide (Abeta) and (or) formation of toxic oligomers are key pathological events in Alzheimer's disease. Several strategies have been introduced to identify small molecule aggregation inhibitors, and based on these methods, a number of aggregation inhibitors have been identified. However, most of these methods use chemically synthesized Abeta42 peptides, which are difficult to maintain in a monomeric state at neutral pH where anti-aggregation screening is usually carried out. We have developed a cell-free Abeta42 aggregation assay based on fluorescence protein refolding. This assay utilizes nanomolar concentrations of protein. We genetically fused Abeta42 to the N-terminus of vYFP, a variant of of GFP, and expressed and purified the folded fusion protein. The refolding efficiency of Abeta42-vYFP fusion was inversely correlated with the solubility of Abeta42. Using fluorescence to monitor refolding of Abeta42-vYFP, we confirmed that Zn2+ binds to Abeta42 and increases its aggregation. The IC50 value estimated for Zn binding is 3.03 +/- 0.65 micromol/L. We also show that this technique is capable of monitoring the aggregation of chemically synthesized Abeta42.

  16. In vitro susceptibility tests for cationic peptides: comparison of broth microdilution methods for bacteria that grow aerobically.

    PubMed

    Giacometti, A; Cirioni, O; Barchiesi, F; Del Prete, M S; Fortuna, M; Caselli, F; Scalise, G

    2000-06-01

    The in vitro susceptibilities of 90 clinical isolates of gram-positive and gram-negative aerobic bacteria to six cationic peptides, buforin II, cecropin P1, indolicidin, magainin II, nisin, and ranalexin, were evaluated by two broth microdilution methods. The first method was performed according to the procedures outlined by the National Committee for Clinical Laboratory Standards for bacteria that grow aerobically, while the second was performed according to the procedures recently proposed by the R. E. W. Hancock laboratory for testing antimicrobial peptides. Overall, the first method produced MICs two- and fourfold higher than the second method. PMID:10817731

  17. What Predicts Use of Learning-Centered, Interactive Engagement Methods?

    ERIC Educational Resources Information Center

    Madson, Laura; Trafimow, David; Gray, Tara; Gutowitz, Michael

    2014-01-01

    What makes some faculty members more likely to use interactive engagement methods than others? We use the theory of reasoned action to predict faculty members' use of interactive engagement methods. Results indicate that faculty members' beliefs about the personal positive consequences of using these methods (e.g., "Using…

  18. Predicted Peptides from Non-Structural Proteins of Porcine Reproductive and Respiratory Syndrome Virus Are Able to Induce IFN-γ and IL-10

    PubMed Central

    Burgara-Estrella, Alexel; Díaz, Ivan; Rodríguez-Gómez, Irene M.; Essler, Sabine E.; Hernández, Jesús; Mateu, Enric

    2013-01-01

    This work describes peptides from non-structural proteins (nsp) of porcine reproductive and respiratory syndrome virus (PRRSV) predicted as potential T cell epitopes by bioinfornatics and tested for their ability to induce IFN-γ and IL-10 responses. Pigs immunized with either genotype 1 or genotype 2 PRRSV attenuated vaccines (n=5/group) and unvaccinated pigs (n = 4) were used to test the peptides. Swine leukocyte antigen haplotype of each pig was also determined. Pigs were initially screened for IFN-γ responses (ELISPOT) and three peptides were identified; two of them in non-conserved segments of nsp2 and nsp5 and the other in a conserved region of nsp5 peptide. Then, peptides were screened for IL-10 inducing properties. Six peptides were found to induce IL-10 release in PBMC and some of them were also able to inhibit IFN-γ responses on PHA-stimulated cells. Interestingly, the IFN-γ low responder pigs against PRRSV were mostly homozygous for their SLA haplotypes. In conclusion, these results indicate that nsp of PRRSV contain T-cell epitopes inducing IFN-γ responses as well as IL-10 inducing segments with inhibitory capabilities. PMID:23435238

  19. Identification of bioactive peptides in a functional yogurt by micro liquid chromatography time-of-flight mass spectrometry assisted by retention time prediction.

    PubMed

    Kunda, Pradeep B; Benavente, Fernando; Catalá-Clariana, Sergio; Giménez, Estela; Barbosa, José; Sanz-Nebot, Victoria

    2012-03-16

    In this study we used micro liquid chromatography coupled to time-of-flight mass spectrometry (microLC-TOF-MS) for separation and identification of bioactive peptides in a yogurt marketed as an antihypertensive functional food. An appropriate sample clean-up using solid-phase extraction (SPE) allowed detection of a large number of low-molecular-mass bioactive peptides by reversed-phase microLC-TOF-MS. The preliminary identification was solely based on the experimental monoisotopic molecular mass values (M(exp)). Later, we evaluated the correlations between predicted normalized elution time (NET) and experimental normalized retention times (t(r)') values to describe the retention behavior of the proposed sequences. The assistance of retention prediction proved to be useful to improve reliability of the identification, avoiding misinterpretations and solving some identity conflicts. After revision, the identity of only fifty bioactive peptides was confirmed. Significant number of these peptides was reported as angiotensin converting enzyme (ACE) inhibitors and nine of them were antihypertensive. The presence of peptide sequences with other biological activities such as antibacterial, antithrombotic, antioxidant, cell modulation, immune or phagocytosis stimulation, epitopes of B cells and opioid agonists was also confirmed.

  20. AVP-IC50 Pred: Multiple machine learning techniques-based prediction of peptide antiviral activity in terms of half maximal inhibitory concentration (IC50).

    PubMed

    Qureshi, Abid; Tandon, Himani; Kumar, Manoj

    2015-11-01

    Peptide-based antiviral therapeutics has gradually paved their way into mainstream drug discovery research. Experimental determination of peptides' antiviral activity as expressed by their IC50 values involves a lot of effort. Therefore, we have developed "AVP-IC50 Pred," a regression-based algorithm to predict the antiviral activity in terms of IC50 values (μM). A total of 759 non-redundant peptides from AVPdb and HIPdb were divided into a training/test set having 683 peptides (T(683)) and a validation set with 76 independent peptides (V(76)) for evaluation. We utilized important peptide sequence features like amino-acid compositions, binary profile of N8-C8 residues, physicochemical properties and their hybrids. Four different machine learning techniques (MLTs) namely Support vector machine, Random Forest, Instance-based classifier, and K-Star were employed. During 10-fold cross validation, we achieved maximum Pearson correlation coefficients (PCCs) of 0.66, 0.64, 0.56, 0.55, respectively, for the above MLTs using the best combination of feature sets. All the predictive models also performed well on the independent validation dataset and achieved maximum PCCs of 0.74, 0.68, 0.59, 0.57, respectively, on the best combination of feature sets. The AVP-IC50 Pred web server is anticipated to assist the researchers working on antiviral therapeutics by enabling them to computationally screen many compounds and focus experimental validation on the most promising set of peptides, thus reducing cost and time efforts. The server is available at http://crdd.osdd.net/servers/ic50avp.

  1. A method to objectively optimize coral bleaching prediction techniques

    NASA Astrophysics Data System (ADS)

    van Hooidonk, R. J.; Huber, M.

    2007-12-01

    Thermally induced coral bleaching is a global threat to coral reef health. Methodologies, e.g. the Degree Heating Week technique, have been developed to predict bleaching induced by thermal stress by utilizing remotely sensed sea surface temperature (SST) observations. These techniques can be used as a management tool for Marine Protected Areas (MPA). Predictions are valuable to decision makers and stakeholders on weekly to monthly time scales and can be employed to build public awareness and support for mitigation. The bleaching problem is only expected to worsen because global warming poses a major threat to coral reef health. Indeed, predictive bleaching methods combined with climate model output have been used to forecast the global demise of coral reef ecosystems within coming decades due to climate change. Accuracy of these predictive techniques has not been quantitatively characterized despite the critical role they play. Assessments have typically been limited, qualitative or anecdotal, or more frequently they are simply unpublished. Quantitative accuracy assessment, using well established methods and skill scores often used in meteorology and medical sciences, will enable objective optimization of existing predictive techniques. To accomplish this, we will use existing remotely sensed data sets of sea surface temperature (AVHRR and TMI), and predictive values from techniques such as the Degree Heating Week method. We will compare these predictive values with observations of coral reef health and calculate applicable skill scores (Peirce Skill Score, Hit Rate and False Alarm Rate). We will (a) quantitatively evaluate the accuracy of existing coral reef bleaching predictive methods against state-of- the-art reef health databases, and (b) present a technique that will objectively optimize the predictive method for any given location. We will illustrate this optimization technique for reefs located in Puerto Rico and the US Virgin Islands.

  2. A peptide ELISA to detect antibodies against Pythium insidiosum based on predicted antigenic determinants of exo-1,3-beta-glucanase.

    PubMed

    Keeratijarut, Angsana; Lohnoo, Tassanee; Yingyong, Wanta; Sriwanichrak, Kanchana; Krajaejun, Theerapong

    2013-07-01

    Human pythiosis is a life-threatening infectious disease caused by the oomycete Pythium insidiosum. Diagnosis of pythiosis relies on culture identification, serodiagnosis, and molecular-based assay. Preparation of a serodiagnostic test requires culture filtrate antigen (CFA) extracted from the live pathogen. A 74-kDa immunoreactive protein of P. insidiosum, is encoded by the exo-1,3-beta-glucanase gene (PinsEXO1). PinsEXO1 protein is recognized by sera from pythiosis patients but not by sera from uninfected patients; therefore, this protein could be used to detect anti-P. insidiosum antibodies. In this study we aimed to: identify, synthesize, and evaluate an antigenic determinant (epitope) of PinsEXO1 to be used to serodiagnose pythiosis based on peptide ELISA, and to compare the diagnostic performance of that test with the current CFA-based ELISA. Two antigenic determinants of PinsEXO1 (Peptide-A and -B) were predicted using the PREDITOP program. The sera from 34 pythiosis patients and 92 control subjects were evaluated. Peptide-A, Peptide-B, and CFA-based ELISAs all had a specificity of 100%. Peptide-B ELISA had a sensitivity of 91% and an accuracy of 98% and both Peptide-A and CFA-based ELISAs had a sensitivity of 100% and an accuracy of 100%. Peptide-A is a more efficient epitope than Peptide-B, and can be used as an alternative antigen to develop a serodiagnostic assay for pythiosis. PMID:24050102

  3. High Throughput Screening Methods for Assessing Antibiofilm and Immunomodulatory Activities of Synthetic Peptides

    PubMed Central

    Haney, Evan F.; Mansour, Sarah; Hilchie, Ashley L.; de la Fuente-Núñez, César; Hancock, Robert E.W.

    2015-01-01

    The recent observation that certain cationic peptides possess potent antibiofilm activity demonstrated that small peptides could be used to treat biofilm-associated infections. Other so-called innate defense regulator peptides possess potent immunomodulatory properties such as leukocyte recruitment and suppression of harmful inflammation. A peptide that directly targets biofilm cells while favourably modulating the immune response would be particularly advantageous for treating serious skin infections caused by S. aureus. In the present work, using SPOT-synthesized peptide arrays on cellulose membranes, we outline a strategy for systematically assessing the antibiofilm activity of hundreds of IDR-1002 (VQRWLIVWRIRK-NH2) and IDR-HH2 (VQLRIRVAVIRA-NH2) peptide variants against MRSA biofilms. In addition, the ability of these peptides to stimulate production of a monocyte chemoattractant protein (MCP-1) and suppress LPS-induced interleukin (IL)-1β production in human peripheral blood mononuclear cells (PBMCs) was evaluated. These results informed the synthesis of second-generation peptides resulting in a new peptide, IDR-2009 (KWRLLIRWRIQK-NH2), with enhanced MCP-1 stimulatory activity, favourable IL-1β suppression characteristics and strong antibiofilm activity against MRSA and Pseudomonas aeruginosa biofilms. This work provides a proof-of-concept that multiple peptide activities can be optimized simultaneously to generate novel sequences that possess a variety of biological properties. PMID:25836992

  4. Modified-Fibonacci-Dual-Lucas method for earthquake prediction

    NASA Astrophysics Data System (ADS)

    Boucouvalas, A. C.; Gkasios, M.; Tselikas, N. T.; Drakatos, G.

    2015-06-01

    The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with

  5. Optimization of Preparation of Antioxidative Peptides from Pumpkin Seeds Using Response Surface Method

    PubMed Central

    Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

    2014-01-01

    Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%. PMID:24637721

  6. Optimization of preparation of antioxidative peptides from pumpkin seeds using response surface method.

    PubMed

    Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

    2014-01-01

    Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%.

  7. Prediction methods of spudcan penetration for jack-up units

    NASA Astrophysics Data System (ADS)

    Zhang, Ai-xia; Duan, Meng-lan; Li, Hai-ming; Zhao, Jun; Wang, Jian-jun

    2012-12-01

    Jack-up units are extensively playing a successful role in drilling engineering around the world, and their safety and efficiency take more and more attraction in both research and engineering practice. An accurate prediction of the spudcan penetration depth is quite instrumental in deciding on whether a jack-up unit is feasible to operate at the site. The prediction of a too large penetration depth may lead to the hesitation or even rejection of a site due to potential difficulties in the subsequent extraction process; the same is true of a too small depth prediction due to the problem of possible instability during operation. However, a deviation between predictive results and final field data usually exists, especially when a strong-over-soft soil is included in the strata. The ultimate decision sometimes to a great extent depends on the practical experience, not the predictive results given by the guideline. It is somewhat risky, but no choice. Therefore, a feasible predictive method for the spudcan penetration depth, especially in strata with strong-over-soft soil profile, is urgently needed by the jack-up industry. In view of this, a comprehensive investigation on methods of predicting spudcan penetration is executed. For types of different soil profiles, predictive methods for spudcan penetration depth are proposed, and the corresponding experiment is also conducted to validate these methods. In addition, to further verify the feasibility of the proposed methods, a practical engineering case encountered in the South China Sea is also presented, and the corresponding numerical and experimental results are also presented and discussed.

  8. The trajectory prediction of spacecraft by grey method

    NASA Astrophysics Data System (ADS)

    Wang, Qiyue; Zhang, Zili; Wang, Zhongyu; Wang, Yanqing; Zhou, Weihu

    2016-08-01

    The real-time and high-precision trajectory prediction of a moving object is a core technology in the field of aerospace engineering. The real-time monitoring and tracking technology are also significant guarantees of aerospace equipment. A dynamic trajectory prediction method called grey dynamic filter (GDF) which combines the dynamic measurement theory and grey system theory is proposed. GDF can use coordinates of the current period to extrapolate coordinates of the following period. At meantime, GDF can also keep the instantaneity of measured coordinates by the metabolism model. In this paper the optimal model length of GDF is firstly selected to improve the prediction accuracy. Then the simulation for uniformly accelerated motion and variably accelerated motion is conducted. The simulation results indicate that the mean composite position error of GDF prediction is one-fifth to that of Kalman filter (KF). By using a spacecraft landing experiment, the prediction accuracy of GDF is compared with the KF method and the primitive grey method (GM). The results show that the motion trajectory of spacecraft predicted by GDF is much closer to actual trajectory than the other two methods. The mean composite position error calculated by GDF is one-eighth to KF and one-fifth to GM respectively.

  9. Predicting sediment yield from alternative surface mining methods

    SciTech Connect

    Warner, R.C.; Wells, L.G.; Barfield, B.J.; Moore, I.D.; Wilson, B.N.

    1982-12-01

    The focus of this research was to compare the predicted sediment yield and hydrologic impact of three alternative surface mining methods used in the Central and Southern Appalachian coal regions. The mining methods investigated were: 1) mountaintop removal, 2) post-1977 block-cut haul-back contour mining, and 3) pre-1977 contour mining. Sediment and hydrologic impacts were predicted through use of the SEDIMOT model. For the mine plans analyzed the post-1977 block-cut haul-back mining method produced significantly lower sediment and peak storm response.

  10. An Updated Test of AMBER Force Fields and Implicit Solvent Models in Predicting the Secondary Structure of Helical, β-Hairpin, and Intrinsically Disordered Peptides.

    PubMed

    Maffucci, Irene; Contini, Alessandro

    2016-02-01

    Replica exchange molecular dynamics simulations were performed to test the ability of six AMBER force fields and three implicit solvent models of predicting the native conformation of two helical peptides, three β-hairpins, and three intrinsically disordered peptides. Although a combination of the force field and implicit solvation models able to accurately predict the native structure of all the considered peptides was not identified, we found that the GB-Neck2 model seems to well compensate for some of the conformational biases showed by ff96 and ff99SB/ildn/ildn-φ. Indeed, the force fields of the ff99SB series coupled with GB-Neck2 reasonably discriminated helices from disordered peptides, while a good prediction of β-hairpin conformations was only achieved by performing two independent simulations: one with the ff96/GB-Neck2 combination and the other with GB-Neck2 coupled with any of the ff99SB/ildn/ildn-φ force fields.

  11. Computational Methods for Failure Analysis and Life Prediction

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler); Harris, Charles E. (Compiler); Housner, Jerrold M. (Compiler); Hopkins, Dale A. (Compiler)

    1993-01-01

    This conference publication contains the presentations and discussions from the joint UVA/NASA Workshop on Computational Methods for Failure Analysis and Life Prediction held at NASA Langley Research Center 14-15 Oct. 1992. The presentations focused on damage failure and life predictions of polymer-matrix composite structures. They covered some of the research activities at NASA Langley, NASA Lewis, Southwest Research Institute, industry, and universities. Both airframes and propulsion systems were considered.

  12. Brain natriuretic peptide predicts forced vital capacity of the lungs, oxygen pulse and peak oxygen consumption in physiological condition.

    PubMed

    Popovic, Dejana; Ostojic, Miodrag C; Popovic, Bojana; Petrovic, Milan; Vujisic-Tesic, Bosiljka; Kocijancic, Aleksandar; Banovic, Marko; Arandjelovic, Aleksandra; Stojiljkovic, Stanimir; Markovic, Vidan; Damjanovic, Svetozar S

    2013-05-01

    Brain natriuretic peptide (NT-pro-BNP) is used as marker of cardiac and pulmonary diseases. However, the predictive value of circulating NT-pro-BNP for cardiac and pulmonary performance is unclear in physiological conditions. Standard echocardiography, tissue Doppler and forced spirometry at rest were used to assess cardiac parameters and forced vital capacity (FVC) in two groups of athletes (16 elite male wrestlers (W), 21 water polo player (WP)), as different stress adaptation models, and 20 sedentary subjects (C) matched for age. Cardiopulmonary test on treadmill (CPET), as acute stress model, was used to measure peak oxygen consumption (peak VO2), maximal heart rate (HRmax) and peak oxygen pulse (peak VO2/HR). NT-pro-BNP was measured by immunoassey sandwich technique 10min before the test - at rest, at the beginning of the test, at maximal effort, at third minute of recovery. FVC was higher in athletes and the highest in W (WP 5.60±0.29 l; W 6.57±1.00 l; C 5.41±0.29 l; p<0.01). Peak VO2 and peak VO2/HR were higher in athletes and the highest in WP. HRmax was not different among groups. In all groups, NT-pro-BNP decreased from rest to the beginning phase, increased in maximal effort and stayed unchanged in recovery. NT-pro-BNP was higher in C than W in all phases; WP had similar values as W and C. On multiple regression analysis, in all three groups together, ΔNT-pro-BNP from rest to the beginning phase independently predicted both peak VO2 and peak VO2/HR (r=0.38, 0.35; B=37.40, 0.19; p=0.007, 0.000, respectively). NT-pro-BNP at rest predicted HRmax (r=-0.32, B=-0.22, p=0.02). Maximal NT-pro-BNP predicted FVC (r=-0.22, B=-0.07, p=0.02). These results show noticeable predictive value of NT-pro-BNP for both cardiac and pulmonary performance in physiological conditions suggesting that NT-pro-BNP could be a common regulatory factor coordinating adaptation of heart and lungs to stress condition.

  13. Accuracy of Four Tooth Size Prediction Methods on Malay Population

    PubMed Central

    Mahmoud, Belal Khaled; Abu Asab, Saifeddin Hamed I.; Taib, Haslina

    2012-01-01

    Objective. To examine the accuracy of Moyers 50%, Tanaka and Johnston, Ling and Wong and Jaroontham and Godfrey methods in predicting the mesio-distal crown width of the permanent canines and premolars (C + P1 + P2) in Malay population. Materials and Methods. The study models of 240 Malay children (120 males and 120 females) aged 14 to 18 years, all free of any signs of dental pathology or anomalies, were measured using a digital caliper accurate to 0.01 mm. The predicted widths (C + P1 + P2) in both arches derived from the tested prediction equations were compared with the actual measured widths. Results. Moyers and Tanaka and Johnston methods showed significant difference between the actual and predicted widths of (C + P1 + P2) for both sexes. Ling and Wong method also showed statistically significant difference for males, however, there was no significant difference for females. Jaroontham and Godfrey method showed statistical significant difference for females, but the male values did not show any significant difference. Conclusion. For male Malay, the method proposed by Jaroontham and Godfrey for male Thai proved to be highly accurate. For female Malay, the method proposed by Ling and Wong for southern Chinese females proved to be highly accurate. PMID:23209918

  14. A simple method of predicting S-wave velocity

    USGS Publications Warehouse

    Lee, M.W.

    2006-01-01

    Prediction of shear-wave velocity plays an important role in seismic modeling, amplitude analysis with offset, and other exploration applications. This paper presents a method for predicting S-wave velocity from the P-wave velocity on the basis of the moduli of dry rock. Elastic velocities of water-saturated sediments at low frequencies can be predicted from the moduli of dry rock by using Gassmann's equation; hence, if the moduli of dry rock can be estimated from P-wave velocities, then S-wave velocities easily can be predicted from the moduli. Dry rock bulk modulus can be related to the shear modulus through a compaction constant. The numerical results indicate that the predicted S-wave velocities for consolidated and unconsolidated sediments agree well with measured velocities if differential pressure is greater than approximately 5 MPa. An advantage of this method is that there are no adjustable parameters to be chosen, such as the pore-aspect ratios required in some other methods. The predicted S-wave velocity depends only on the measured P-wave velocity and porosity. ?? 2006 Society of Exploration Geophysicists.

  15. Diagnosis of bacterial vaginosis by a new multiplex peptide nucleic acid fluorescence in situ hybridization method.

    PubMed

    Machado, António; Castro, Joana; Cereija, Tatiana; Almeida, Carina; Cerca, Nuno

    2015-01-01

    Bacterial vaginosis (BV) is one of most common vaginal infections. However, its diagnosis by classical methods reveals low specificity. Our goal was to evaluate the accuracy diagnosis of 150 vaginal samples with research gold standard methods and our Peptide Nucleic Acid (PNA) probes by Fluorescence in situ Hybridization (FISH) methodology. Also, we described the first PNA-FISH methodology for BV diagnosis, which provides results in approximately 3 h. The results showed a sensitivity of 84.6% (95% confidence interval (CI), from 64.3 to 95.0%) and a specificity of 97.6% (95% CI [92.6-99.4%]), demonstrating the higher specificity of the PNA-FISH method and showing false positive results in BV diagnosis commonly obtained by the classical methods. This methodology combines the specificity of PNA probes for Lactobacillus species and G. vaginalis visualization and the calculation of the microscopic field by Nugent score, allowing a trustful evaluation of the bacteria present in vaginal microflora and avoiding the occurrence of misleading diagnostics. Therefore, the PNA-FISH methodology represents a valuable alternative for BV diagnosis. PMID:25737820

  16. Diagnosis of bacterial vaginosis by a new multiplex peptide nucleic acid fluorescence in situ hybridization method

    PubMed Central

    Machado, António; Castro, Joana; Cereija, Tatiana; Almeida, Carina

    2015-01-01

    Bacterial vaginosis (BV) is one of most common vaginal infections. However, its diagnosis by classical methods reveals low specificity. Our goal was to evaluate the accuracy diagnosis of 150 vaginal samples with research gold standard methods and our Peptide Nucleic Acid (PNA) probes by Fluorescence in situ Hybridization (FISH) methodology. Also, we described the first PNA-FISH methodology for BV diagnosis, which provides results in approximately 3 h. The results showed a sensitivity of 84.6% (95% confidence interval (CI), from 64.3 to 95.0%) and a specificity of 97.6% (95% CI [92.6–99.4%]), demonstrating the higher specificity of the PNA-FISH method and showing false positive results in BV diagnosis commonly obtained by the classical methods. This methodology combines the specificity of PNA probes for Lactobacillus species and G. vaginalis visualization and the calculation of the microscopic field by Nugent score, allowing a trustful evaluation of the bacteria present in vaginal microflora and avoiding the occurrence of misleading diagnostics. Therefore, the PNA-FISH methodology represents a valuable alternative for BV diagnosis. PMID:25737820

  17. Evaluation of Methods to Predict Reactivity of Gold Nanoparticles

    SciTech Connect

    Allison, Thomas C.; Tong, Yu ye J.

    2011-06-20

    Several methods have appeared in the literature for predicting reactivity on metallic surfaces and on the surface of metallic nanoparticles. All of these methods have some relationship to the concept of frontier molecular orbital theory. The d-band theory of Hammer and Nørskov is perhaps the most widely used predictor of reactivity on metallic surfaces, and it has been successfully applied in many cases. Use of the Fukui function and the condensed Fukui function is well established in organic chemistry, but has not been so widely applied in predicting the reactivity of metallic nanoclusters. In this article, we will evaluate the usefulness of the condensed Fukui function in predicting the reactivity of a family of cubo-octahedral gold nanoparticles and make comparison with the d-band method.

  18. A comparative study of extraction methods reveals preferred solvents for cystine knot peptide isolation from Momordica cochinchinensis seeds.

    PubMed

    Mahatmanto, Tunjung; Poth, Aaron G; Mylne, Joshua S; Craik, David J

    2014-06-01

    MCoTI-I and MCoTI-II (short for Momordica cochinchinensis Trypsin Inhibitor-I and -II, respectively) are attractive candidates for developing novel intracellular-targeting drugs because both are exceptionally stable and can internalize into cells. These seed-derived cystine knot peptides are examples of how natural product discovery efforts can lead to biomedical applications. However, discovery efforts are sometimes hampered by the limited availability of seed materials, highlighting the need for efficient extraction methods. In this study, we assessed five extraction methods using M. cochinchinensis seeds, a source of well-characterized cystine knot peptides. The most efficient extraction of nine known cystine knot peptides was achieved by a method based on acetonitrile/water/formic acid (25:24:1), followed by methods based on sodium acetate (20 mM, pH 5.0), ammonium bicarbonate (5 mM, pH 8.0), and boiling water. On average, the yields obtained by these four methods were more than 250-fold higher than that obtained using dichloromethane/methanol (1:1) extraction, a previously applied standard method. Extraction using acetonitrile/water/formic acid (25:24:1) yielded the highest number of reconstructed masses within the majority of plant-derived cystine knot peptide mass range but only accounted for around 50% of the total number of masses, indicating that any single method may result in under-sampling. Applying acetonitrile/water/formic acid (25:24:1), boiling water, and ammonium bicarbonate (5 mM, pH 8.0) extractions either successively or discretely significantly increased the sampling number. Overall, acetonitrile/water/formic acid (25:24:1) can facilitate efficient extraction of cystine-knot peptides from M. cochinchinensis seeds but for discovery purposes the use of a combination of extraction methods is recommended where practical. PMID:24613804

  19. A comparative study of extraction methods reveals preferred solvents for cystine knot peptide isolation from Momordica cochinchinensis seeds.

    PubMed

    Mahatmanto, Tunjung; Poth, Aaron G; Mylne, Joshua S; Craik, David J

    2014-06-01

    MCoTI-I and MCoTI-II (short for Momordica cochinchinensis Trypsin Inhibitor-I and -II, respectively) are attractive candidates for developing novel intracellular-targeting drugs because both are exceptionally stable and can internalize into cells. These seed-derived cystine knot peptides are examples of how natural product discovery efforts can lead to biomedical applications. However, discovery efforts are sometimes hampered by the limited availability of seed materials, highlighting the need for efficient extraction methods. In this study, we assessed five extraction methods using M. cochinchinensis seeds, a source of well-characterized cystine knot peptides. The most efficient extraction of nine known cystine knot peptides was achieved by a method based on acetonitrile/water/formic acid (25:24:1), followed by methods based on sodium acetate (20 mM, pH 5.0), ammonium bicarbonate (5 mM, pH 8.0), and boiling water. On average, the yields obtained by these four methods were more than 250-fold higher than that obtained using dichloromethane/methanol (1:1) extraction, a previously applied standard method. Extraction using acetonitrile/water/formic acid (25:24:1) yielded the highest number of reconstructed masses within the majority of plant-derived cystine knot peptide mass range but only accounted for around 50% of the total number of masses, indicating that any single method may result in under-sampling. Applying acetonitrile/water/formic acid (25:24:1), boiling water, and ammonium bicarbonate (5 mM, pH 8.0) extractions either successively or discretely significantly increased the sampling number. Overall, acetonitrile/water/formic acid (25:24:1) can facilitate efficient extraction of cystine-knot peptides from M. cochinchinensis seeds but for discovery purposes the use of a combination of extraction methods is recommended where practical.

  20. Predicting Spacecraft Trajectories by the WeavEncke Method

    NASA Technical Reports Server (NTRS)

    Weaver, Jonathan K.; Adamo, Daniel R.

    2011-01-01

    A combination of methods is proposed of predicting spacecraft trajectories that possibly include multiple maneuvers and/or perturbing accelerations, with greater speed, accuracy, and repeatability than were heretofore achievable. The combination is denoted the WeavEncke method because it is based on unpublished studies by Jonathan Weaver of the orbit-prediction formulation of the noted astronomer Johann Franz Encke. Weaver evaluated a number of alternatives that arise within that formulation, arriving at an orbit-predicting algorithm optimized for complex trajectory operations. In the WeavEncke method, Encke's method of prediction of perturbed orbits is enhanced by application of modern numerical methods. Among these methods are efficient Kepler s-equation time-of-flight solutions and self-starting numerical integration with time as the independent variable. Self-starting numerical integration satisfies the requirements for accuracy, reproducibility, and efficiency (and, hence, speed). Self-starting numerical integration also supports fully analytic regulation of integration step sizes, thereby further increasing speed while maintaining accuracy.

  1. An analytical method to predict efficiency of aircraft gearboxes

    NASA Technical Reports Server (NTRS)

    Anderson, N. E.; Loewenthal, S. H.; Black, J. D.

    1984-01-01

    A spur gear efficiency prediction method previously developed by the authors was extended to include power loss of planetary gearsets. A friction coefficient model was developed for MIL-L-7808 oil based on disc machine data. This combined with the recent capability of predicting losses in spur gears of nonstandard proportions allows the calculation of power loss for complete aircraft gearboxes that utilize spur gears. The method was applied to the T56/501 turboprop gearbox and compared with measured test data. Bearing losses were calculated with large scale computer programs. Breakdowns of the gearbox losses point out areas for possible improvement.

  2. A correction method suitable for dynamical seasonal prediction

    NASA Astrophysics Data System (ADS)

    Chen, H.; Lin, Z. H.

    2006-05-01

    Based on the hindcast results of summer rainfall anomalies over China for the period 1981-2000 by the Dynamical Climate Prediction System (IAP-DCP) developed by the Institute of Atmospheric Physics, a correction method that can account for the dependence of model's systematic biases on SST anomalies is proposed. It is shown that this correction method can improve the hindcast skill of the IAP-DCP for summer rainfall anomalies over China, especially in western China and southeast China, which may imply its potential application to real-time seasonal prediction.

  3. Preface to the Focus Issue: Chaos Detection Methods and Predictability

    SciTech Connect

    Gottwald, Georg A.; Skokos, Charalampos

    2014-06-01

    This Focus Issue presents a collection of papers originating from the workshop Methods of Chaos Detection and Predictability: Theory and Applications held at the Max Planck Institute for the Physics of Complex Systems in Dresden, June 17–21, 2013. The main aim of this interdisciplinary workshop was to review comprehensively the theory and numerical implementation of the existing methods of chaos detection and predictability, as well as to report recent applications of these techniques to different scientific fields. The collection of twelve papers in this Focus Issue represents the wide range of applications, spanning mathematics, physics, astronomy, particle accelerator physics, meteorology and medical research. This Preface surveys the papers of this Issue.

  4. Developing a comparative docking protocol for the prediction of peptide selectivity profiles: investigation of potassium channel toxins.

    PubMed

    Chen, Po-Chia; Kuyucak, Serdar

    2012-02-01

    During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to "predict" the various selectivity profiles of several major αKTX scorpion toxin families versus K(v)1.1, K(v)1.2 and K(v)1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and K(v)1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.

  5. Development of aerodynamic prediction methods for irregular planform wings

    NASA Technical Reports Server (NTRS)

    Benepe, D. B., Sr.

    1983-01-01

    A set of empirical methods was developed to predict low-speed lift, drag and pitching-moment variations with angle of attack for a class of low aspect ratio irregular planform wings suitable for application to advanced aerospace vehicles. The data base, an extensive series of wind-tunnel tests accomplished by the Langley Research Center of the National Aeronautics and Space Administration, is summarized. The approaches used to analyze the wind tunnel data, the evaluation of previously existing methods, data correlation efforts, and the development of the selected methods are presented and discussed. A summary of the methods is also presented to document the equations, computational charts and design guides which have been programmed for digital computer solution. Comparisons of predictions and test data are presented which show that the new methods provide a significant improvement in capability for evaluating the landing characteristics of advanced aerospace vehicles during the preliminary design phase of the configuration development cycle.

  6. Analysis of CASP8 targets, predictions and assessment methods

    PubMed Central

    Shi, ShuoYong; Pei, Jimin; Sadreyev, Ruslan I.; Kinch, Lisa N.; Majumdar, Indraneel; Tong, Jing; Cheng, Hua; Kim, Bong-Hyun; Grishin, Nick V.

    2009-01-01

    Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets. Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8. PMID:20157476

  7. Analysis of CASP8 targets, predictions and assessment methods.

    PubMed

    Shi, Shuoyong; Pei, Jimin; Sadreyev, Ruslan I; Kinch, Lisa N; Majumdar, Indraneel; Tong, Jing; Cheng, Hua; Kim, Bong-Hyun; Grishin, Nick V

    2009-01-01

    Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets.Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8. PMID:20157476

  8. Development of Improved Surface Integral Methods for Jet Aeroacoustic Predictions

    NASA Technical Reports Server (NTRS)

    Pilon, Anthony R.; Lyrintzis, Anastasios S.

    1997-01-01

    The accurate prediction of aerodynamically generated noise has become an important goal over the past decade. Aeroacoustics must now be an integral part of the aircraft design process. The direct calculation of aerodynamically generated noise with CFD-like algorithms is plausible. However, large computer time and memory requirements often make these predictions impractical. It is therefore necessary to separate the aeroacoustics problem into two parts, one in which aerodynamic sound sources are determined, and another in which the propagating sound is calculated. This idea is applied in acoustic analogy methods. However, in the acoustic analogy, the determination of far-field sound requires the solution of a volume integral. This volume integration again leads to impractical computer requirements. An alternative to the volume integrations can be found in the Kirchhoff method. In this method, Green's theorem for the linear wave equation is used to determine sound propagation based on quantities on a surface surrounding the source region. The change from volume to surface integrals represents a tremendous savings in the computer resources required for an accurate prediction. This work is concerned with the development of enhancements of the Kirchhoff method for use in a wide variety of aeroacoustics problems. This enhanced method, the modified Kirchhoff method, is shown to be a Green's function solution of Lighthill's equation. It is also shown rigorously to be identical to the methods of Ffowcs Williams and Hawkings. This allows for development of versatile computer codes which can easily alternate between the different Kirchhoff and Ffowcs Williams-Hawkings formulations, using the most appropriate method for the problem at hand. The modified Kirchhoff method is developed primarily for use in jet aeroacoustics predictions. Applications of the method are shown for two dimensional and three dimensional jet flows. Additionally, the enhancements are generalized so that

  9. In silico methods for predicting T-cell epitopes: Dr Jekyll or Mr Hyde?

    PubMed

    Gowthaman, Uthaman; Agrewala, Javed N

    2009-10-01

    In silico tools offer an attractive alternative strategy to the cumbersome experimental approaches to identify T-cell epitopes. These computational tools have metamorphosed over the years into complex algorithms that attempt to efficiently predict the binding of a plethora of peptides to HLA alleles. In recent years, the scientific community has embraced these techniques to reduce the burden of wet-laboratory experimentation. Although there are some splendid examples of the utility of these methods, there are also evidences where they fall short and remain inconsistent. Hence, are these computational tools 'Dr Jekyll' or 'Mr Hyde' to the researcher, who wishes to utilize them intrepidly? This article reviews the progress and pitfalls of the in silico tools that identify T-cell epitopes. PMID:19811074

  10. Increased Fidelity in Prediction Methods For Landing Gear Noise

    NASA Technical Reports Server (NTRS)

    Lopes, Leonard V.; Brentner, Kenneth S.; Morris, Philip J.; Lockhard, David P.

    2006-01-01

    An aeroacoustic prediction scheme has been developed for landing gear noise. The method is designed to handle the complex landing gear geometry of current and future aircraft. The gear is represented by a collection of subassemblies and simple components that are modeled using acoustic elements. These acoustic elements are generic, but generate noise representative of the physical components on a landing gear. The method sums the noise radiation from each component of the undercarriage in isolation accounting for interference with adjacent components through an estimate of the local upstream and downstream flows and turbulence intensities. The acoustic calculations are made in the code LGMAP, which computes the sound pressure levels at various observer locations. The method can calculate the noise from the undercarriage in isolation or installed on an aircraft for both main and nose landing gear. Comparisons with wind tunnel and flight data are used to initially calibrate the method, then it may be used to predict the noise of any landing gear. In this paper, noise predictions are compared with wind tunnel data for model landing gears of various scales and levels of fidelity, as well as with flight data on fullscale undercarriages. The present agreement between the calculations and measurements suggests the method has promise for future application in the prediction of airframe noise.

  11. Relationship between N-terminal pro-B-type natriuretic peptide and renal function: the effects on predicting early outcome after off-pump coronary artery bypass surgery

    PubMed Central

    Jo, Youn Yi; Kwak, Young Lan; Lee, Jonghoon

    2011-01-01

    Background Plasma levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP) provide useful prognostic predictors in patients after cardiac surgery. However, predictive accuracy of NT-proBNP levels has varied significantly according to renal dysfunction. The purpose of this study was to assess whether preoperative NT-proBNP levels could be used as predictors of early postoperative outcomes on the basis of renal function in patients undergoing off-pump coronary artery bypass surgery (OPCAB). Methods In 219 patients undergoing elective OPCAB, NT-proBNP and an estimated glomerular filtration rate (eGFR) were assessed preoperatively. All patients were divided into 3 groups according to tertiles of eGFR: the first (eGFR ≥ 90 ml/min/1.73 m2), the second (90 ml/min/1.73 m2 > eGFR ≥ 72 ml/min/1.73 m2) and the third tertile group (eGFR < 72 ml/min/1.73 m2). End point was the composite of early postoperative complications defined as myocardial infarction, new onset atrial fibrillation, ventricular dysfunction, prolonged mechanical ventilator care (> 48 hr), prolonged ICU stay (≥ 3 days), and in hospital mortality. Results There was no difference in early postoperative complications among groups. A preoperative NT-proBNP level of 228 pg/ml and 302 pg/ml (sensitivity 70%, specificity 67%, P < 0.001 and sensitivity 73%, specificity 63%, P = 0.001, respectively) were optimal cut-off values predicting complicated early postoperative course in second and third tertile group, respectively. Conclusions Preoperative NT-proBNP levels seem to be predictive of early postoperative complications in patients with eGFR < 90 ml/min/1.73 m2 undergoing OPCAB. PMID:21860749

  12. High accuracy operon prediction method based on STRING database scores.

    PubMed

    Taboada, Blanca; Verde, Cristina; Merino, Enrique

    2010-07-01

    We present a simple and highly accurate computational method for operon prediction, based on intergenic distances and functional relationships between the protein products of contiguous genes, as defined by STRING database (Jensen,L.J., Kuhn,M., Stark,M., Chaffron,S., Creevey,C., Muller,J., Doerks,T., Julien,P., Roth,A., Simonovic,M. et al. (2009) STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412-D416). These two parameters were used to train a neural network on a subset of experimentally characterized Escherichia coli and Bacillus subtilis operons. Our predictive model was successfully tested on the set of experimentally defined operons in E. coli and B. subtilis, with accuracies of 94.6 and 93.3%, respectively. As far as we know, these are the highest accuracies ever obtained for predicting bacterial operons. Furthermore, in order to evaluate the predictable accuracy of our model when using an organism's data set for the training procedure, and a different organism's data set for testing, we repeated the E. coli operon prediction analysis using a neural network trained with B. subtilis data, and a B. subtilis analysis using a neural network trained with E. coli data. Even for these cases, the accuracies reached with our method were outstandingly high, 91.5 and 93%, respectively. These results show the potential use of our method for accurately predicting the operons of any other organism. Our operon predictions for fully-sequenced genomes are available at http://operons.ibt.unam.mx/OperonPredictor/. PMID:20385580

  13. Comparison of molecular dynamics simulation methods for amyloid β(1-42) monomers containing D-aspartic acid residues for predicting retention times in chromatography.

    PubMed

    Oda, Akifumi; Kobayashi, Kana; Takahashi, Ohgi

    2011-11-01

    Molecular dynamics simulations of amyloid β(1-42) containing D-aspartic acid residues were performed using several continuous solvent models to investigate the usefulness of simulation methods for D-amino acid-containing proteins and peptides. Normal molecular dynamics simulations and replica exchange molecular dynamics simulations, which are one of the generalized-ensemble algorithms, were performed. Because the β-structure contents of amyloid β(1-42) peptides obtained by replica exchange molecular dynamics simulations with Onufriev-Bashford-Case generalized Born implicit solvent were qualitatively consistent with experimental data, replica exchange molecular dynamics rather than other methods appeared to be more reasonable for calculations of amyloid β(1-42) containing D-aspartic acid residues. Computational results revealed that peptides with stereoinversion of Asp23 tend to form β-sheet structures by themselves, in contrast to the wild-type peptides that form β-sheet structures only after aggregation. These results are expected to be useful for computational investigations of proteins and peptides such as prediction of retention time of peptides and proteins containing D-aspartic acid residues.

  14. A Method of Recording and Predicting the Pollen Count.

    ERIC Educational Resources Information Center

    Buck, M.

    1985-01-01

    A hair dryer, plastic funnel, and microscope slide can be used for predicting pollen counts on a day-to-day basis. Materials, methods for assembly, collection technique, meteorological influences, and daily patterns are discussed. Data collected using the apparatus suggest that airborne grass products other than pollen also affect hay fever…

  15. Composition and method for self-assembly and mineralization of peptide amphiphiles

    DOEpatents

    Stupp, Samuel I.; Beniash, Elia; Hartgerink, Jeffrey D.

    2009-06-30

    The present invention is directed to a composition useful for making homogeneously mineralized self assembled peptide-amphiphile nanofibers and nanofiber gels. The composition is generally a solution comprised of a positively or negatively charged peptide-amphiphile and a like signed ion from the mineral. Mixing this solution with a second solution containing a dissolved counter-ion of the mineral and/or a second oppositely charged peptide amphiphile, results in the rapid self assembly of the peptide-amphiphiles into a nanofiber gel and templated mineralization of the ions. Templated mineralization of the initially dissolved mineral cations and anions in the mixture occurs with preferential orientation of the mineral crystals along the fiber surfaces within the nanofiber gel. One advantage of the present invention is that it results in homogenous growth of the mineral throughout the nanofiber gel. Another advantage of the present invention is that the nanofiber gel formation and mineralization reactions occur in a single mixing step and under substantially neutral or physiological pH conditions. These homogeneous nanostructured composite materials are useful for medical applications especially the regeneration of damaged bone in mammals. This invention is directed to the synthesis of peptide-amphiphiles with more than one amphiphilic moment and to supramolecular compositions comprised of such multi-dimensional peptide-amphiphiles. Supramolecular compositions can be formed by self assembly of multi-dimensional peptide-amphiphiles by mixing them with a solution comprising a monovalent cation.

  16. Composition and method for self-assembly and mineralization of peptide-amphiphiles

    DOEpatents

    Stupp, Samuel I.; Beniash, Elia; Hartgerink, Jeffrey D.

    2012-02-28

    The present invention is directed to a composition useful for making homogeneously mineralized self assembled peptide-amphiphile nanofibers and nanofiber gels. The composition is generally a solution comprised of a positively or negatively charged peptide-amphiphile and a like signed ion from the mineral. Mixing this solution with a second solution containing a dissolved counter-ion of the mineral and/or a second oppositely charged peptide amphiphile, results in the rapid self assembly of the peptide-amphiphiles into a nanofiber gel and templated mineralization of the ions. Templated mineralization of the initially dissolved mineral cations and anions in the mixture occurs with preferential orientation of the mineral crystals along the fiber surfaces within the nanofiber gel. One advantage of the present invention is that it results in homogenous growth of the mineral throughout the nanofiber gel. Another advantage of the present invention is that the nanofiber gel formation and mineralization reactions occur in a single mixing step and under substantially neutral or physiological pH conditions. These homogeneous nanostructured composite materials are useful for medical applications especially the regeneration of damaged bone in mammals. This invention is directed to the synthesis of peptide-amphiphiles with more than one amphiphilic moment and to supramolecular compositions comprised of such multi-dimensional peptide-amphiphiles. Supramolecular compositions can be formed by self assembly of multi-dimensional peptide-amphiphiles by mixing them with a solution comprising a monovalent cation.

  17. Risk prediction with machine learning and regression methods.

    PubMed

    Steyerberg, Ewout W; van der Ploeg, Tjeerd; Van Calster, Ben

    2014-07-01

    This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.

  18. Hybrid robust predictive optimization method of power system dispatch

    DOEpatents

    Chandra, Ramu Sharat; Liu, Yan; Bose, Sumit; de Bedout, Juan Manuel

    2011-08-02

    A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

  19. Role of galectin-3 and plasma B type-natriuretic peptide in predicting prognosis in discharged chronic heart failure patients

    PubMed Central

    Feola, Mauro; Testa, Marzia; Leto, Laura; Cardone, Marco; Sola, Mario; Rosso, Gian Luca

    2016-01-01

    Abstract Galectin-3 demonstrated to be a robust independent marker of cardiovascular mid-term (18-month) outcome in heart failure (HF) patients. The objective of this study was to analyze the value of a predischarged determination of plasma galectin-3 alone and with plasma brain natriuretic peptide (BNP) in predicting mid-term outcome in frequent-flyers (FF) HF (≥2 hospitalization for HF/year)/dead patients discharged after an acute decompensated HF (ADHF) episode. All FF chronic HF subjects discharged alive after an ADHF were enrolled. All patients underwent a determination of BNP and galectin-3, a 6-minute walk test, and an echocardiogram within 48 hours upon hospital discharge. Death by any cause, cardiac transplantation, and worsening HF requiring readmission to hospital were considered cardiovascular events. Eighty-three patients (67 males, age 73.2 ± 8.6 years old) were analyzed (mean follow-up 11.6 ± 5.2 months; range 4–22 months). During the follow-up 38 events (45.7%) were scheduled: (13 cardiac deaths, 35 rehospitalizations for ADHF). According to medical history, in 33 patients (39.8%) a definition of FF HF patients was performed (range 2–4 hospitalization/year). HF patients who suffered an event (FF or death) demonstrated more impaired ventricular function (P = 0.037), higher plasma BNP (P = 0.005), and Gal-3 at predischarge evaluation (P = 0.027). Choosing adequate cut-off points (BNP ≥ 500 pg/mL and Gal-3 ≥ 17.6 ng/mL), the Kaplan–Meier curves depicted the powerful stratification using BNP + Gal-3 in predicting clinical course at mid-term follow-up (log rank 5.65; P = 0.017). Adding Gal-3 to BNP, a single predischarge strategy testing seemed to obtain a satisfactorily predictive value in alive HF patients discharged after an ADHF episode. PMID:27368017

  20. Evolutionary computational methods to predict oral bioavailability QSPRs.

    PubMed

    Bains, William; Gilbert, Richard; Sviridenko, Lilya; Gascon, Jose-Miguel; Scoffin, Robert; Birchall, Kris; Harvey, Inman; Caldwell, John

    2002-01-01

    This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico. PMID:11865672

  1. Evolutionary computational methods to predict oral bioavailability QSPRs.

    PubMed

    Bains, William; Gilbert, Richard; Sviridenko, Lilya; Gascon, Jose-Miguel; Scoffin, Robert; Birchall, Kris; Harvey, Inman; Caldwell, John

    2002-01-01

    This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico.

  2. Toward the Prediction of FBPase Inhibitory Activity Using Chemoinformatic Methods

    PubMed Central

    Hao, Ming; Zhang, Shuwei; Qiu, Jieshan

    2012-01-01

    Currently, Chemoinformatic methods are used to perform the prediction for FBPase inhibitory activity. A genetic algorithm-random forest coupled method (GA-RF) was proposed to predict fructose 1,6-bisphosphatase (FBPase) inhibitors to treat type 2 diabetes mellitus using the Mold2 molecular descriptors. A data set of 126 oxazole and thiazole analogs was used to derive the GA-RF model, yielding the significant non-cross-validated correlation coefficient r2ncv and cross-validated r2cv values of 0.96 and 0.67 for the training set, respectively. The statistically significant model was validated by a test set of 64 compounds, producing the prediction correlation coefficient r2pred of 0.90. More importantly, the building GA-RF model also passed through various criteria suggested by Tropsha and Roy with r2o and r2m values of 0.90 and 0.83, respectively. In order to compare with the GA-RF model, a pure RF model developed based on the full descriptors was performed as well for the same data set. The resulting GA-RF model with significantly internal and external prediction capacities is beneficial to the prediction of potential oxazole and thiazole series of FBPase inhibitors prior to chemical synthesis in drug discovery programs. PMID:22837677

  3. A free wake method for performance prediction of VAWT

    NASA Astrophysics Data System (ADS)

    Ilin, S.; Dumitrescu, H.; Cardos, V.; Dumitrache, A.

    2012-09-01

    Based on the lifting line theory and a free vortex wake model, a method including dynamic stall effects is presented for predicting the performance of a three-dimensional vertical-axis wind turbine (VAWT). A vortex model is used in which the wake is composed of trailing streamwise and shedding spanwise vortices, whose strengths are equal to the change in the bound vortex strength as dictated by Helmholtz and Kelvin's theorems. Performance parameters are calculated by application of the Biot-Savart law along with the Kutta-Joukowski theorem and a semi-empirical dynamic stall model. Predictions are shown to compare favorably with existing experimental data.

  4. A Rapid and Simple LC-MS Method Using Collagen Marker Peptides for Identification of the Animal Source of Leather.

    PubMed

    Kumazawa, Yuki; Taga, Yuki; Iwai, Kenji; Koyama, Yoh-Ichi

    2016-08-01

    Identification of the animal source of leather is difficult using traditional methods, including microscopic observation and PCR. In the present study, a LC-MS method was developed for detecting interspecies differences in the amino acid sequence of type I collagen, which is a major component of leather, among six animals (cattle, horse, pig, sheep, goat, and deer). After a dechroming procedure and trypsin digestion, six tryptic peptides of type I collagen were monitored by LC-MS in multiple reaction monitoring mode for the animal source identification using the patterns of the presence or absence of the marker peptides. We analyzed commercial leathers from various production areas using this method, and found some leathers in which the commercial label disagreed with the identified animal source. Our method enabled rapid and simple leather certification and could be applied to other animals whether or not their collagen sequences are available in public databases.

  5. A Rapid and Simple LC-MS Method Using Collagen Marker Peptides for Identification of the Animal Source of Leather.

    PubMed

    Kumazawa, Yuki; Taga, Yuki; Iwai, Kenji; Koyama, Yoh-Ichi

    2016-08-01

    Identification of the animal source of leather is difficult using traditional methods, including microscopic observation and PCR. In the present study, a LC-MS method was developed for detecting interspecies differences in the amino acid sequence of type I collagen, which is a major component of leather, among six animals (cattle, horse, pig, sheep, goat, and deer). After a dechroming procedure and trypsin digestion, six tryptic peptides of type I collagen were monitored by LC-MS in multiple reaction monitoring mode for the animal source identification using the patterns of the presence or absence of the marker peptides. We analyzed commercial leathers from various production areas using this method, and found some leathers in which the commercial label disagreed with the identified animal source. Our method enabled rapid and simple leather certification and could be applied to other animals whether or not their collagen sequences are available in public databases. PMID:27397145

  6. Application of linear gauss pseudospectral method in model predictive control

    NASA Astrophysics Data System (ADS)

    Yang, Liang; Zhou, Hao; Chen, Wanchun

    2014-03-01

    This paper presents a model predictive control(MPC) method aimed at solving the nonlinear optimal control problem with hard terminal constraints and quadratic performance index. The method combines the philosophies of the nonlinear approximation model predictive control, linear quadrature optimal control and Gauss Pseudospectral method. The current control is obtained by successively solving linear algebraic equations transferred from the original problem via linearization and the Gauss Pseudospectral method. It is not only of high computational efficiency since it does not need to solve nonlinear programming problem, but also of high accuracy though there are a few discrete points. Therefore, this method is suitable for on-board applications. A design of terminal impact with a specified direction is carried out to evaluate the performance of this method. Augmented PN guidance law in the three-dimensional coordinate system is applied to produce the initial guess. And various cases for target with straight-line movements are employed to demonstrate the applicability in different impact angles. Moreover, performance of the proposed method is also assessed by comparison with other guidance laws. Simulation results indicate that this method is not only of high computational efficiency and accuracy, but also applicable in the framework of guidance design.

  7. Paroxysmal atrial fibrillation prediction method with shorter HRV sequences.

    PubMed

    Boon, K H; Khalil-Hani, M; Malarvili, M B; Sia, C W

    2016-10-01

    This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF), using heart rate variability (HRV) segments that are shorter than those applied in existing methods, while maintaining good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to stabilize (electrically) and prevent the onset of atrial arrhythmias with different pacing techniques. We investigate the effect of HRV features extracted from different lengths of HRV segments prior to PAF onset with the proposed PAF prediction method. The pre-processing stage of the predictor includes QRS detection, HRV quantification and ectopic beat correction. Time-domain, frequency-domain, non-linear and bispectrum features are then extracted from the quantified HRV. In the feature selection, the HRV feature set and classifier parameters are optimized simultaneously using an optimization procedure based on genetic algorithm (GA). Both full feature set and statistically significant feature subset are optimized by GA respectively. For the statistically significant feature subset, Mann-Whitney U test is used to filter non-statistical significance features that cannot pass the statistical test at 20% significant level. The final stage of our predictor is the classifier that is based on support vector machine (SVM). A 10-fold cross-validation is applied in performance evaluation, and the proposed method achieves 79.3% prediction accuracy using 15-minutes HRV segment. This accuracy is comparable to that achieved by existing methods that use 30-minutes HRV segments, most of which achieves accuracy of around 80%. More importantly, our method significantly outperforms those that applied segments shorter than 30 minutes. PMID:27480743

  8. The critical role of peptide chemistry in the life sciences.

    PubMed

    Kent, Stephen B H

    2015-03-01

    Peptide chemistry plays a key role in the synthesis and study of protein molecules and their functions. Modern ligation methods enable the total synthesis of enzymes and the systematic dissection of the chemical basis of enzyme catalysis. Predicted developments in peptide science are described.

  9. How well does B-type natriuretic peptide predict death and cardiac events in patients with heart failure: systematic review

    PubMed Central

    Doust, Jenny A; Pietrzak, Eva; Dobson, Annette; Glasziou, Paul

    2005-01-01

    Objective To assess how well B-type natriuretic peptide (BNP) predicts prognosis in patients with heart failure. Design Systematic review of studies assessing BNP for prognosis in patients with heart failure or asymptomatic patients. Data sources Electronic searches of Medline and Embase from January 1994 to March 2004 and reference lists of included studies. Study selection and data extraction We included all studies that estimated the relation between BNP measurement and the risk of death, cardiac death, sudden death, or cardiovascular event in patients with heart failure or asymptomatic patients, including initial values and changes in values in response to treatment. Multivariable models that included both BNP and left ventricular ejection fraction as predictors were used to compare the prognostic value of each variable. Two reviewers independently selected studies and extracted data. Data synthesis 19 studies used BNP to estimate the relative risk of death or cardiovascular events in heart failure patients and five studies in asymptomatic patients. In heart failure patients, each 100 pg/ml increase was associated with a 35% increase in the relative risk of death. BNP was used in 35 multivariable models of prognosis. In nine of the models, it was the only variable to reach significance—that is, other variables contained no prognostic information beyond that of BNP. Even allowing for the scale of the variables, it seems to be a strong indicator of risk. Conclusion Although systematic reviews of prognostic studies have inherent difficulties, including the possibility of publication bias, the results of the studies in this review show that BNP is a strong prognostic indicator for both asymptomatic patients and for patients with heart failure at all stages of disease. PMID:15774989

  10. Evaluation of ride quality prediction methods for operational military helicopters

    NASA Technical Reports Server (NTRS)

    Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

    1984-01-01

    The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots' discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

  11. Benchmarking B cell epitope prediction: underperformance of existing methods.

    PubMed

    Blythe, Martin J; Flower, Darren R

    2005-01-01

    Sequence profiling is used routinely to predict the location of B-cell epitopes. In the postgenomic era, the need for reliable epitope prediction is clear. We assessed 484 amino acid propensity scales in combination with ranges of plotting parameters to examine exhaustively the correlation of peaks and epitope location within 50 proteins mapped for polyclonal responses. After examining more than 10(6) combinations, we found that even the best set of scales and parameters performed only marginally better than random. Our results confirm the null hypothesis: Single-scale amino acid propensity profiles cannot be used to predict epitope location reliably. The implication for studies using such methods is obvious. PMID:15576553

  12. Comparison of Predictive Modeling Methods of Aircraft Landing Speed

    NASA Technical Reports Server (NTRS)

    Diallo, Ousmane H.

    2012-01-01

    Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

  13. Pedophilia: an evaluation of diagnostic and risk prediction methods.

    PubMed

    Wilson, Robin J; Abracen, Jeffrey; Looman, Jan; Picheca, Janice E; Ferguson, Meaghan

    2011-06-01

    One hundred thirty child sexual abusers were diagnosed using each of following four methods: (a) phallometric testing, (b) strict application of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision [DSM-IV-TR]) criteria, (c) Rapid Risk Assessment of Sex Offender Recidivism (RRASOR) scores, and (d) "expert" diagnoses rendered by a seasoned clinician. Comparative utility and intermethod consistency of these methods are reported, along with recidivism data indicating predictive validity for risk management. Results suggest that inconsistency exists in diagnosing pedophilia, leading to diminished accuracy in risk assessment. Although the RRASOR and DSM-IV-TR methods were significantly correlated with expert ratings, RRASOR and DSM-IV-TR were unrelated to each other. Deviant arousal was not associated with any of the other methods. Only the expert ratings and RRASOR scores were predictive of sexual recidivism. Logistic regression analyses showed that expert diagnosis did not add to prediction of sexual offence recidivism over and above RRASOR alone. Findings are discussed within a context of encouragement of clinical consistency and evidence-based practice regarding treatment and risk management of those who sexually abuse children.

  14. A computational method to predict carbonylation sites in yeast proteins.

    PubMed

    Lv, H Q; Liu, J; Han, J Q; Zheng, J G; Liu, R L

    2016-01-01

    Several post-translational modifications (PTM) have been discussed in literature. Among a variety of oxidative stress-induced PTM, protein carbonylation is considered a biomarker of oxidative stress. Only certain proteins can be carbonylated because only four amino acid residues, namely lysine (K), arginine (R), threonine (T) and proline (P), are susceptible to carbonylation. The yeast proteome is an excellent model to explore oxidative stress, especially protein carbonylation. Current experimental approaches in identifying carbonylation sites are expensive, time-consuming and limited in their abilities to process proteins. Furthermore, there is no bioinformational method to predict carbonylation sites in yeast proteins. Therefore, we propose a computational method to predict yeast carbonylation sites. This method has total accuracies of 86.32, 85.89, 84.80, and 86.80% in predicting the carbonylation sites of K, R, T, and P, respectively. These results were confirmed by 10-fold cross-validation. The ability to identify carbonylation sites in different kinds of features was analyzed and the position-specific composition of the modification site-flanking residues was discussed. Additionally, a software tool has been developed to help with the calculations in this method. Datasets and the software are available at https://sourceforge.net/projects/hqlstudio/ files/CarSpred.Y/. PMID:27420944

  15. Improved load ratio method for predicting crack length

    SciTech Connect

    Chen, X.; Albrecht, P.; Wright, W.; Joyce, J.A.

    1995-04-01

    The elastic compliance from unloading/reloading sequences in a load-displacement record estimates well crack length in elastic-plastic fracture toughness tests of compact tension [C(T)] and bending type specimens. The need for partial unloading of the specimen makes it difficult to run the test under static loading and impossible under either dynamic loading or very high temperatures. Furthermore, fracture toughness testing in which crack length is determined from elastic compliance requires high precision testing equipment and highly skilled technicians. As a result, such tests are confined usually to research laboratories and seldom used under production settings. To eliminate these problems, an improved load ratio method of predicting crack length is proposed that utilizes only the recorded load versus load-line displacement curve (or load versus crack-mouth-opening displacement curve) without unloading/reloading sequences. As a result, the instrumentation is much simpler than in the elastic compliance or potential drop methods. If only a monotonic load-displacement record is to be measured the fracture toughness test becomes almost as simple to perform as a tension test. The method described here improves in three ways the ``original load ratio method`` proposed by Hu et al. First, a blunting term is added to the crack length before maximum load. Second, a strain hardening correction is included after maximum load. And, third, the initial crack length and the physical (final) crack length measured at the end of the test serve to anchor the predicted crack lengths, forcing agreement between predicted and measured values. The method predicts crack extension with excellent accuracy in specimens fabricated from A302, A508, and A533B piping and pressure vessel steels, A588 and A572 structural steels, and HY-80 ship steel.

  16. Prediction by neural network methods compared for energy control problems

    SciTech Connect

    Surkan, A.J.; Skurikhin, A.N.

    1996-10-01

    Daily recordings of energy consumption are sequenced to construct a time series that is used to test the accuracy of a variety of neural networks in making one- and two-day demand predictions. Five neural network methods were applied to the same data for a problem of predicting daily energy usage. These included four which were gradient-based, namely, back propagation (BACKPROP), quick-propagation (QUICKPROP), cascade correlation (CASCOR), memory neuron network (MNN), and a correlation-based method called ALOPEX. The observed time series is the only information source used for making predictions. Other supplementary parallel series of independent data can produce improvements. It was demonstrated that these neural network learning algorithms can train networks to predict consistently, one-day-ahead, over one year of set-aside test patterns and reduce the average error to below 19%. Reported is a comparison of applicability of neural networks by programmed simulations of the widely used gradient-based algorithms along with newer algorithms MNN and ALOPEX. The diverse capabilities of these various networks give insights which are a useful basis for selecting further studies.

  17. Predict octane numbers using a generalized interaction method

    SciTech Connect

    Twu, C.H.; Coon, J.E.

    1996-02-01

    An interaction-based correlation using a new approach can be used to predict research and motor octane numbers of gasoline blends. An ultimately detailed analysis of the gasoline cut is not necessary. This correlation can describe blending behavior over the entire composition range of gasoline cuts. The component-oriented interaction approach is general and will accurately predict, without performing additional blending studies, blending behavior for new gasoline cuts. The proposed correlation fits the data quite closely for blends of many gasoline cuts. The regression gives realistic values for binary interaction parameters between components. A unique set of binary interaction parameters was found for the equation for predicting octane number of any gasoline blend. The binary interaction parameters between components contained in gasoline cuts have been converted to binary interaction parameters between gasoline cuts through a general equation to simplify the calculations. Because of the proposed method`s accuracy, optimum allocation of components among gasoline grades can be obtained and predicted values can be used for quality control of the octane number of marketed gasolines.

  18. Application of hydrophilic interaction chromatography retention coefficients for predicting peptide elution with TFA and methanesulfonic acid ion-pairing reagents.

    PubMed

    Wujcik, Chad E; Tweed, Joseph; Kadar, Eugene P

    2010-03-01

    Hydrophilic retention coefficients for 17 peptides were calculated based on retention coefficients previously published for TSKgel silica-60 and were compared with the experimental elution profile on a Waters Atlantis HILIC silica column using TFA and methanesulfonic acid (MSA) as ion-pairing reagents. Relative peptide retention could be accurately determined with both counter-ions. Peptide retention and chromatographic behavior were influenced by the percent acid modifier used with increases in both retention and peak symmetry observed at increasing modifier concentrations. The enhancement of net peptide polarity through MSA pairing shifted retention out by nearly five-fold for the earliest eluting peptide, compared with TFA. Despite improvements in retention and efficiency (N(eff)) for MSA over TFA, a consistent reduction in calculated selectivity (alpha) was observed. This result is believed to be attributed to the stronger polar contribution of MSA masking and diminishing the underlying influence of the amino acid residues of each associated peptide. Finally, post-column infusion of propionic acid and acetic acid was evaluated for their potential to recover signal intensity for TFA and MSA counter-ions for LC-ESI-MS applications. Acetic acid generally yielded more substantial signal improvements over propionic acid on the TFA system while minimal benefits and some further reductions were noted with MSA.

  19. Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods

    SciTech Connect

    Shen, Yufeng; Tolić, Nikola; Xie, Fang; Zhao, Rui; Purvine, Samuel O.; Schepmoes, Athena A.; Moore, Ronald, J.; Anderson, Gordon A.; Smith, Richard D.

    2011-09-02

    We report on use of an Orbitrap Velos mass spectrometer for comparison of fragmentation methods namely CID-, HCD-, and ETD for FT MS/MS analysis of human blood plasma peptidomic peptides. The peptidomic peptides were able to be identified from CID, HCD, and ETD spectra on specific confidence levels (e.g., 1% false discovery rate) with use of conventional SEQUEST database search software, and the number of identified peptides was increased by ~50% using accurate fragments (e.g., with mass tolerance of 0.05Da) in comparison with traditional moderate accuracy fragments (e.g., with 1 Da mass tolerance) for database search. However, the peptide datasets identified with such decoy search strategy were found to be varied by ~25% in the dataset size and ~20% in the dataset content with type of decoy database and precursor mass tolerances used for database search. CID was evaluated as the largest contributor to the identified peptide datasets, and HCD, and ETD provided ~20% and ~22% respectively additional peptides with accurate fragments for peptide identification, in contrast to ~25% and ~13% respectively with use of moderate accuracy fragments. When long (typically ≥7 amino acids) sequences were used for identification of peptides from the previously published UStags and de novo sequencing methods, HCD was evaluated as the largest contributor, and CID and ETD provided ~26% and ~8% respectively additional peptides from the UStags method and ~26% and ~6% respectively additional peptides from the de novo sequencing method. The peptide datasets identified with the UStags method were little influenced by the decoy database and mass tolerance and 98-99% peptide overlaps could be achieved between these datasets. CID, HCD, and ETD contributed their identifications of various charge state peptides in the m/z range highly overlapped and complementary implementation of CID, HCD, and ETD should be applied to maximize the number of peptides identified. Finally, the investigation

  20. Fast prediction unit selection method for HEVC intra prediction based on salient regions

    NASA Astrophysics Data System (ADS)

    Feng, Lei; Dai, Ming; Zhao, Chun-lei; Xiong, Jing-ying

    2016-07-01

    In order to reduce the computational complexity of the high efficiency video coding (HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit (PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit (LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate ( BDBR) of 0.62%.

  1. Method to predict external store carriage characteristics at transonic speeds

    NASA Technical Reports Server (NTRS)

    Rosen, Bruce S.

    1988-01-01

    Development of a computational method for prediction of external store carriage characteristics at transonic speeds is described. The geometric flexibility required for treatment of pylon-mounted stores is achieved by computing finite difference solutions on a five-level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body-conforming grid improves the accuracy of the computed store body flow field. A nonlinear relaxation scheme developed specifically for modified transonic small disturbance flow equations enhances the method's numerical stability and accuracy. As a result, treatment of lower aspect ratio, more highly swept and tapered wings is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, and force/moment correlations show good agreement with experimental data for several test cases. A detailed computer program description for the Transonic Store Carriage Loads Prediction (TSCLP) Code is included.

  2. Coastal cliff recession: the use of probabilistic prediction methods

    NASA Astrophysics Data System (ADS)

    Lee, E. M.; Hall, J. W.; Meadowcroft, I. C.

    2001-10-01

    A range of probabilistic methods is introduced for predicting coastal cliff recession, which provide a means of demonstrating the potential variability in such predictions. They form the basis for risk-based land-use planning, cliff management and engineering decision-making. Examples of probabilistic models are presented for a number of different cliff settings: the simulation of recession on eroding cliffs; the use of historical records and statistical experiments to model the behaviour of cliffs affected by rare, episodic landslide events; the adaptation of an event tree approach to assess the probability of failure of protected cliffs, taking into account the residual life of the existing defences; and the evaluation of the probability of landslide reactivation in areas of pre-existing landslide systems. These methods are based on a geomorphological assessment of the episodic nature of the recession process, together with historical records.

  3. Usefulness of N-terminal pro-brain natriuretic peptide and C-reactive protein to predict ICU mortality in unselected medical ICU patients: a prospective, observational study

    PubMed Central

    2011-01-01

    Introduction The performance of N-terminal pro-brain natriuretic peptide (NT-proBNP) and C-reactive protein (CRP) to predict clinical outcomes in ICU patients is unimpressive. We aimed to assess the prognostic value of NT-proBNP, CRP or the combination of both in unselected medical ICU patients. Methods A total of 576 consecutive patients were screened for eligibility and followed up during the ICU stay. We collected each patient's baseline characteristics including the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score, NT-proBNP and CRP levels. The primary outcome was ICU mortality. Potential predictors were analyzed for possible association with outcomes. We also evaluated the ability of NT-proBNP and CRP additive to APACHE-II score to predict ICU mortality by calculation of C-index, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. Results Multiple regression revealed that CRP, NT-proBNP, APACHE-II score and fasting plasma glucose independently predicted ICU mortality (all P < 0.01). The C-index with respect to prediction of ICU mortality of APACHE II score (0.82 ± 0.02; P < 0.01) was greater than that of NT-proBNP (0.71 ± 0.03; P < 0.01) or CRP (0.65 ± 0.03; P < 0.01) (all P < 0.01). As compared with APACHE-II score (0.82 ± 0.02; P < 0.01), combination of CRP (0.83 ± 0.02; P < 0.01) or NT-proBNP (0.83 ± 0.02; P < 0.01) or both (0.84 ± 0.02; P < 0.01) with APACHE-II score did not significantly increase C-index for predicting ICU mortality (all P > 0.05). However, addition of NT-proBNP to APACHE-II score gave IDI of 6.6% (P = 0.003) and NRI of 16.6% (P = 0.007), addition of CRP to APACHE-II score provided IDI of 5.6% (P = 0.026) and NRI of 12.1% (P = 0.023), and addition of both markers to APACHE-II score yielded IDI of 7.5% (P = 0.002) and NRI of 17.9% (P = 0.002). In the cardiac subgroup (N = 213), NT-proBNP but not CRP independently predicted ICU mortality and addition of NT-proBNP to

  4. Epileptic seizure prediction by non-linear methods

    DOEpatents

    Hively, L.M.; Clapp, N.E.; Day, C.S.; Lawkins, W.F.

    1999-01-12

    This research discloses methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming. 76 figs.

  5. Epileptic seizure prediction by non-linear methods

    DOEpatents

    Hively, Lee M.; Clapp, Ned E.; Daw, C. Stuart; Lawkins, William F.

    1999-01-01

    Methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming.

  6. CREME96 and Related Error Rate Prediction Methods

    NASA Technical Reports Server (NTRS)

    Adams, James H., Jr.

    2012-01-01

    Predicting the rate of occurrence of single event effects (SEEs) in space requires knowledge of the radiation environment and the response of electronic devices to that environment. Several analytical models have been developed over the past 36 years to predict SEE rates. The first error rate calculations were performed by Binder, Smith and Holman. Bradford and Pickel and Blandford, in their CRIER (Cosmic-Ray-Induced-Error-Rate) analysis code introduced the basic Rectangular ParallelePiped (RPP) method for error rate calculations. For the radiation environment at the part, both made use of the Cosmic Ray LET (Linear Energy Transfer) spectra calculated by Heinrich for various absorber Depths. A more detailed model for the space radiation environment within spacecraft was developed by Adams and co-workers. This model, together with a reformulation of the RPP method published by Pickel and Blandford, was used to create the CR ME (Cosmic Ray Effects on Micro-Electronics) code. About the same time Shapiro wrote the CRUP (Cosmic Ray Upset Program) based on the RPP method published by Bradford. It was the first code to specifically take into account charge collection from outside the depletion region due to deformation of the electric field caused by the incident cosmic ray. Other early rate prediction methods and codes include the Single Event Figure of Merit, NOVICE, the Space Radiation code and the effective flux method of Binder which is the basis of the SEFA (Scott Effective Flux Approximation) model. By the early 1990s it was becoming clear that CREME and the other early models needed Revision. This revision, CREME96, was completed and released as a WWW-based tool, one of the first of its kind. The revisions in CREME96 included improved environmental models and improved models for calculating single event effects. The need for a revision of CREME also stimulated the development of the CHIME (CRRES/SPACERAD Heavy Ion Model of the Environment) and MACREE (Modeling and

  7. A Fmoc-compatible Method for the Solid-Phase Synthesis of Peptide C-Terminal (alpha)-Thioesters based on the Safety-Catch Hydrazine Linker

    SciTech Connect

    Camarero, J A; Hackel, B J; de Yoreo, J J; Mitchell, A R

    2003-11-22

    C-terminal peptide thioesters are key intermediates for the synthesis/semisynthesis of proteins and for the production of cyclic peptides by native chemical ligation. They can be synthetically prepared by solid-phase peptide synthesis (SPPS) methods or biosynthetically by protein splicing techniques. Until recently, the chemical synthesis of C-terminal a-thioester peptides by SPPS was largely restricted to the Boc/Benzyl methodology because of the poor stability of the thioester bond to the basic conditions employed for the deprotection of the N{sup {alpha}}-Fmoc group. In the present work, we describe a new method for the SPPS of C-terminal thioesters by Fmoc/t-Bu chemistry. This method is based on the use of an aryl hydrazide linker, which is totally stable to the Fmoc-SPPS conditions. Once the peptide synthesis has been completed, activation of the linker can be achieved by mild oxidation. This step transforms the hydrazide group into a highly reactive diazene intermediate which can react with different H-AA-SEt to yield the corresponding {alpha}-thioester peptide in good yields. This method has been successfully used for the generation of different thioester peptides, circular peptides and a fully functional SH3 protein domain.

  8. Development of a capillary high performance liquid chromatography-ion trap-mass spectrometry method for the determination of VLIVP antihypertensive peptide in soybean crops.

    PubMed

    Puchalska, Patrycja; García, M Concepción; Marina, M Luisa

    2014-04-18

    Soybean peptide VLIVP presents a very high antihypertensive activity (IC50 value 1.69μM), even higher than extensively studied IPP and VPP peptides from milk. Nevertheless, no much attention has been paid to this peptide and there is no method enabling its determination in soybeans. The aim of this work was the development of an analytical methodology for this purpose. A methodology consisting of the extraction of soybean proteins, their digestion with Protease P enzyme, their chromatographic separation using capillary-HPLC, and IT-MS detection was optimized. Protein extraction was performed by the use of high intensity focused ultrasounds to obtain a reduced extraction time. Optimization of chromatographic and mass spectrometry parameters enabled the separation of VLIVP peptide within just 7min and its sensitive detection. The analytical characteristics of the capillary-HPLC-IT-MS method were evaluated through the study of linearity, LOD, LOQ, study of the presence of matrix interferences, precision, and recovery. The method enabled to detect as low as 3.6ng of peptide and to determine as low as 12ng of peptide in 1g of soybean (as dry basis). Finally, the developed method was applied to the determination of the antihypertensive peptide VLIVP in different soybean varieties. The results showed the highest yield of VLIVP peptide in variety Mazowiecka II from Poland. PMID:24630980

  9. Two Efficient Twin ELM Methods With Prediction Interval.

    PubMed

    Ning, Kefeng; Liu, Min; Dong, Mingyu; Wu, Cheng; Wu, ZhanSong

    2015-09-01

    In the operational optimization and scheduling problems of actual industrial processes, such as iron and steel, and microelectronics, the operational indices and process parameters usually need to be predicted. However, for some input and output variables of these prediction models, there may exist a lot of uncertainties coming from themselves, the measurement error, the rough representation, and so on. In such cases, constructing a prediction interval (PI) for the output of the corresponding prediction model is very necessary. In this paper, two twin extreme learning machine (TELM) models for constructing PIs are proposed. First, we propose a regularized asymmetric least squares extreme learning machine (RALS-ELM) method, in which different weights of its squared error loss function are set according to whether the error of the model output is positive or negative in order that the above error can be differentiated in the parameter learning process, and Tikhonov regularization is introduced to reduce overfitting. Then, we propose an asymmetric Bayesian extreme learning machine (AB-ELM) method based on the Bayesian framework with the asymmetric Gaussian distribution (AB-ELM), in which the weights of its likelihood function are determined as the same method in RALS-ELM, and the type II maximum likelihood algorithm is derived to learn the parameters of AB-ELM. Based on RALS-ELM and AB-ELM, we use a pair of weights following the reciprocal relationship to obtain two nonparallel regressors, including a lower-bound regressor and an upper-bound regressor, respectively, which can be used for calculating the PIs. Finally, some discussions are given, about how to adjust the weights adaptively to meet the desired PI, how to use the proposed TELMs for nonlinear quantile regression, and so on. Results of numerical comparison on data from one synthetic regression problem, three University of California Irvine benchmark regression problems, and two actual industrial regression

  10. Method of predicting mechanical properties of decayed wood

    DOEpatents

    Kelley, Stephen S.

    2003-07-15

    A method for determining the mechanical properties of decayed wood that has been exposed to wood decay microorganisms, comprising: a) illuminating a surface of decayed wood that has been exposed to wood decay microorganisms with wavelengths from visible and near infrared (VIS-NIR) spectra; b) analyzing the surface of the decayed wood using a spectrometric method, the method generating a first spectral data of wavelengths in VIS-NIR spectra region; and c) using a multivariate analysis to predict mechanical properties of decayed wood by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data of wavelengths in VIS-NIR spectra obtained from a reference decay wood, the second spectral data being correlated with a known mechanical property analytical result obtained from the reference decayed wood.

  11. Predictive Values of N-Terminal Pro-B-Type Natriuretic Peptide and Cardiac Troponin I for Myocardial Fibrosis in Hypertrophic Obstructive Cardiomyopathy

    PubMed Central

    Zhang, Changlin; Liu, Rong; Yuan, Jiansong; Cui, Jingang; Hu, Fenghuan; Yang, Weixian; Zhang, Yan; Chen, Youzhou; Qiao, Shubin

    2016-01-01

    Background Both high-sensitivity cardiac troponin T and B-type natriuretic peptide are useful in detecting myocardial fibrosis, as determined by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR), in patients with non-obstructive hypertrophic cardiomyopathy. However, their values to predict myocardial fibrosis in hypertrophic obstructive cardiomyopathy (HOCM) remain unclear. We investigated the role of N-Terminal Pro-B-Type Natriuretic Peptide (NT-proBNP) and cardiac troponin I (cTnI) to identify LGE-CMR in patients with HOCM. Methods Peripheral concentrations of NT-proBNP and cTnI were determined in patients with HOCM (n = 163; age = 47.2 ± 10.8 years; 38.7% females). Contrast-enhanced CMR was performed to identify and quantify myocardial fibrosis. Results LGE was detected in 120 of 163 patients (73.6%). Patients with LGE had significantly higher levels of NT-proBNP and cTnI than those without LGE (1386.2 [904.6–2340.8] vs. 866.6 [707.2–1875.2] pmol/L, P = 0.003; 0.024 [0.010–0.049] vs. 0.010 [0.005–0.021] ng/ml, P <0.001, respectively). The extent of LGE was positively correlated with log cTnI (r = 0.371, P <0.001) and log NT-proBNP (r = 0.211, P = 0.007). On multivariable analysis, both log cTnI and maximum wall thickness (MWT) were independent predictors of the presence of LGE (OR = 3.193, P = 0.033; OR = 1.410, P < 0.001, respectively), whereas log NT-proBNP was not. According to the ROC curve analysis, combined measurements of MWT ≥21 mm and/or cTnI ≥0.025ng/ml indicated good diagnostic performance for the presence of LGE, with specificity of 95% or sensitivity of 88%. Conclusions Serum cTnI is an independent predictor useful for identifying myocardial fibrosis, while plasma NT-proBNP is only associated with myocardial fibrosis on univariate analysis. Combined measurements of serum cTnI with MWT further improve its value in detecting myocardial fibrosis in patients with HOCM. PMID:26765106

  12. Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

    NASA Technical Reports Server (NTRS)

    Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.

    2008-01-01

    This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.

  13. Method for predicting photocatalytic oxidation rates of organic compounds.

    PubMed

    Sattler, Melanie L; Liljestrand, Howard M

    2003-01-01

    In designing a photocatalytic oxidation (PCO) system for a given air pollution source, destruction rates for volatile organic compounds (VOCs) are required. The objective of this research was to develop a systematic method of predicting PCO rate constants by correlating rate constants with physical-chemical characteristics of compounds. Accordingly, reaction rate constants were determined for destruction of volatile organics over a titanium dioxide (TiO2) catalyst in a continuous mixed-batch reactor. It was found that PCO rate constants for alkanes and alkenes vary linearly with gas-phase ionization potential (IP) and with gas-phase hydroxyl radical reaction rate constant. The correlations allow rates of destruction of compounds not tested in this research to be predicted based on physical-chemical characteristics. PMID:12568248

  14. Methods for exploring uncertainty in groundwater management predictions

    USGS Publications Warehouse

    Guillaume, Joseph H. A.; Hunt, Randall J.; Comunian, Alessandro; Fu, Baihua; Blakers, Rachel S; Jakeman, Anthony J; Barreteau, Olivier; Hunt, Randall J.; Rinaudo, Jean-Daniel; Ross, Andrew

    2016-01-01

    Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

  15. Prediction of protein-peptide interactions: application of the XPairIt API to anthrax lethal factor and substrates

    NASA Astrophysics Data System (ADS)

    Hurley, Margaret M.; Sellers, Michael S.

    2013-05-01

    As software and methodology develop, key aspects of molecular interactions such as detailed energetics and flexibility are continuously better represented in docking simulations. In the latest iteration of the XPairIt API and Docking Protocol, we perform a blind dock of a peptide into the cleavage site of the Anthrax lethal factor (LF) metalloprotein. Molecular structures are prepared from RCSB:1JKY and we demonstrate a reasonably accurate docked peptide through analysis of protein motion and, using NCI Plot, visualize and characterize the forces leading to binding. We compare our docked structure to the 1JKY crystal structure and the more recent 1PWV structure, and discuss both captured and overlooked interactions. Our results offer a more detailed look at secondary contact and show that both van der Waals and electrostatic interactions from peptide residues further from the enzyme's catalytic site are significant.

  16. PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM

    PubMed Central

    Ghanat Bari, Mehrab; Ma, Xuepo; Zhang, Jianqiu

    2014-01-01

    Motivation: In liquid chromatography–mass spectrometry/tandem mass spectrometry (LC-MS/MS), it is necessary to link tandem MS-identified peptide peaks so that protein expression changes between the two runs can be tracked. However, only a small number of peptides can be identified and linked by tandem MS in two runs, and it becomes necessary to link peptide peaks with tandem identification in one run to their corresponding ones in another run without identification. In the past, peptide peaks are linked based on similarities in retention time (rt), mass or peak shape after rt alignment, which corrects mean rt shifts between runs. However, the accuracy in linking is still limited especially for complex samples collected from different conditions. Consequently, large-scale proteomics studies that require comparison of protein expression profiles of hundreds of patients can not be carried out effectively. Method: In this article, we consider the problem of linking peptides from a pair of LC-MS/MS runs and propose a new method, PeakLink (PL), which uses information in both the time and frequency domain as inputs to a non-linear support vector machine (SVM) classifier. The PL algorithm first uses a threshold on an rt likelihood ratio score to remove candidate corresponding peaks with excessively large elution time shifts, then PL calculates the correlation between a pair of candidate peaks after reducing noise through wavelet transformation. After converting rt and peak shape correlation to statistical scores, an SVM classifier is trained and applied for differentiating corresponding and non-corresponding peptide peaks. Results: PL is tested in multiple challenging cases, in which LC-MS/MS samples are collected from different disease states, different instruments and different laboratories. Testing results show significant improvement in linking accuracy compared with other algorithms. Availability and implementation: M files for the PL alignment method are available

  17. Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

    PubMed Central

    2010-01-01

    Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant

  18. Predicting recreational water quality advisories: A comparison of statistical methods

    USGS Publications Warehouse

    Brooks, Wesley R.; Corsi, Steven R.; Fienen, Michael N.; Carvin, Rebecca B.

    2016-01-01

    Epidemiological studies indicate that fecal indicator bacteria (FIB) in beach water are associated with illnesses among people having contact with the water. In order to mitigate public health impacts, many beaches are posted with an advisory when the concentration of FIB exceeds a beach action value. The most commonly used method of measuring FIB concentration takes 18–24 h before returning a result. In order to avoid the 24 h lag, it has become common to ”nowcast” the FIB concentration using statistical regressions on environmental surrogate variables. Most commonly, nowcast models are estimated using ordinary least squares regression, but other regression methods from the statistical and machine learning literature are sometimes used. This study compares 14 regression methods across 7 Wisconsin beaches to identify which consistently produces the most accurate predictions. A random forest model is identified as the most accurate, followed by multiple regression fit using the adaptive LASSO.

  19. Species Identification of Bovine, Ovine and Porcine Type 1 Collagen; Comparing Peptide Mass Fingerprinting and LC-Based Proteomics Methods

    PubMed Central

    Buckley, Mike

    2016-01-01

    Collagen is one of the most ubiquitous proteins in the animal kingdom and the dominant protein in extracellular tissues such as bone, skin and other connective tissues in which it acts primarily as a supporting scaffold. It has been widely investigated scientifically, not only as a biomedical material for regenerative medicine, but also for its role as a food source for both humans and livestock. Due to the long-term stability of collagen, as well as its abundance in bone, it has been proposed as a source of biomarkers for species identification not only for heat- and pressure-rendered animal feed but also in ancient archaeological and palaeontological specimens, typically carried out by peptide mass fingerprinting (PMF) as well as in-depth liquid chromatography (LC)-based tandem mass spectrometric methods. Through the analysis of the three most common domesticates species, cow, sheep, and pig, this research investigates the advantages of each approach over the other, investigating sites of sequence variation with known functional properties of the collagen molecule. Results indicate that the previously identified species biomarkers through PMF analysis are not among the most variable type 1 collagen peptides present in these tissues, the latter of which can be detected by LC-based methods. However, it is clear that the highly repetitive sequence motif of collagen throughout the molecule, combined with the variability of the sites and relative abundance levels of hydroxylation, can result in high scoring false positive peptide matches using these LC-based methods. Additionally, the greater alpha 2(I) chain sequence variation, in comparison to the alpha 1(I) chain, did not appear to be specific to any particular functional properties, implying that intra-chain functional constraints on sequence variation are not as great as inter-chain constraints. However, although some of the most variable peptides were only observed in LC-based methods, until the range of

  20. Non-animal test methods for predicting skin sensitization potentials.

    PubMed

    Mehling, Annette; Eriksson, Tove; Eltze, Tobias; Kolle, Susanne; Ramirez, Tzutzuy; Teubner, Wera; van Ravenzwaay, Bennard; Landsiedel, Robert

    2012-08-01

    Contact allergies are complex diseases, and it is estimated that 15-20 % of the general population suffers from contact allergy, with increasing prevalence. Evaluation of the sensitization potential of a substance is usually carried out in animal models. Nowadays, there is much interest in reducing and ultimately replacing current animal tests. Furthermore, as of 2013, the EU has posed a ban on animal testing of cosmetic ingredients that includes skin sensitization. Therefore, predictive and robust in vitro tests are urgently needed. In order to establish alternatives to animal testing, the in vitro tests must mimic the very complex interactions between the sensitizing chemical and the different parts of the immune system. This review article summarizes recent efforts to develop in vitro tests for predicting skin sensitizers. Cell-based assays, in chemico methods and, to a lesser extent, in silico methods are presented together with a discussion of their current status. With considerable progress having been achieved during the last years, the rationale today is that data from different non-animal test methods will have to be combined in order to obtain reliable hazard and potency information on potential skin sensitizers. PMID:22707154

  1. Unstructured CFD and Noise Prediction Methods for Propulsion Airframe Aeroacoustics

    NASA Technical Reports Server (NTRS)

    Pao, S. Paul; Abdol-Hamid, Khaled S.; Campbell, Richard L.; Hunter, Craig A.; Massey, Steven J.; Elmiligui, Alaa A.

    2006-01-01

    Using unstructured mesh CFD methods for Propulsion Airframe Aeroacoustics (PAA) analysis has the distinct advantage of precise and fast computational mesh generation for complex propulsion and airframe integration arrangements that include engine inlet, exhaust nozzles, pylon, wing, flaps, and flap deployment mechanical parts. However, accurate solution values of shear layer velocity, temperature and turbulence are extremely important for evaluating the usually small noise differentials of potential applications to commercial transport aircraft propulsion integration. This paper describes a set of calibration computations for an isolated separate flow bypass ratio five engine nozzle model and the same nozzle system with a pylon. These configurations have measured data along with prior CFD solutions and noise predictions using a proven structured mesh method, which can be used for comparison to the unstructured mesh solutions obtained in this investigation. This numerical investigation utilized the TetrUSS system that includes a Navier-Stokes solver, the associated unstructured mesh generation tools, post-processing utilities, plus some recently added enhancements to the system. New features necessary for this study include the addition of two equation turbulence models to the USM3D code, an h-refinement utility to enhance mesh density in the shear mixing region, and a flow adaptive mesh redistribution method. In addition, a computational procedure was developed to optimize both solution accuracy and mesh economy. Noise predictions were completed using an unstructured mesh version of the JeT3D code.

  2. Predictions for rapid methods and automation in food microbiology.

    PubMed

    Fung, Daniel Y C

    2002-01-01

    A discussion is presented on the present status of rapid methods and automation in microbiology. Predictions are also presented for development in the following areas: viable cell counts; real-time monitoring of hygiene; polymerase chain reaction, ribotyping, and genetic tests in food laboratories; automated enzyme-linked immunosorbent assay and immunotests; rapid dipstick technology; biosensors for Hazard Analysis Critical Control Point programs; instant detection of target pathogens by computer-generated matrix; effective separation and concentration for rapid identification of target cells; microbiological alert systems in food packages; and rapid alert kits for detecting pathogens at home.

  3. Novel copoly(styrene-divinylbenzene)-resins with different phenylmethylamine groups for use in Peptide synthesis method.

    PubMed

    Souza, Sinval E G; Malavolta, Luciana; Cilli, Eduardo M; Schreier, Shirley; Jubilut, Guita N; Nakaie, Clovis R

    2015-01-01

    Differently than the 4-methylbenzhydrylamine-resin (MBHAR) which contains a methyl group coupled to the phenylmethylamine-functionalized copoly(styrene-divinilbenzene) structure, alternative resins containing the electron-donating 4-tert-butyl- (BUBHAR) or the electron-withdrawing 2-chloro- (ClBHAR) and 2,4-chloro- (diClBHAR) groups were developed as potential supports for α- carboxamide peptide synthesis. Initially, a time-course investigation of HF cleavage reaction (0 °C) with these resins bearing the vasoconstrictor angiotensin II (AngII, DRVYIHPF) or its Gly(8)-AngII analogue revealed that the peptide- BUBHAR linkage is much more labile than those with ClBHAR or diClBHAR. HF cleavage times of near 2 h or longer than 24 h were needed for complete removal of peptide chains from these two classes of resin, respectively. By including MBHAR and benzhydrylamine-resins (BHAR) in this comparative study, the decreasing order of acid stability of the peptidyl- resin linkage was diClBHAR > ClBHAR > BHAR > MBHAR ~ BUBHAR. The same stability order was observed for the HCl/propionic acid hydrolysis reaction (130°C) with the Phe- or Gly-resins. These findings thus suggest that ClBHAR and diClBHAR are not appropriate for use in peptide synthesis. Nevertheless, these supports could still be tested as stationary phases for affinity chromatography. When placed into more apolar solvents, the beads of all of these resins exhibited a greater swelling (as measured by a microscope) or higher mobility of the polymer matrix (as measured with EPR experiments using spin-labeled beads). Moreover, under the latter approach, BUBHAR displayed a comparatively higher solvation degree than did MBHAR (in DCM, DMF and NMP), with slightly higher peptide synthesis yields as well. PMID:25658115

  4. An experiment in hurricane track prediction using parallel computing methods

    NASA Technical Reports Server (NTRS)

    Song, Chang G.; Jwo, Jung-Sing; Lakshmivarahan, S.; Dhall, S. K.; Lewis, John M.; Velden, Christopher S.

    1994-01-01

    The barotropic model is used to explore the advantages of parallel processing in deterministic forecasting. We apply this model to the track forecasting of hurricane Elena (1985). In this particular application, solutions to systems of elliptic equations are the essence of the computational mechanics. One set of equations is associated with the decomposition of the wind into irrotational and nondivergent components - this determines the initial nondivergent state. Another set is associated with recovery of the streamfunction from the forecasted vorticity. We demonstrate that direct parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to this decomposition and forecast problem. A 72-h track prediction was made using incremental time steps of 16 min on a network of 3000 grid points nominally separated by 100 km. The prediction took 30 sec on the 8-processor Alliant FX/8 computer. This was a speed-up of 3.7 when compared to the one-processor version. The 72-h prediction of Elena's track was made as the storm moved toward Florida's west coast. Approximately 200 km west of Tampa Bay, Elena executed a dramatic recurvature that ultimately changed its course toward the northwest. Although the barotropic track forecast was unable to capture the hurricane's tight cycloidal looping maneuver, the subsequent northwesterly movement was accurately forecasted as was the location and timing of landfall near Mobile Bay.

  5. A Primer In Advanced Fatigue Life Prediction Methods

    NASA Technical Reports Server (NTRS)

    Halford, Gary R.

    2000-01-01

    Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

  6. Development of a LC-MS/MS method to monitor palmitoyl peptides content in anti-wrinkle cosmetics.

    PubMed

    Chirita, Raluca-Ioana; Chaimbault, Patrick; Archambault, Jean-Christophe; Robert, Isabelle; Elfakir, Claire

    2009-05-01

    Palmitoyl peptides are anti-aging agents widely used in cosmetics. This article describes the development of a LC-MS/MS analytical procedure that allows, after a liquid-liquid extraction procedure, their unambiguous detection in cosmetic formulation. MS/MS detection is shown to be specific regarding placebo formulations. Limits of quantification, linearity, accuracy and precision of the method were estimated. The results presented show that palmitoyl peptides can be thus reliably assayed. The palmitoylated pentapeptide palmitoyl-lysyl-threonyl-threonyl-lysyl-serine (pal-KTTKS) was assayed in anti-wrinkle creams using palmitoyl-glycyl-histidyl-lysine (pal-GHK) as internal standard. From the results obtained, the influence of the formulation on pal-KTTKS availability is evidenced. PMID:19393372

  7. In silico peptide prediction for antibody generation to recognize 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in genetically modified organisms.

    PubMed

    Marani, Mariela M; Costa, Joana; Mafra, Isabel; Oliveira, Maria Beatriz P P; Camperi, Silvia A; Leite, José Roberto de Souza Almeida

    2015-03-01

    For the prospective immunorecognition of 5-enolpyruvylshikimate-3-phosphate synthase (CP4-EPSPS) as a biomarker protein expressed by transgenic soybean, an extensive in silico evaluation of the referred protein was performed. The main objective of this study was the selection of a set of peptides that could function as potential immunogens for the production of novel antibodies against CP4-EPSPS protein. For this purpose, the protein was in silico cleaved with trypsin/chymotrypsin and the resultant peptides were extensively analyzed for further selection of the best candidates for antibody production. The analysis enabled the successful proposal of four peptides with potential immunogenicity for their future use as screening biomarkers of genetically modified organisms. To our knowledge, this is the first attempt to select and define potential linear epitopes for the immunization of animals and, subsequently, to generate adequate antibodies for CP4-EPSPS recognition. The present work will be followed by the synthesis of the candidate peptides to be incubated in animals for antibody generation and potential applicability for the development of an immunosensor for CP4-EPSPS detection.

  8. Prediction and In Silico Identification of Novel B-Cells and T-Cells Epitopes in the S1-Spike Glycoprotein of M41 and CR88 (793/B) Infectious Bronchitis Virus Serotypes for Application in Peptide Vaccines

    PubMed Central

    Hair Bejo, Mohd; Kadkhodaei, Saeid

    2016-01-01

    Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, YTSNETTDVTS175–185, was identified in M41 IBV strains while three such epitopes types namely, VSNASPNSGGVD279–290, HPKCNFRPENI328–338, and NETNNAGSVSDCTAGT54–69, were predicted in CR88 IBV strains. Analysis of MHCI binding peptides in M41 IBV strains revealed the presence of 15 antigenic peptides out of which 12 were highly conserved in 96–100% of the total M41 strains analysed. Interestingly three of these peptides, GGPITYKVM208, WFNSLSVSI356, and YLADAGLAI472, relatively had high antigenicity index (>1.0). On the other hand, 11 MHCI binding epitope peptides were identified in CR88 IBV strains. Of these, five peptides were found to be highly conserved with a range between 90% and 97%. However, WFNSLSVSL358, SYNISAASV88, and YNISAASVA89 peptides comparably showed high antigenicity scores (>1.0). Combination of antigenic B-cells and T-cells peptides that are conserved across many strains as approach to evoke humoral and CTL immune response will potentially lead to a broad-based vaccine that could reduce the challenges in using live attenuated vaccine technology in the control of IBV infection in poultry. PMID:27667997

  9. Prediction and In Silico Identification of Novel B-Cells and T-Cells Epitopes in the S1-Spike Glycoprotein of M41 and CR88 (793/B) Infectious Bronchitis Virus Serotypes for Application in Peptide Vaccines.

    PubMed

    Bande, Faruku; Arshad, Siti Suri; Hair Bejo, Mohd; Kadkhodaei, Saeid; Omar, Abdul Rahman

    2016-01-01

    Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, YTSNETTDVTS(175-185), was identified in M41 IBV strains while three such epitopes types namely, VSNASPNSGGVD(279-290), HPKCNFRPENI(328-338), and NETNNAGSVSDCTAGT(54-69), were predicted in CR88 IBV strains. Analysis of MHCI binding peptides in M41 IBV strains revealed the presence of 15 antigenic peptides out of which 12 were highly conserved in 96-100% of the total M41 strains analysed. Interestingly three of these peptides, GGPITYKVM(208), WFNSLSVSI(356), and YLADAGLAI(472), relatively had high antigenicity index (>1.0). On the other hand, 11 MHCI binding epitope peptides were identified in CR88 IBV strains. Of these, five peptides were found to be highly conserved with a range between 90% and 97%. However, WFNSLSVSL(358), SYNISAASV(88), and YNISAASVA(89) peptides comparably showed high antigenicity scores (>1.0). Combination of antigenic B-cells and T-cells peptides that are conserved across many strains as approach to evoke humoral and CTL immune response will potentially lead to a broad-based vaccine that could reduce the challenges in using live attenuated vaccine technology in the control of IBV infection in poultry. PMID:27667997

  10. Prediction and In Silico Identification of Novel B-Cells and T-Cells Epitopes in the S1-Spike Glycoprotein of M41 and CR88 (793/B) Infectious Bronchitis Virus Serotypes for Application in Peptide Vaccines

    PubMed Central

    Hair Bejo, Mohd; Kadkhodaei, Saeid

    2016-01-01

    Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, YTSNETTDVTS175–185, was identified in M41 IBV strains while three such epitopes types namely, VSNASPNSGGVD279–290, HPKCNFRPENI328–338, and NETNNAGSVSDCTAGT54–69, were predicted in CR88 IBV strains. Analysis of MHCI binding peptides in M41 IBV strains revealed the presence of 15 antigenic peptides out of which 12 were highly conserved in 96–100% of the total M41 strains analysed. Interestingly three of these peptides, GGPITYKVM208, WFNSLSVSI356, and YLADAGLAI472, relatively had high antigenicity index (>1.0). On the other hand, 11 MHCI binding epitope peptides were identified in CR88 IBV strains. Of these, five peptides were found to be highly conserved with a range between 90% and 97%. However, WFNSLSVSL358, SYNISAASV88, and YNISAASVA89 peptides comparably showed high antigenicity scores (>1.0). Combination of antigenic B-cells and T-cells peptides that are conserved across many strains as approach to evoke humoral and CTL immune response will potentially lead to a broad-based vaccine that could reduce the challenges in using live attenuated vaccine technology in the control of IBV infection in poultry.

  11. Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2006-01-01

    compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

  12. Context-dependent effects on the hydrophilicity/hydrophobicity of side-chains during reversed-phase high-performance liquid chromatography: Implications for prediction of peptide retention behaviour

    PubMed Central

    Mant, C.T.; Hodges, R.S.

    2009-01-01

    The present study set out to investigate whether observed relative hydrophilicity/hydrophobicity values of positively charged side-chains (with Lys and Arg as representative side-chains) or hydrophobic side-chains (with Ile as the representative side-chain) were context-dependent, i.e., did such measured values vary depending on characteristics of the peptides within which such side-chains are substituted (overall peptide hydrophobicity, number of positive charges) and/or properties of the mobile phase (anionic counterions of varying hydrophobicity and concentration)? Reversed-phase high-performance liquid chromatography (RP-HPLC) was applied to two series of four synthetic peptide analogues (+1, +2, +3 and +4 net charge), the only difference between the two peptide series being the substitution of one hydrophobic Ile residue for a Gly residue, in the presence of anionic ion-pairing reagents of varying hydrophobicity (HCOOH ≈ H3PO4 < TFA < PFPA < HFBA) and concentration (2–50 mM). RP-HPLC of these peptide series revealed that the relative hydrophilicity of Lys and Arg side-chains in the peptides increased with peptide hydrophobicity. In addition the relative hydrophobicity of Ile decreased dramatically with an increase in the number of positive charges in the peptide, this hydrophobicity decrease being of greater magnitude as the hydrophobicity of the anionic ion-pairing reagent increased. These results have significant implications in the prediction of peptide retention times for proteomic applications. PMID:16814308

  13. GalNAc-transferase specificity prediction based on feature selection method.

    PubMed

    Lu, Lin; Niu, Bing; Zhao, Jun; Liu, Liang; Lu, Wen-Cong; Liu, Xiao-Jun; Li, Yi-Xue; Cai, Yu-Dong

    2009-02-01

    GalNAc-transferase can catalyze the biosynthesis of O-linked oligosaccharides. The specificity of GalNAc-transferase is composed of nine amino acid residues denoted by R4, R3, R2, R1, R0, R1', R2', R3', R4'. To predict whether the reducing monosaccharide will be covalently linked to the central residue R0(Ser or Thr), a new method based on feature selection has been proposed in our work. 277 nonapeptides from reference [Chou KC. A sequence-coupled vector-projection model for predicting the specificity of GalNAc-transferase. Protein Sci 1995;4:1365-83] are chosen for training set. Each nonapeptide is represented by hundreds of amino acid properties collected by Amino Acid Index database (http://www.genome.jp/aaindex) and transformed into a numeric vector with 4554 features. The Maximum Relevance Minimum Redundancy (mRMR) method combining with Incremental Feature Selection (IFS) and Feature Forward Selection (FFS) are then applied for feature selection. Nearest Neighbor Algorithm (NNA) is used to build prediction models. The optimal model contains 54 features and its correct rate tested by Jackknife cross-validation test reaches 91.34%. Final feature analysis indicates that amino acid residues at position R3' play the most important role in the recognition of GalNAc-transferase specificity, which were confirmed by the experiments [Elhammer AP, Poorman RA, Brown E, Maggiora LL, Hoogerheide JG, Kezdy FJ. The specificity of UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase as inferred from a database of in vivo substrates and from the in vitro glycosylation of proteins and peptides. J Biol Chem 1993;268:10029-38; O'Connell BC, Hagen FK, Tabak LA. The influence of flanking sequence on the O-glycosylation of threonine in vitro. J Biol Chem 1992;267:25010-8; Yoshida A, Suzuki M, Ikenaga H, Takeuchi M. Discovery of the shortest sequence motif for high level mucin-type O-glycosylation. J Biol Chem 1997;272:16884-8]. Our method can be used as a tool for predicting O

  14. Predicting Hepatic Steatosis in Living Liver Donors via Noninvasive Methods.

    PubMed

    Kim, Jong Man; Ha, Sang Yun; Joh, Jae-Won; Sinn, Dong Hyun; Jeong, Woo Kyung; Choi, Gyu-Seong; Gwak, Geum Youn; Kwon, Choon Hyuck David; Kim, Young Kon; Paik, Yong Han; Lee, Joon Hyeok; Lee, Won Jae; Lee, Suk-Koo; Park, Cheol Keun

    2016-02-01

    Hepatic steatosis assessment is of paramount importance for living liver donor selection because significant hepatic steatosis can affect the postoperative outcome of recipients and the safety of the donor. The validity of various noninvasive imaging methods to assess hepatic steatosis remains controversial. The purpose of our study is to investigate the association between noninvasive imaging methods and pathology to detect steatosis in living liver donors and to propose a prediction model for hepatic steatosis. Liver stiffness measurements (LSMs) and controlled attenuation parameter values in vibration controlled transient elastography, ultrasonography, computed tomography (CT), and magnetic resonance imaging were used as pretransplant screening methods to evaluate living liver donors between 2012 and 2014. Only 1 pathologist assessed tissue sample for hepatic steatosis. The median age of the 79 living donors (53 men and 26 women) was 32 years (16-68 years). The CT liver-spleen attenuation (L-S) difference and the controlled attenuation parameter values were well correlated with the level of hepatic steatosis on liver pathology. Multivariate analysis showed that liver stiffness measurement (LSM) (β = 0.903; 95% CI, 0.105-1.702; P = 0.027) and the CT L to S attenuation difference (β = -3.322; 95% CI, -0.502 to -0.142; P = 0.001) were closely associated with hepatic steatosis. We generated the following equation to predict total hepatic steatosis: Hepatic steatosis = 0.903 × LSM - 0.322 × CT L to S attenuation difference (AUC = 86.6% and P = 0.001). The values predicted by the equation correlated well with the presence of hepatic steatosis (r = 0.509 and P < 0.001). The combination of nonenhanced CT L to S attenuation difference and transient elastography using vibration controlled transient elastography provides sufficient information to predict hepatic steatosis in living liver donor candidates. PMID:26886612

  15. Predicting Hepatic Steatosis in Living Liver Donors via Noninvasive Methods

    PubMed Central

    Kim, Jong Man; Ha, Sang Yun; Joh, Jae-Won; Sinn, Dong Hyun; Jeong, Woo Kyung; Choi, Gyu-Seong; Gwak, Geum Youn; Kwon, Choon Hyuck David; Kim, Young Kon; Paik, Yong Han; Lee, Joon Hyeok; Lee, Won Jae; Lee, Suk-Koo; Park, Cheol Keun

    2016-01-01

    Abstract Hepatic steatosis assessment is of paramount importance for living liver donor selection because significant hepatic steatosis can affect the postoperative outcome of recipients and the safety of the donor. The validity of various noninvasive imaging methods to assess hepatic steatosis remains controversial. The purpose of our study is to investigate the association between noninvasive imaging methods and pathology to detect steatosis in living liver donors and to propose a prediction model for hepatic steatosis. Liver stiffness measurements (LSMs) and controlled attenuation parameter values in vibration controlled transient elastography, ultrasonography, computed tomography (CT), and magnetic resonance imaging were used as pretransplant screening methods to evaluate living liver donors between 2012 and 2014. Only 1 pathologist assessed tissue sample for hepatic steatosis. The median age of the 79 living donors (53 men and 26 women) was 32 years (16–68 years). The CT liver–spleen attenuation (L–S) difference and the controlled attenuation parameter values were well correlated with the level of hepatic steatosis on liver pathology. Multivariate analysis showed that liver stiffness measurement (LSM) (β = 0.903; 95% CI, 0.105–1.702; P = 0.027) and the CT L to S attenuation difference (β = −3.322; 95% CI, −0.502 to −0.142; P = 0.001) were closely associated with hepatic steatosis. We generated the following equation to predict total hepatic steatosis: Hepatic steatosis = 0.903 × LSM – 0.322 × CT L to S attenuation difference (AUC = 86.6% and P = 0.001). The values predicted by the equation correlated well with the presence of hepatic steatosis (r = 0.509 and P < 0.001). The combination of nonenhanced CT L to S attenuation difference and transient elastography using vibration controlled transient elastography provides sufficient information to predict hepatic steatosis in living liver donor

  16. Decision tree methods: applications for classification and prediction.

    PubMed

    Song, Yan-Yan; Lu, Ying

    2015-04-25

    Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure. PMID:26120265

  17. Mathematical analysis method for predicting temperature rise in BIPV

    NASA Astrophysics Data System (ADS)

    Ibarahim, Zahari; Ruslan, Mohd Hafidz; Ibrahim, Zamry

    2013-05-01

    In order to estimate the airflow rate and temperature in the channel of building an integrated photovoltaic (BIPV) system, a simplified mathematical method has been derived in which the buoyancy force balances the friction along the channel. The channel is represented as a closed duct and the pressure losses are calculated in a similar fashion to those in a pipe circuit. Pressure losses at ventilation inlets and outlets are calculated using pressure loss factors, Kf. The effect of wind pressure on mass flow rate and temperature in the channel can be estimated with the inclusion of the wind speed pressure into the formulation. The benefit of wind pressure applied normal to the inlet and tangential to the outlet of the channel can be seen. The procedure yields the mass flow rate and temperature directly by solution of a simple cubic equation. This method allows the engineers and scientist to predict optimum configuration of their PV cladding design.

  18. Recent methods for predicting quality of whole meat.

    PubMed

    Monin, G

    1998-01-01

    The world of meat faces a permanent need for new methods of meat quality evaluation. Researchers want improved techniques to deepen their understanding of meat features. Expectations of consumers for meat quality grow constantly, which induces the necessity of quality control at the levels of slaughtering, meat cutting, and distribution. This article is focused on techniques intended to predict technological and sensory qualities from measurements carried out on fresh intact meat. pH has been measured for a long time, but its on-line determination still progresses through automation. In the laboratory, NMR provides new insights on WHC mechanisms. Image processing has considerably improved the assessment of meat appearance. Developments of techniques for prediction of toughness are in progress, either directly, through ultrasonic analysis or NIR reflectance, or indirectly, through determination of connective tissue content by fluorescence probes. Control of authenticity benefits from the last developments of molecular biology and analytical chemistry. However, implementation of methods for meat quality evaluation has been very limited in the industry. The reasons for that situation are analyzed. Among the techniques recently described, the most promising for large-scale meat quality evaluation are considered to be ultrasonic analysis, image processing and NIR spectroscopy.

  19. Conditional Weather Resampling Method for Seasonal Ensemble Streamflow Prediction

    NASA Astrophysics Data System (ADS)

    Beckers, Joost; Weerts, Albrecht; Welles, Edwin

    2014-05-01

    Ensemble Streamflow Prediction (ESP) is a commonly used method for water resources planning on the seasonal time scale. The starting point for the ESP is the current state of the hydrological system, which is generated form a short historical simulation up to the time of forecast. Starting from this initial state, a hydrologic model is run to produce an ensemble of possible realizations of future streamflows, taking meteorological time series from historical years as input. It is assumed that these historical weather time series represent climatology. One disadvantage of the original ESP method is that an expected deviation from average climatology is not accounted for. Here, we propose a variation to the ESP, in which shorter periods from historical time years are resampled and assembled to generate additional possible realizations of future weather. The resampling is done in such a way as to incorporate statistical deviations from the average climate that are linked to climate modes, such as El Niño Southern Oscillation (ENSO) or Pacific Decadal Oscillation (PDO). These climate modes are known to affect the local weather in many regions around the world. The resampling of historical weather periods is conditioned on the climate mode indices, starting with the current climate index value and searching for historical years with similar climate indices. The resampled weather time series are used as input for the hydrological model, similar to the original ESP procedure. The method was implemented in the operational forecasting environment of Bonneville Power Administration (BPA), which based on Delft-FEWS. The method was run for 55 non-operational years of hindcasts (forecasts in retrospect) for the Columbia River in the North-West of the U.S. An increase in forecast skill up to 5% was found relative to the standard ESP for streamflow predictions at three test-locations.

  20. Detection of trans–cis flips and peptide-plane flips in protein structures

    SciTech Connect

    Touw, Wouter G.; Joosten, Robbie P.; Vriend, Gert

    2015-07-28

    A method is presented to detect peptide bonds that need either a trans–cis flip or a peptide-plane flip. A coordinate-based method is presented to detect peptide bonds that need correction either by a peptide-plane flip or by a trans–cis inversion of the peptide bond. When applied to the whole Protein Data Bank, the method predicts 4617 trans–cis flips and many thousands of hitherto unknown peptide-plane flips. A few examples are highlighted for which a correction of the peptide-plane geometry leads to a correction of the understanding of the structure–function relation. All data, including 1088 manually validated cases, are freely available and the method is available from a web server, a web-service interface and through WHAT-CHECK.

  1. Distinguishing Aspartic and Isoaspartic Acids in Peptides by Several Mass Spectrometric Fragmentation Methods

    NASA Astrophysics Data System (ADS)

    DeGraan-Weber, Nick; Zhang, Jun; Reilly, James P.

    2016-09-01

    Six ion fragmentation techniques that can distinguish aspartic acid from its isomer, isoaspartic acid, were compared. MALDI post-source decay (PSD), MALDI 157 nm photodissociation, tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) charge tagging in PSD and photodissociation, ESI collision-induced dissociation (CID), electron transfer dissociation (ETD), and free-radical initiated peptide sequencing (FRIPS) with CID were applied to peptides containing either aspartic or isoaspartic acid. Diagnostic ions, such as the y-46 and b+H2O, are present in PSD, photodissociation, and charge tagging. c•+57 and z-57 ions are observed in ETD and FRIPS experiments. For some molecules, aspartic and isoaspartic acid yield ion fragments with significantly different intensities. ETD and charge tagging appear to be most effective at distinguishing these residues.

  2. Novel Method for Radiolabeling and Dimerizing Thiolated Peptides Using (18)F-Hexafluorobenzene.

    PubMed

    Jacobson, Orit; Yan, Xuefeng; Ma, Ying; Niu, Gang; Kiesewetter, Dale O; Chen, Xiaoyuan

    2015-10-21

    Hexafluorobenzene (HFB) reacts with free thiols to produce a unique and selective perfluoroaromatic linkage between two sulfurs. We modified this chemical reaction to produce dimeric (18)F-RGD-tetrafluorobenzene (TFB)-RGD, an integrin αvβ3 receptor ligand. (18)F-HFB was prepared by a fluorine exchange reaction using K(18)F/K2.2.2 at room temperature. The automated radiofluorination was optimized to minimize the amount of HFB precursor and, thus, maximize the specific activity. (18)F-HFB was isolated by distillation and subsequently reacted with thiolated c(RGDfk) peptide under basic and reducing conditions. The resulting (18)F-RGD-TFB-RGD demonstrated integrin receptor specific binding, cellular uptake, and in vivo tumor accumulation.(18)F-HFB can be efficiently incorporated into thiol-containing peptides at room temperature to provide novel imaging agents. PMID:26086295

  3. A GIS modeling method applied to predicting forest songbird habitat

    USGS Publications Warehouse

    Dettmers, Randy; Bart, Jonathan

    1999-01-01

    We have developed an approach for using a??presencea?? data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators a??anda?? and a??or.a?? We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on speciesa?? microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these

  4. Extremely Randomized Machine Learning Methods for Compound Activity Prediction.

    PubMed

    Czarnecki, Wojciech M; Podlewska, Sabina; Bojarski, Andrzej J

    2015-11-09

    Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called 'extremely randomized methods'-Extreme Entropy Machine and Extremely Randomized Trees-for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their 'non-extreme' competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  5. Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

    NASA Technical Reports Server (NTRS)

    Pirzadeh, Shahyar Z.

    2003-01-01

    A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

  6. Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

    NASA Technical Reports Server (NTRS)

    Pirzadeh, Shahyar Z.

    2001-01-01

    A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

  7. Predicting human height by Victorian and genomic methods.

    PubMed

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-08-01

    In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified. PMID:19223933

  8. Predicting human height by Victorian and genomic methods

    PubMed Central

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-01-01

    In the Victorian era, Sir Francis Galton showed that ‘when dealing with the transmission of stature from parents to children, the average height of the two parents, … is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4–6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified. PMID:19223933

  9. Predicting human height by Victorian and genomic methods.

    PubMed

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-08-01

    In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.

  10. Computational peptide vaccinology.

    PubMed

    Söllner, Johannes

    2015-01-01

    Immunoinformatics focuses on modeling immune responses for better understanding of the immune system and in many cases for proposing agents able to modify the immune system. The most classical of these agents are vaccines derived from living organisms such as smallpox or polio. More modern vaccines comprise recombinant proteins, protein domains, and in some cases peptides. Generating a vaccine from peptides however requires technologies and concepts very different from classical vaccinology. Immunoinformatics therefore provides the computational tools to propose peptides suitable for formulation into vaccines. This chapter introduces the essential biological concepts affecting design and efficacy of peptide vaccines and discusses current methods and workflows applied to design successful peptide vaccines using computers.

  11. Evolutionary method for predicting surface reconstructions with variable stoichiometry

    NASA Astrophysics Data System (ADS)

    Zhu, Qiang; Li, Li; Oganov, Artem R.; Allen, Philip B.

    2013-05-01

    We present a specially designed evolutionary algorithm for the prediction of surface reconstructions. This technique allows one to automatically explore stable and low-energy metastable configurations with variable surface atoms and variable surface unit cells through the whole chemical potential range. The power of evolutionary search is demonstrated by the efficient identification of diamond 2×1 (100) and 2×1 (111) surface reconstructions with a fixed number of surface atoms and a fixed cell size. With further variation of surface unit cells, we study the reconstructions of the polar surface MgO (111). Experiment has detected an oxygen trimer (ozone) motif [Plass , Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.81.4891 81, 4891 (1998)]. We predict another version of this motif which can be thermodynamically stable in extreme oxygen-rich conditions. Finally, we perform a variable stoichiometry search for a complex ternary system: semipolar GaN (101¯1) with and without adsorbed oxygen. The search yields a counterintuitive reconstruction based on N3 trimers. These examples demonstrate that an automated scheme to explore the energy landscape of surfaces will improve our understanding of surface reconstructions. The method presented in this paper can be generally applied to binary and multicomponent systems.

  12. Methods and Techniques for Risk Prediction of Space Shuttle Upgrades

    NASA Technical Reports Server (NTRS)

    Hoffman, Chad R.; Pugh, Rich; Safie, Fayssal

    1998-01-01

    Since the Space Shuttle Accident in 1986, NASA has been trying to incorporate probabilistic risk assessment (PRA) in decisions concerning the Space Shuttle and other NASA projects. One major study NASA is currently conducting is in the PRA area in establishing an overall risk model for the Space Shuttle System. The model is intended to provide a tool to predict the Shuttle risk and to perform sensitivity analyses and trade studies including evaluation of upgrades. Marshall Space Flight Center (MSFC) and its prime contractors including Pratt and Whitney (P&W) are part of the NASA team conducting the PRA study. MSFC responsibility involves modeling the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). A major challenge that faced the PRA team is modeling the shuttle upgrades. This mainly includes the P&W High Pressure Fuel Turbopump (HPFTP) and the High Pressure Oxidizer Turbopump (HPOTP). The purpose of this paper is to discuss the various methods and techniques used for predicting the risk of the P&W redesigned HPFTP and HPOTP.

  13. Predicting lattice thermal conductivity with help from ab initio methods

    NASA Astrophysics Data System (ADS)

    Broido, David

    2015-03-01

    The lattice thermal conductivity is a fundamental transport parameter that determines the utility a material for specific thermal management applications. Materials with low thermal conductivity find applicability in thermoelectric cooling and energy harvesting. High thermal conductivity materials are urgently needed to help address the ever-growing heat dissipation problem in microelectronic devices. Predictive computational approaches can provide critical guidance in the search and development of new materials for such applications. Ab initio methods for calculating lattice thermal conductivity have demonstrated predictive capability, but while they are becoming increasingly efficient, they are still computationally expensive particularly for complex crystals with large unit cells . In this talk, I will review our work on first principles phonon transport for which the intrinsic lattice thermal conductivity is limited only by phonon-phonon scattering arising from anharmonicity. I will examine use of the phase space for anharmonic phonon scattering and the Grüneisen parameters as measures of the thermal conductivities for a range of materials and compare these to the widely used guidelines stemming from the theory of Liebfried and Schölmann. This research was supported primarily by the NSF under Grant CBET-1402949, and by the S3TEC, an Energy Frontier Research Center funded by the US DOE, office of Basic Energy Sciences under Award No. DE-SC0001299.

  14. Study of improved methods for predicting chemical equilibria

    NASA Astrophysics Data System (ADS)

    Lenz, Terry G.; Vaughan, John D.

    The research involves developing general computational methods for predicting the thermodynamic properties of condensed state chemically reactive systems. The overall effort has encompassed both computer studies, and parallel laboratory experimental work to support the evolving computational models. To date, the soundness of molecular mechanics/force-field techniques were demonstrated for accurate prediction of the thermodynamic properties of chemically reactive systems. Extensive work was done with three molecular mechanics models, Boyd's MOLBD3, Allinger's MMP2 and the Warshel/Lifson/Karplus QCFF/PI program. Not one of these programs at present has general full thermodynamic output capability. Modification of the QCFF/PI is well on its way to full thermodynamic capability. Supporting laboratory studies have involved careful bomb calorimetry for H(sub f) information, X-ray structure determination for accurate molecular geometry data, and kinetics/equilibrium determinations for various prototypical Diels-Alder reactions. Vapor pressure studies for candidate Diels-Alder compounds are also underway. The bomb calorimetric and greater initial effort on vapor pressure studies have replaced the original solvent effect and hindered rotation NMR studies planned, on the basis of most critical data needs for correct computational model development.

  15. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

    Hasselman, T. K.; Chrostowski, Jon D.

    1990-01-01

    Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

  16. Development of methods to predict agglomeration and disposition in FBCs

    SciTech Connect

    Mann, M.D.; Henderson, A.K.; Swanson, M.K.; Erickson, T.A.

    1995-11-01

    This 3-year, multiclient program is providing the information needed to determine the behavior of inorganic components in FBC units using advanced methods of analysis coupled with bench-scale combustion experiments. The major objectives of the program are as follows: (1) To develop further our advanced ash and deposit characterization techniques to quantify the effects of the liquid-phase components in terms of agglomerate formation and ash deposits, (2) To determine the mechanisms of inorganic transformations that lead to bed agglomeration and ash deposition in FBC systems, and (3) To develop a better means to predict the behavior of inorganic components as a function of coal composition, bed material characteristics, and combustion conditions.

  17. In vitro method for prediction of plaque reduction by dentifrice.

    PubMed

    Tepper, Bruce; Howard, Brian; Schnell, Daniel; Mills, Lisa; Xu, Jian

    2015-11-01

    An in vitro Particle Based Biofilm (PBB) model was developed to enable high throughput screening tests to predict clinical plaque reduction. Multi-species oral biofilms were cultured from pooled stimulated human saliva on continuously-colliding hydroxyapatite particles. After three days PBBs were saline washed prior to use in screening tests. Testing involved dosing PBBs for 1min followed by neutralization of test materials and rinsing. PBBs were then assayed for intact biofilm activity measured as ATP. The ranking of commercial dentifrices from most to least reduction of intact biofilm activity was Crest ProHealth Clinical Gum Protection, Crest ProHealth, Colgate Total and Crest Cavity Protection. We demonstrated five advantages of the PBB model: 1) the ATP metric had a linear response over ≥1000-fold dynamic range, 2) potential interference with the ATP assay by treatments was easily eliminated by rinsing PBBs with saline, 3) discriminating power was statistically excellent between all treatment comparisons with the negative controls, 4) screening test results were reproducible across four tests, and 5) the screening test produced the same rank order for dentifrices as clinical studies that measured plaque reduction. In addition, 454 pyrosequencing of the PBBs indicated an oral microbial consortium was present. The most prevalent genera were Neisseria, Rothia, Streptococcus, Porphyromonas, Prevotella, Actinomyces, Fusobacterium, Veillonella and Haemophilus. We conclude these in vitro methods offer an efficient, effective and relevant screening tool for reduction of intact biofilm activity by dentifrices. Moreover, dentifrice rankings by the in vitro test method are expected to predict clinical results for plaque reduction. PMID:26151407

  18. Antimicrobial Peptides in Reptiles

    PubMed Central

    van Hoek, Monique L.

    2014-01-01

    Reptiles are among the oldest known amniotes and are highly diverse in their morphology and ecological niches. These animals have an evolutionarily ancient innate-immune system that is of great interest to scientists trying to identify new and useful antimicrobial peptides. Significant work in the last decade in the fields of biochemistry, proteomics and genomics has begun to reveal the complexity of reptilian antimicrobial peptides. Here, the current knowledge about antimicrobial peptides in reptiles is reviewed, with specific examples in each of the four orders: Testudines (turtles and tortosises), Sphenodontia (tuataras), Squamata (snakes and lizards), and Crocodilia (crocodilans). Examples are presented of the major classes of antimicrobial peptides expressed by reptiles including defensins, cathelicidins, liver-expressed peptides (hepcidin and LEAP-2), lysozyme, crotamine, and others. Some of these peptides have been identified and tested for their antibacterial or antiviral activity; others are only predicted as possible genes from genomic sequencing. Bioinformatic analysis of the reptile genomes is presented, revealing many predicted candidate antimicrobial peptides genes across this diverse class. The study of how these ancient creatures use antimicrobial peptides within their innate immune systems may reveal new understandings of our mammalian innate immune system and may also provide new and powerful antimicrobial peptides as scaffolds for potential therapeutic development. PMID:24918867

  19. Water accessibility in a membrane-inserting peptide comparing Overhauser DNP and pulse EPR methods.

    PubMed

    Segawa, Takuya F; Doppelbauer, Maximilian; Garbuio, Luca; Doll, Andrin; Polyhach, Yevhen O; Jeschke, Gunnar

    2016-05-21

    Water accessibility is a key parameter for the understanding of the structure of biomolecules, especially membrane proteins. Several experimental techniques based on the combination of electron paramagnetic resonance (EPR) spectroscopy with site-directed spin labeling are currently available. Among those, we compare relaxation time measurements and electron spin echo envelope modulation (ESEEM) experiments using pulse EPR with Overhauser dynamic nuclear polarization (DNP) at X-band frequency and a magnetic field of 0.33 T. Overhauser DNP transfers the electron spin polarization to nuclear spins via cross-relaxation. The change in the intensity of the (1)H NMR spectrum of H2O at a Larmor frequency of 14 MHz under a continuous-wave microwave irradiation of the nitroxide spin label contains information on the water accessibility of the labeled site. As a model system for a membrane protein, we use the hydrophobic α-helical peptide WALP23 in unilamellar liposomes of DOPC. Water accessibility measurements with all techniques are conducted for eight peptides with different spin label positions and low radical concentrations (10-20 μM). Consistently in all experiments, the water accessibility appears to be very low, even for labels positioned near the end of the helix. The best profile is obtained by Overhauser DNP, which is the only technique that succeeds in discriminating neighboring positions in WALP23. Since the concentration of the spin-labeled peptides varied, we normalized the DNP parameter ϵ, being the relative change of the NMR intensity, by the electron spin concentration, which was determined from a continuous-wave EPR spectrum.

  20. Water accessibility in a membrane-inserting peptide comparing Overhauser DNP and pulse EPR methods

    NASA Astrophysics Data System (ADS)

    Segawa, Takuya F.; Doppelbauer, Maximilian; Garbuio, Luca; Doll, Andrin; Polyhach, Yevhen O.; Jeschke, Gunnar

    2016-05-01

    Water accessibility is a key parameter for the understanding of the structure of biomolecules, especially membrane proteins. Several experimental techniques based on the combination of electron paramagnetic resonance (EPR) spectroscopy with site-directed spin labeling are currently available. Among those, we compare relaxation time measurements and electron spin echo envelope modulation (ESEEM) experiments using pulse EPR with Overhauser dynamic nuclear polarization (DNP) at X-band frequency and a magnetic field of 0.33 T. Overhauser DNP transfers the electron spin polarization to nuclear spins via cross-relaxation. The change in the intensity of the 1H NMR spectrum of H2O at a Larmor frequency of 14 MHz under a continuous-wave microwave irradiation of the nitroxide spin label contains information on the water accessibility of the labeled site. As a model system for a membrane protein, we use the hydrophobic α-helical peptide WALP23 in unilamellar liposomes of DOPC. Water accessibility measurements with all techniques are conducted for eight peptides with different spin label positions and low radical concentrations (10-20 μM). Consistently in all experiments, the water accessibility appears to be very low, even for labels positioned near the end of the helix. The best profile is obtained by Overhauser DNP, which is the only technique that succeeds in discriminating neighboring positions in WALP23. Since the concentration of the spin-labeled peptides varied, we normalized the DNP parameter ɛ, being the relative change of the NMR intensity, by the electron spin concentration, which was determined from a continuous-wave EPR spectrum.

  1. Effective Design of Multifunctional Peptides by Combining Compatible Functions

    PubMed Central

    Diener, Christian; Garza Ramos Martínez, Georgina; Moreno Blas, Daniel; Castillo González, David A.; Corzo, Gerardo; Castro-Obregon, Susana; Del Rio, Gabriel

    2016-01-01

    Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf. PMID:27096600

  2. Effective Design of Multifunctional Peptides by Combining Compatible Functions.

    PubMed

    Diener, Christian; Garza Ramos Martínez, Georgina; Moreno Blas, Daniel; Castillo González, David A; Corzo, Gerardo; Castro-Obregon, Susana; Del Rio, Gabriel

    2016-04-01

    Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf.

  3. MapReduce Implementation of a Hybrid Spectral Library-Database Search Method for Large-Scale Peptide Identification

    SciTech Connect

    Kalyanaraman, Anantharaman; Cannon, William R.; Latt, Benjamin K.; Baxter, Douglas J.

    2011-11-01

    A MapReduce-based implementation called MR- MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs.

  4. An analytical method for predicting postwildfire peak discharges

    USGS Publications Warehouse

    Moody, John A.

    2012-01-01

    An analytical method presented here that predicts postwildfire peak discharge was developed from analysis of paired rainfall and runoff measurements collected from selected burned basins. Data were collected from 19 mountainous basins burned by eight wildfires in different hydroclimatic regimes in the western United States (California, Colorado, Nevada, New Mexico, and South Dakota). Most of the data were collected for the year of the wildfire and for 3 to 4 years after the wildfire. These data provide some estimate of the changes with time of postwildfire peak discharges, which are known to be transient but have received little documentation. The only required inputs for the analytical method are the burned area and a quantitative measure of soil burn severity (change in the normalized burn ratio), which is derived from Landsat reflectance data and is available from either the U.S. Department of Agriculture Forest Service or the U.S. Geological Survey. The method predicts the postwildfire peak discharge per unit burned area for the year of a wildfire, the first year after a wildfire, and the second year after a wildfire. It can be used at three levels of information depending on the data available to the user; each subsequent level requires either more data or more processing of the data. Level 1 requires only the burned area. Level 2 requires the burned area and the basin average value of the change in the normalized burn ratio. Level 3 requires the burned area and the calculation of the hydraulic functional connectivity, which is a variable that incorporates the sequence of soil burn severity along hillslope flow paths within the burned basin. Measurements indicate that the unit peak discharge response increases abruptly when the 30-minute maximum rainfall intensity is greater than about 5 millimeters per hour (0.2 inches per hour). This threshold may relate to a change in runoff generation from saturated-excess to infiltration-excess overland flow. The

  5. Prediction of plantar shear stress distribution by artificial intelligence methods.

    PubMed

    Yavuz, Metin; Ocak, Hasan; Hetherington, Vincent J; Davis, Brian L

    2009-09-01

    Shear forces under the human foot are thought to be responsible for various foot pathologies such as diabetic plantar ulcers and athletic blisters. Frictional shear forces might also play a role in the metatarsalgia observed among hallux valgus (HaV) and rheumatoid arthritis (RA) patients. Due to the absence of commercial devices capable of measuring shear stress distribution, a number of linear models were developed. All of these have met with limited success. This study used nonlinear methods, specifically neural network and fuzzy logic schemes, to predict the distribution of plantar shear forces based on vertical loading parameters. In total, 73 subjects were recruited; 17 had diabetic neuropathy, 14 had HaV, 9 had RA, 11 had frequent foot blisters, and 22 were healthy. A feed-forward neural network (NN) and adaptive neurofuzzy inference system (NFIS) were built. These systems were then applied to a custom-built platform, which collected plantar pressure and shear stress data as subjects walked over the device. The inputs to both models were peak pressure, peak pressure-time integral, and time to peak pressure, and the output was peak resultant shear. Root-mean-square error (RMSE) values were calculated to test the models' accuracy. RMSE/actual shear ratio varied between 0.27 and 0.40 for NN predictions. Similarly, NFIS estimations resulted in a 0.28-0.37 ratio for local peak values in all subject groups. On the other hand, error percentages for global peak shear values were found to be in the range 11.4-44.1. These results indicate that there is no direct relationship between pressure and shear magnitudes. Future research should aim to decrease error levels by introducing shear stress dependent variables into the models. PMID:19725696

  6. Identification of human adenovirus early region 1 products by using antisera against synthetic peptides corresponding to the predicted carboxy termini.

    PubMed Central

    Yee, S P; Rowe, D T; Tremblay, M L; McDermott, M; Branton, P E

    1983-01-01

    Synthetic peptides were prepared which corresponded to the carboxy termini of the human adenovirus type 5 early region 1B (E1B) 58,000-molecular-weight (58K) protein (Tyr-Ser-Asp-Glu-Asp-Thr-Asp) and of the E1A gene products (Tyr-Gly-Lys-Arg-Pro-Arg-Pro). Antisera raised against these peptides precipitated polypeptides from adenovirus type 5-infected KB cells; serum raised against the 58K carboxy terminus was active against the E1B 58K phosphoprotein, whereas serum raised against the E1A peptide immunoprecipitated four major and at least two minor polypeptides. These latter proteins migrated with apparent molecular weights of 52K, 50K, 48.5K, 45K, 37.5K, and 35K, and all were phosphoproteins. By using tryptic phosphopeptide analysis, the four major species (52K, 50K, 48.5K, and 45K) were found to be related, as would be expected if all were products of the E1A region. The ability of the antipeptide sera to precipitate these viral proteins thus confirmed that the previously proposed sequence of E1 DNA and mRNA and the reading frame of the mRNA are correct. Immunofluorescent-antibody staining with the antipeptide sera indicated that the 58K E1B protein was localized both in the nucleus and in the cytoplasm, especially in the perinuclear region. The E1A-specific serum also stained both discrete patches in the nucleus and diffuse areas of the cytoplasm. These data suggest that both the 58K protein and the E1A proteins may function in or around the nucleus. These highly specific antipeptide sera should allow for a more complete identification and characterization of these important viral proteins. Images PMID:6343626

  7. Efficient Methods to Generate Reproducible Mass Spectra in Matrix-Assisted Laser Desorption Ionization of Peptides

    NASA Astrophysics Data System (ADS)

    Ahn, Sung Hee; Park, Kyung Man; Bae, Yong Jin; Kim, Myung Soo

    2013-06-01

    In our previous matrix-assisted laser desorption ionization (MALDI) studies of peptides, we found that their mass spectra were virtually determined by the effective temperature in the early matrix plume, Tearly, when samples were rather homogeneous. This empirical rule allowed acquisition of quantitatively reproducible spectra. A difficulty in utilizing this rule was the complicated spectral treatment needed to get Tearly. In this work, we found another empirical rule that the total number of particles hitting the detector, or TIC, was a good measure of the spectral temperature and, hence, selection of spectra with the same TIC resulted in reproducible spectra. We also succeeded in obtaining reproducible spectra throughout a measurement by controlling TIC near a preset value through feedback adjustment of laser pulse energy. Both TIC selection and TIC control substantially reduced the shot-to-shot spectral variation in a spot, spot-to-spot variation in a sample, and even sample-to-sample variation in MALDI using α-cyano-4-hydroxycinnamic acid or 2,5-dihydroxybenzoic acid as matrix. Based on the utilization of acquired data, TIC control was more efficient than TIC selection by an order of magnitude. Both techniques produced calibration curves with excellent linearity, suggesting their utility in quantification of peptides.

  8. Numerical Weather Predictions Evaluation Using Spatial Verification Methods

    NASA Astrophysics Data System (ADS)

    Tegoulias, I.; Pytharoulis, I.; Kotsopoulos, S.; Kartsios, S.; Bampzelis, D.; Karacostas, T.

    2014-12-01

    During the last years high-resolution numerical weather prediction simulations have been used to examine meteorological events with increased convective activity. Traditional verification methods do not provide the desired level of information to evaluate those high-resolution simulations. To assess those limitations new spatial verification methods have been proposed. In the present study an attempt is made to estimate the ability of the WRF model (WRF -ARW ver3.5.1) to reproduce selected days with high convective activity during the year 2010 using those feature-based verification methods. Three model domains, covering Europe, the Mediterranean Sea and northern Africa (d01), the wider area of Greece (d02) and central Greece - Thessaly region (d03) are used at horizontal grid-spacings of 15km, 5km and 1km respectively. By alternating microphysics (Ferrier, WSM6, Goddard), boundary layer (YSU, MYJ) and cumulus convection (Kain-­-Fritsch, BMJ) schemes, a set of twelve model setups is obtained. The results of those simulations are evaluated against data obtained using a C-Band (5cm) radar located at the centre of the innermost domain. Spatial characteristics are well captured but with a variable time lag between simulation results and radar data. Acknowledgements: This research is co­financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-­-2013).

  9. Evaluation of a two-point method for prediction of lithium maintenance dosage.

    PubMed

    Karki, S D; Carson, S W; Holden, J M; Nanavati, D

    1987-10-01

    A lithium test dose method, based on the two-point method of Perry et al. (1982), was evaluated in 20 patients for the prediction of maintenance dosage of slow-release lithium carbonate tablets. These predictions were compared with the predictions obtained from the dosing chart of Cooper et al. (1973). The two-point method accurately predicted the maintenance dosage within clinically acceptable limits, but dosages predicted from the dosing chart would have yielded much higher serum lithium concentrations. PMID:3121719

  10. A facile method for expression and purification of (15)N isotope-labeled human Alzheimer's β-amyloid peptides from E. coli for NMR-based structural analysis.

    PubMed

    Sharma, Sudhir C; Armand, Tara; Ball, K Aurelia; Chen, Anna; Pelton, Jeffrey G; Wemmer, David E; Head-Gordon, Teresa

    2015-12-01

    Alzheimer's disease (AD) is a progressive neurodegenerative disease affecting millions of people worldwide. AD is characterized by the presence of extracellular plaques composed of aggregated/oligomerized β-amyloid peptides with Aβ42 peptide representing a major isoform in the senile plaques. Given the pathological significance of Aβ42 in the progression of AD, there is considerable interest in understanding the structural ensembles for soluble monomer and oligomeric forms of Aβ42. This report describes an efficient method to express and purify high quality (15)N isotope-labeled Aβ42 for structural studies by NMR. The protocol involves utilization of an auto induction system with (15)N isotope labeled medium, for high-level expression of Aβ42 as a fusion with IFABP. After the over-expression of the (15)N isotope-labeled IFABP-Aβ42 fusion protein in the inclusion bodies, pure (15)N isotope-labeled Aβ42 peptide is obtained following a purification method that is streamlined and improved from the method originally developed for the isolation of unlabeled Aβ42 peptide (Garai et al., 2009). We obtain a final yield of ∼ 6 mg/L culture for (15)N isotope-labeled Aβ42 peptide. Mass spectrometry and (1)H-(15)N HSQC spectra of monomeric Aβ42 peptide validate the uniform incorporation of the isotopic label. The method described here is equally applicable for the uniform isotope labeling with (15)N and (13)C in Aβ42 peptide as well as its other variants including any Aβ42 peptide mutants.

  11. Stoichiometry determination of the MP1-p14 complex using a novel and cost-efficient method to produce an equimolar mixture of standard peptides.

    PubMed

    Holzmann, Johann; Pichler, Peter; Madalinski, Mathias; Kurzbauer, Robert; Mechtler, Karl

    2009-12-15

    Determination of protein complex stoichiometry can be achieved by absolute quantification of the interacting constituents based on isotope dilution mass spectrometry. Current available platforms for the generation of standard peptides are cost-intensive and deliver variable results concerning the equimolarity of the standard peptides. Here we describe a novel and cost-efficient method to generate an equimolar mixture of standard peptides, which we call the equimolarity through equalizer peptide (EtEP) strategy. The rationale of the strategy allows equalization of internal standard peptides and absolute quantification of any protein of interest via a single peptide, from which the exact amount was determined by amino acid analysis. This and the use of the mTRAQ reagent significantly decrease the costs of absolute quantification and stoichiometry determination. We used the EtEP strategy to determine the MP1-p14 complex stoichiometry of two different concentrations, one simulating a condition following tandem affinity purification. Absolute quantification of MP1-p14 was performed on two different mass spectrometers, and the 1:1 stoichiometry was confirmed with high accuracy and precision. On the basis of the quantification of MP1-p14, we demonstrate the importance to assess completeness of protein digestion and discuss the use of peptides containing labile amino acids and the choice of instrumentation.

  12. Peptide dynamics by molecular dynamics simulation and diffusion theory method with improved basis sets

    NASA Astrophysics Data System (ADS)

    Hsu, Po Jen; Lai, S. K.; Rapallo, Arnaldo

    2014-03-01

    Improved basis sets for the study of polymer dynamics by means of the diffusion theory, and tests on a melt of cis-1,4-polyisoprene decamers, and a toluene solution of a 71-mer syndiotactic trans-1,2-polypentadiene were presented recently [R. Gaspari and A. Rapallo, J. Chem. Phys. 128, 244109 (2008)]. The proposed hybrid basis approach (HBA) combined two techniques, the long time sorting procedure and the maximum correlation approximation. The HBA takes advantage of the strength of these two techniques, and its basis sets proved to be very effective and computationally convenient in describing both local and global dynamics in cases of flexible synthetic polymers where the repeating unit is a unique type of monomer. The question then arises if the same efficacy continues when the HBA is applied to polymers of different monomers, variable local stiffness along the chain and with longer persistence length, which have different local and global dynamical properties against the above-mentioned systems. Important examples of this kind of molecular chains are the proteins, so that a fragment of the protein transthyretin is chosen as the system of the present study. This peptide corresponds to a sequence that is structured in β-sheets of the protein and is located on the surface of the channel with thyroxin. The protein transthyretin forms amyloid fibrils in vivo, whereas the peptide fragment has been shown [C. P. Jaroniec, C. E. MacPhee, N. S. Astrof, C. M. Dobson, and R. G. Griffin, Proc. Natl. Acad. Sci. U.S.A. 99, 16748 (2002)] to form amyloid fibrils in vitro in extended β-sheet conformations. For these reasons the latter is given considerable attention in the literature and studied also as an isolated fragment in water solution where both experimental and theoretical efforts have indicated the propensity of the system to form β turns or α helices, but is otherwise predominantly unstructured. Differing from previous computational studies that employed implicit

  13. Peptide dynamics by molecular dynamics simulation and diffusion theory method with improved basis sets

    SciTech Connect

    Hsu, Po Jen; Lai, S. K.; Rapallo, Arnaldo

    2014-03-14

    Improved basis sets for the study of polymer dynamics by means of the diffusion theory, and tests on a melt of cis-1,4-polyisoprene decamers, and a toluene solution of a 71-mer syndiotactic trans-1,2-polypentadiene were presented recently [R. Gaspari and A. Rapallo, J. Chem. Phys. 128, 244109 (2008)]. The proposed hybrid basis approach (HBA) combined two techniques, the long time sorting procedure and the maximum correlation approximation. The HBA takes advantage of the strength of these two techniques, and its basis sets proved to be very effective and computationally convenient in describing both local and global dynamics in cases of flexible synthetic polymers where the repeating unit is a unique type of monomer. The question then arises if the same efficacy continues when the HBA is applied to polymers of different monomers, variable local stiffness along the chain and with longer persistence length, which have different local and global dynamical properties against the above-mentioned systems. Important examples of this kind of molecular chains are the proteins, so that a fragment of the protein transthyretin is chosen as the system of the present study. This peptide corresponds to a sequence that is structured in β-sheets of the protein and is located on the surface of the channel with thyroxin. The protein transthyretin forms amyloid fibrils in vivo, whereas the peptide fragment has been shown [C. P. Jaroniec, C. E. MacPhee, N. S. Astrof, C. M. Dobson, and R. G. Griffin, Proc. Natl. Acad. Sci. U.S.A. 99, 16748 (2002)] to form amyloid fibrils in vitro in extended β-sheet conformations. For these reasons the latter is given considerable attention in the literature and studied also as an isolated fragment in water solution where both experimental and theoretical efforts have indicated the propensity of the system to form β turns or α helices, but is otherwise predominantly unstructured. Differing from previous computational studies that employed implicit

  14. Peptide dynamics by molecular dynamics simulation and diffusion theory method with improved basis sets.

    PubMed

    Hsu, Po Jen; Lai, S K; Rapallo, Arnaldo

    2014-03-14

    Improved basis sets for the study of polymer dynamics by means of the diffusion theory, and tests on a melt of cis-1,4-polyisoprene decamers, and a toluene solution of a 71-mer syndiotactic trans-1,2-polypentadiene were presented recently [R. Gaspari and A. Rapallo, J. Chem. Phys. 128, 244109 (2008)]. The proposed hybrid basis approach (HBA) combined two techniques, the long time sorting procedure and the maximum correlation approximation. The HBA takes advantage of the strength of these two techniques, and its basis sets proved to be very effective and computationally convenient in describing both local and global dynamics in cases of flexible synthetic polymers where the repeating unit is a unique type of monomer. The question then arises if the same efficacy continues when the HBA is applied to polymers of different monomers, variable local stiffness along the chain and with longer persistence length, which have different local and global dynamical properties against the above-mentioned systems. Important examples of this kind of molecular chains are the proteins, so that a fragment of the protein transthyretin is chosen as the system of the present study. This peptide corresponds to a sequence that is structured in β-sheets of the protein and is located on the surface of the channel with thyroxin. The protein transthyretin forms amyloid fibrils in vivo, whereas the peptide fragment has been shown [C. P. Jaroniec, C. E. MacPhee, N. S. Astrof, C. M. Dobson, and R. G. Griffin, Proc. Natl. Acad. Sci. U.S.A. 99, 16748 (2002)] to form amyloid fibrils in vitro in extended β-sheet conformations. For these reasons the latter is given considerable attention in the literature and studied also as an isolated fragment in water solution where both experimental and theoretical efforts have indicated the propensity of the system to form β turns or α helices, but is otherwise predominantly unstructured. Differing from previous computational studies that employed implicit

  15. Method for the Determination of ¹⁵N Incorporation Percentage in Labeled Peptides and Proteins.

    PubMed

    Kilpatrick, Eric L

    2016-01-01

    Use of labeled (15)N proteins and peptides as internal standards in isotope-dilution mass spectrometry for the quantification of proteins has been increasing and is now accepted as a gold standard for this analysis. As a necessary reagent in this process, stable heavy isotope-labeled internal standards must be rigorously characterized in a number of ways including identity, concentration, purity, and structure. Additionally, the degree of the incorporation of the heavy isotope is a critical feature to consider. For proteins that are (15)N labeled, the percentage of incorporation is a valid measurement used to assess the fitness-to-purpose of the material. This measurement should be objective, repeatable, and based on empirical analysis. One means of assigning this value is to compare a mass spectrum of the isotopic profile of a peptide against a series of theoretical profiles containing different enrichment rates. This comparison can be made using the Pearson product-moment correlation coefficient (r) to find the best match between the empirical and theoretical profiles. Theoretical profiles can be generated using probability multinomial analysis but are computationally intensive and require the use of computers for practical use. The method described in this chapter describes the development and use of a computer program to calculate the percentage of (15)N enrichment of a labeled internal standard. Additionally, methods will be described for the empirical determination of an isotopic profile using a variety of mass spectrometry techniques.

  16. A Low-Cost Method for Multiple Disease Prediction

    PubMed Central

    Bayati, Mohsen; Bhaskar, Sonia; Montanari, Andrea

    2015-01-01

    Recently, in response to the rising costs of healthcare services, employers that are financially responsible for the healthcare costs of their workforce have been investing in health improvement programs for their employees. A main objective of these so called “wellness programs” is to reduce the incidence of chronic illnesses such as cardiovascular disease, cancer, diabetes, and obesity, with the goal of reducing future medical costs. The majority of these wellness programs include an annual screening to detect individuals with the highest risk of developing chronic disease. Once these individuals are identified, the company can invest in interventions to reduce the risk of those individuals. However, capturing many biomarkers per employee creates a costly screening procedure. We propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases. Our solution uses multi-task learning and group dimensionality reduction from machine learning and statistics. We provide empirical validation of the proposed solution using data from two different electronic medical records systems, with comparisons to a statistical benchmark. PMID:26958164

  17. Predictive methods for estimating pesticide flux to air

    SciTech Connect

    Woodrow, J.E.; Seiber, J.N.

    1996-10-01

    Published evaporative flux values for pesticides volatilizing from soil, plants, and water were correlated with compound vapor pressures (VP), modified by compound properties appropriate to the treated matrix (e.g., soil adsorption coefficient [K{sub oc}], water solubility [S{sub w}]). These correlations were formulated as Ln-Ln plots with correlation (r{sup 2}) coefficients in the range 0.93-0.99: (1) Soil surface - Ln flux vs Ln (VP/[K{sub oc} x S{sub w}]); (2) soil incorporation - Ln flux vs Ln [(VP x AR)/(K{sub oc} x S{sub w} x d)] (AR = application rate, d = incorporation depth); (3) plants - Ln flux vs Ln VP; and (4) water - Ln (flux/water conc) vs Ln (VP/Sw). Using estimated flux values from the plant correlation as source terms in the EPA`s SCREEN-2 dispersion model gave downwind concentrations that agreed to within 65-114% with measured concentrations. Further validation using other treated matrices is in progress. These predictive methods for estimating flux, when coupled with downwind dispersion modeling, provide tools for limiting downwind exposures.

  18. Predicting sulphur and nitrogen deposition using a simple statistical method

    NASA Astrophysics Data System (ADS)

    Oulehle, Filip; Kopáček, Jiří; Chuman, Tomáš; Černohous, Vladimír; Hůnová, Iva; Hruška, Jakub; Krám, Pavel; Lachmanová, Zora; Navrátil, Tomáš; Štěpánek, Petr; Tesař, Miroslav; Evans, Christopher D.

    2016-09-01

    Data from 32 long-term (1994-2012) monitoring sites were used to assess temporal development and spatial variability of sulphur (S) and inorganic nitrogen (N) concentrations in bulk precipitation, and S in throughfall, for the Czech Republic. Despite large variance in absolute S and N concentration/deposition among sites, temporal coherence using standardised data (Z score) was demonstrated. Overall significant declines of SO4 concentration in bulk and throughfall precipitation, as well as NO3 and NH4 concentration in bulk precipitation, were observed. Median Z score values of bulk SO4, NO3 and NH4 and throughfall SO4 derived from observations and the respective emission rates of SO2, NOx and NH3 in the Czech Republic and Slovakia showed highly significant (p < 0.001) relationships. Using linear regression models, Z score values were calculated for the whole period 1900-2012 and then back-transformed to give estimates of concentration for the individual sites. Uncertainty associated with the concentration calculations was estimated as 20% for SO4 bulk precipitation, 22% for throughfall SO4, 18% for bulk NO3 and 28% for bulk NH4. The application of the method suggested that it is effective in the long-term reconstruction and prediction of S and N deposition at a variety of sites. Multiple regression modelling was used to extrapolate site characteristics (mean precipitation chemistry and its standard deviation) from monitored to unmonitored sites. Spatially distributed temporal development of S and N depositions were calculated since 1900. The method allows spatio-temporal estimation of the acid deposition in regions with extensive monitoring of precipitation chemistry.

  19. Methods to Study the Role of the Glycocalyx in the Uptake of Cell-Penetrating Peptides.

    PubMed

    Schmidt, Samuel; Wallbrecher, Rike; van Kuppevelt, Toin H; Brock, Roland

    2015-01-01

    Cells are covered by a layer of negatively charged oligo- and polysaccharides, the glycocalyx. Cell-penetrating peptides and other drug delivery vehicles first encounter these polyanions before contacting the lipid bilayer of the plasma membrane. While a large body of data supports the notion that interactions with the glycocalyx promote or even trigger uptake, in some cases, the glycocalyx compromises delivery. As a consequence there is a need to address the role of the glycocalyx in delivery for each specific delivery vehicle and for each particular type of cell. Here, we describe protocols to obtain information on the composition and dynamics of the glycocalyx, and the role of individual glycocalyx components in the uptake of drug delivery vehicles.

  20. Modeling for Airframe Noise Prediction Using Vortex Methods

    NASA Astrophysics Data System (ADS)

    Zheng, Z. Charlie

    2002-12-01

    Various components of the airframe are known to be a significant source of noise. With the advent of technology in quieting modern engines, airframe generated noise competes and, in certain instances, surpasses the engine noise. Airframe noise is most pronounced during aircraft approach when the engines are operating at reduced thrust, and airframe components such as high-lift devices and landing gears are in deployed conditions. Recent experimental studies have reaffirmed that the most significant sources of high-lift noise are from the leading-edge slat and the side edges of flaps. Studies of flow field around these structures have consistently shown that there are complicated unsteady vortical flows such as vortex shedding, secondary vortices and vortex breakdown, which are susceptible to far-field radiated sound. The near-field CFD computational data have been used to calculate the far-field acoustics by employing Ffowcs-Williams/Hawkings equation using Lighthill's analogy. However, because of the limit of current computing capacity, it is very time consuming to generate unsteady Navier-Stokes (N-S) computational data for aeroacoustics. Although the N-S simulations are probably necessary to reveal many complex flow phenomena that are unsteady and fully nonlinear, these simulations are not feasible to be used for parametric design. purposes. The objective of this study is thus to develop theoretical models for airframe noise predictions which have quick turn-around computing time. Since it is known that vorticity is a major mechanism responsible for noise generation on high-lift devices, vortex methods have been chosen as modeling tools. Vortex methods are much faster in comparison with other numerical methods, yet they are able to incorporate nonlinear interactions between vortices. Obviously, as with any theoretical model, assumptions have to be made and justified when such models are used in complex flow. The merit and applicability of the models for

  1. Peptide nanotubes.

    PubMed

    Hamley, Ian W

    2014-07-01

    The self-assembly of different classes of peptide, including cyclic peptides, amyloid peptides and surfactant-like peptides into nanotube structures is reviewed. The modes of self-assembly are discussed. Additionally, applications in bionanotechnology and synthetic materials science are summarized.

  2. C-Peptide Level in Fasting Plasma and Pooled Urine Predicts HbA1c after Hospitalization in Patients with Type 2 Diabetes Mellitus.

    PubMed

    Sonoda, Remi; Tanaka, Kentaro; Kikuchi, Takako; Onishi, Yukiko; Takao, Toshiko; Tahara, Tazu; Yoshida, Yoko; Suzawa, Naoki; Kawazu, Shoji; Iwamoto, Yasuhiko; Kushiyama, Akifumi

    2016-01-01

    In this study, we investigate how measures of insulin secretion and other clinical information affect long-term glycemic control in patients with type 2 diabetes mellitus. Between October 2012 and June 2014, we monitored 202 diabetes patients who were admitted to the hospital of Asahi Life Foundation for glycemic control, as well as for training and education in diabetes management. We measured glycated hemoglobin (HbA1c) six months after discharge to assess disease management. In univariate analysis, fasting plasma C-peptide immunoreactivity (F-CPR) and pooled urine CPR (U-CPR) were significantly associated with HbA1c, in contrast to ΔCPR and C-peptide index (CPI). This association was strongly independent of most other patient variables. In exploratory factor analysis, five underlying factors, namely insulin resistance, aging, sex differences, insulin secretion, and glycemic control, represented patient characteristics. In particular, insulin secretion and resistance strongly influenced F-CPR, while insulin secretion affected U-CPR. In conclusion, the data indicate that among patients with type 2 diabetes mellitus, F-CPR and U-CPR may predict improved glycemic control six months after hospitalization.

  3. C-Peptide Level in Fasting Plasma and Pooled Urine Predicts HbA1c after Hospitalization in Patients with Type 2 Diabetes Mellitus

    PubMed Central

    Sonoda, Remi; Tanaka, Kentaro; Kikuchi, Takako; Onishi, Yukiko; Takao, Toshiko; Tahara, Tazu; Yoshida, Yoko; Suzawa, Naoki; Kawazu, Shoji; Iwamoto, Yasuhiko; Kushiyama, Akifumi

    2016-01-01

    In this study, we investigate how measures of insulin secretion and other clinical information affect long-term glycemic control in patients with type 2 diabetes mellitus. Between October 2012 and June 2014, we monitored 202 diabetes patients who were admitted to the hospital of Asahi Life Foundation for glycemic control, as well as for training and education in diabetes management. We measured glycated hemoglobin (HbA1c) six months after discharge to assess disease management. In univariate analysis, fasting plasma C-peptide immunoreactivity (F-CPR) and pooled urine CPR (U-CPR) were significantly associated with HbA1c, in contrast to ΔCPR and C-peptide index (CPI). This association was strongly independent of most other patient variables. In exploratory factor analysis, five underlying factors, namely insulin resistance, aging, sex differences, insulin secretion, and glycemic control, represented patient characteristics. In particular, insulin secretion and resistance strongly influenced F-CPR, while insulin secretion affected U-CPR. In conclusion, the data indicate that among patients with type 2 diabetes mellitus, F-CPR and U-CPR may predict improved glycemic control six months after hospitalization. PMID:26849676

  4. Approaches towards the automated interpretation and prediction of electrospray tandem mass spectra of non-peptidic combinatorial compounds.

    PubMed

    Klagkou, Katerina; Pullen, Frank; Harrison, Mark; Organ, Andy; Firth, Alistair; Langley, G John

    2003-01-01

    Combinatorial chemistry is widely used within the pharmaceutical industry as a means of rapid identification of potential drugs. With the growth of combinatorial libraries, mass spectrometry (MS) became the key analytical technique because of its speed of analysis, sensitivity, accuracy and ability to be coupled with other analytical techniques. In the majority of cases, electrospray mass spectrometry (ES-MS) has become the default ionisation technique. However, due to the absence of fragment ions in the resulting spectra, tandem mass spectrometry (MS/MS) is required to provide structural information for the identification of an unknown analyte. This work discusses the first steps of an investigation into the fragmentation pathways taking place in electrospray tandem mass spectrometry. The ultimate goal for this project is to set general fragmentation rules for non-peptidic, pharmaceutical, combinatorial compounds. As an aid, an artificial intelligence (AI) software package is used to facilitate interpretation of the spectra. This initial study has focused on determining the fragmentation rules for some classes of compound types that fit the remit as outlined above. Based on studies carried out on several combinatorial libraries of these compounds, it was established that different classes of drug molecules follow unique fragmentation pathways. In addition to these general observations, the specific ionisation processes and the fragmentation pathways involved in the electrospray mass spectra of these systems were explored. The ultimate goal will be to incorporate our findings into the computer program and allow identification of an unknown, non-peptidic compound following insertion of its ES-MS/MS spectrum into the AI package. The work herein demonstrates the potential benefit of such an approach in addressing the issue of high-throughput, automated MS/MS data interpretation.

  5. N-terminal pro b-type natriuretic peptide (NT-pro-BNP) –based score can predict in-hospital mortality in patients with heart failure

    PubMed Central

    Huang, Ya-Ting; Tseng, Yuan-Teng; Chu, Tung-Wei; Chen, John; Lai, Min-Yu; Tang, Woung-Ru; Shiao, Chih-Chung

    2016-01-01

    Serum N-terminal pro b-type natriuretic peptide (NT-pro-BNP) testing is recommended in the patients with heart failure (HF). We hypothesized that NT-pro-BNP, in combination with other clinical factors in terms of a novel NT-pro BNP-based score, may provide even better predictive power for in-hospital mortality among patients with HF. A retrospective study enrolled adult patients with hospitalization-requiring HF who fulfilled the predefined criteria during the period from January 2011 to December 2013. We proposed a novel scoring system consisting of several independent predictors including NT-pro-BNP for predicting in-hospital mortality, and then compared the prognosis-predictive power of the novel NT-pro BNP-based score with other prognosis-predictive scores. A total of 269 patients were enrolled in the current study. Factors such as “serum NT-pro-BNP level above 8100 mg/dl,” “age above 79 years,” “without taking angiotensin converting enzyme inhibitors/angiotensin receptor blocker,” “without taking beta-blocker,” “without taking loop diuretics,” “with mechanical ventilator support,” “with non-invasive ventilator support,” “with vasopressors use,” and “experience of cardio-pulmonary resuscitation” were found as independent predictors. A novel NT-pro BNP-based score composed of these risk factors was proposed with excellent predictability for in-hospital mortality. The proposed novel NT-pro BNP-based score was extremely effective in predicting in-hospital mortality in HF patients. PMID:27411951

  6. N-terminal pro b-type natriuretic peptide (NT-pro-BNP) -based score can predict in-hospital mortality in patients with heart failure.

    PubMed

    Huang, Ya-Ting; Tseng, Yuan-Teng; Chu, Tung-Wei; Chen, John; Lai, Min-Yu; Tang, Woung-Ru; Shiao, Chih-Chung

    2016-01-01

    Serum N-terminal pro b-type natriuretic peptide (NT-pro-BNP) testing is recommended in the patients with heart failure (HF). We hypothesized that NT-pro-BNP, in combination with other clinical factors in terms of a novel NT-pro BNP-based score, may provide even better predictive power for in-hospital mortality among patients with HF. A retrospective study enrolled adult patients with hospitalization-requiring HF who fulfilled the predefined criteria during the period from January 2011 to December 2013. We proposed a novel scoring system consisting of several independent predictors including NT-pro-BNP for predicting in-hospital mortality, and then compared the prognosis-predictive power of the novel NT-pro BNP-based score with other prognosis-predictive scores. A total of 269 patients were enrolled in the current study. Factors such as "serum NT-pro-BNP level above 8100 mg/dl," "age above 79 years," "without taking angiotensin converting enzyme inhibitors/angiotensin receptor blocker," "without taking beta-blocker," "without taking loop diuretics," "with mechanical ventilator support," "with non-invasive ventilator support," "with vasopressors use," and "experience of cardio-pulmonary resuscitation" were found as independent predictors. A novel NT-pro BNP-based score composed of these risk factors was proposed with excellent predictability for in-hospital mortality. The proposed novel NT-pro BNP-based score was extremely effective in predicting in-hospital mortality in HF patients. PMID:27411951

  7. A novel method to isolate protein N-terminal peptides from proteome samples using sulfydryl tagging and gold-nanoparticle-based depletion.

    PubMed

    Li, Lanting; Wu, Runqing; Yan, Guoquan; Gao, Mingxia; Deng, Chunhui; Zhang, Xiangmin

    2016-01-01

    A novel method to isolate global N-termini using sulfydryl tagging and gold-nanoparticle-based depletion (STagAu method) is presented. The N-terminal and lysine amino groups were first completely dimethylated at the protein level, after which the proteins were digested. The newly generated internal peptides were tagged with sulfydryl by Traut's reagent through digested N-terminal amines in yields of 96%. The resulting sulfydryl peptides were depleted through binding onto nano gold composite materials. The Au-S bond is stable and widely used in materials science. Nano gold composite materials showed nearly complete depletion of sulfydryl peptides. A set of the acetylated and dimethylated N-terminal peptides were analyzed by liquid chromatography-tandem mass spectrometry. This method was demonstrated to be an efficient N-terminus enrichment method because of the use of an effective derivatization reaction, in combination with robust and relative easy to implement Au-S coupling. We identified 632 N-terminal peptides from 386 proteins in a mouse liver sample. The STagAu approach presented is therefore a facile and efficient method for mass-spectrometry-based analysis of proteome N-termini or protease-generated cleavage products.

  8. Does the Current Minimum Validate (or Invalidate) Cycle Prediction Methods?

    NASA Technical Reports Server (NTRS)

    Hathaway, David H.

    2010-01-01

    This deep, extended solar minimum and the slow start to Cycle 24 strongly suggest that Cycle 24 will be a small cycle. A wide array of solar cycle prediction techniques have been applied to predicting the amplitude of Cycle 24 with widely different results. Current conditions and new observations indicate that some highly regarded techniques now appear to have doubtful utility. Geomagnetic precursors have been reliable in the past and can be tested with 12 cycles of data. Of the three primary geomagnetic precursors only one (the minimum level of geomagnetic activity) suggests a small cycle. The Sun's polar field strength has also been used to successfully predict the last three cycles. The current weak polar fields are indicative of a small cycle. For the first time, dynamo models have been used to predict the size of a solar cycle but with opposite predictions depending on the model and the data assimilation. However, new measurements of the surface meridional flow indicate that the flow was substantially faster on the approach to Cycle 24 minimum than at Cycle 23 minimum. In both dynamo predictions a faster meridional flow should have given a shorter cycle 23 with stronger polar fields. This suggests that these dynamo models are not yet ready for solar cycle prediction.

  9. Skill forecasting from different wind power ensemble prediction methods

    NASA Astrophysics Data System (ADS)

    Pinson, Pierre; Nielsen, Henrik Aa; Madsen, Henrik; Kariniotakis, George

    2007-07-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed.

  10. An empirical method for prediction of cheese yield.

    PubMed

    Melilli, C; Lynch, J M; Carpino, S; Barbano, D M; Licitra, G; Cappa, A

    2002-10-01

    Theoretical cheese yield can be estimated from the milk fat and casein or protein content of milk using classical formulae, such as the VanSlyke formula. These equations are reliable predictors of theoretical or actual yield based on accurately measured milk fat and casein content. Many cheese makers desire to base payment for milk to dairy farmers on the yield of cheese. In small factories, however, accurate measurement of fat and casein content of milk by either chemical methods or infrared milk analysis is too time consuming and expensive. Therefore, an empirical test to predict cheese yield was developed which uses simple equipment (i.e., clinical centrifuge, analytical balance, and forced air oven) to carry out a miniature cheese making, followed by a gravimetric measurement of dry weight yield. A linear regression of calculated theoretical versus dry weight yields for milks of known fat and casein content was calculated. A regression equation of y = 1.275x + 1.528, where y is theoretical yield and x is measured dry solids yield (r2 = 0.981), for Cheddar cheese was developed using milks with a range of theoretical yield from 7 to 11.8%. The standard deviation of the difference (SDD) between theoretical cheese yield and dry solids yield was 0.194 and the coefficient of variation (SDD/mean x 100) was 1.95% upon cross validation. For cheeses without a well-established theoretical cheese yield equation, the measured dry weight yields could be directly correlated to the observed yields in the factory; this would more accurately reflect the expected yield performance. Payments for milk based on these measurements would more accurately reflect quality and composition of the milk and the actual average recovery of fat and casein achieved under practical cheese making conditions. PMID:12416825

  11. Method for predicting cracking in waste glass canisters

    SciTech Connect

    Faletti, D.W.; Ethridge, L.J.

    1986-08-01

    A correlation has been developed that predicts the surface area created by cracking to within the accuracy of the existing data. The correlation is a simple linear equation; the surface area can be computed from a knowledge of the steady-state radial temperature difference and the radial temperature difference when the glass centerline temperature was at 500/sup 0/C. This correlation should be easy to use for waste glass canister applications since, in many cases, a two-dimensional heat transfer analysis can be used to determine the radial temperature differences. Although the correlation is useful for scoping purposes, there is a need to validate the correlation against additional canister cracking data, particularly in the case of stainless steel canisters. The use of Fiberfrax liners deserves serious consideration for use in stainless steel waste glass canisters. The amount of cracking is reduced because the liner eliminates the metal-glass interactions that produce significant stresses in the glass. Another less obvious, but very important, advantage of using Fiberfrax is that thermal shocking during decontamination and post-fill operations is reduced because of the liner's insulating capacity. More extensive studies to verify these results are recommended; canisters should be produced, under identical cooling conditions, that differ only in the use of liners. The data for any canister type are extremely sparse, and there is considerable uncertainty about the accuracy of the different methods that have been used to obtain surface area estimates. The comparative roles played by batch and continuous filling of the canisters also need to be clarified. There is a need for accurate thermal data to validate computer codes for determining the temperature histories of canisters. Suggestions for future cracking studies are given.

  12. Accelerating ab initio molecular dynamics simulations by linear prediction methods

    NASA Astrophysics Data System (ADS)

    Herr, Jonathan D.; Steele, Ryan P.

    2016-09-01

    Acceleration of ab initio molecular dynamics (AIMD) simulations can be reliably achieved by extrapolation of electronic data from previous timesteps. Existing techniques utilize polynomial least-squares regression to fit previous steps' Fock or density matrix elements. In this work, the recursive Burg 'linear prediction' technique is shown to be a viable alternative to polynomial regression, and the extrapolation-predicted Fock matrix elements were three orders of magnitude closer to converged elements. Accelerations of 1.8-3.4× were observed in test systems, and in all cases, linear prediction outperformed polynomial extrapolation. Importantly, these accelerations were achieved without reducing the MD integration timestep.

  13. Development of a novel efficient method to construct an adenovirus library displaying random peptides on the fiber knob

    PubMed Central

    Yamamoto, Yuki; Goto, Naoko; Miura, Kazuki; Narumi, Kenta; Ohnami, Shumpei; Uchida, Hiroaki; Miura, Yoshiaki; Yamamoto, Masato; Aoki, Kazunori

    2014-01-01

    Redirection of adenovirus vectors by engineering the capsid-coding region has shown limited success because proper targeting ligands are generally unknown. To overcome this limitation, we constructed an adenovirus library displaying random peptides on the fiber knob, and its screening led to successful selections of several particular targeted vectors. In the previous library construction method, the full length of an adenoviral genome was generated by a Cre-lox mediated in vitro recombination between a fiber-modified plasmid library and the enzyme-digested adenoviral DNA/terminal protein complex (DNA-TPC) before transfection to the producer cells. In this system, the procedures were complicated and time-consuming, and approximately 30% of the vectors in the library were defective with no displaying peptide. These may hinder further extensive exploration of cancer-targeting vectors. To resolve these problems, in this study, we developed a novel method with the transfection of a fiber-modified plasmid library and a fiberless adenoviral DNA-TPC in Cre-expressing 293 cells. The use of in-cell Cre recombination and fiberless adenovirus greatly simplified the library-making steps. The fiberless adenovirus was useful in suppressing the expansion of unnecessary adenovirus vectors. In addition, the complexity of the library was more than a 104 level in one well in a 6-well dish, which was 10-fold higher than that of the original method. The results demonstrated that this novel method is useful in producing a high quality live adenovirus library, which could facilitate the development of targeted adenovirus vectors for a variety of applications in medicine. PMID:24380399

  14. Development of a novel efficient method to construct an adenovirus library displaying random peptides on the fiber knob.

    PubMed

    Yamamoto, Yuki; Goto, Naoko; Miura, Kazuki; Narumi, Kenta; Ohnami, Shumpei; Uchida, Hiroaki; Miura, Yoshiaki; Yamamoto, Masato; Aoki, Kazunori

    2014-03-01

    Redirection of adenovirus vectors by engineering the capsid-coding region has shown limited success because proper targeting ligands are generally unknown. To overcome this limitation, we constructed an adenovirus library displaying random peptides on the fiber knob, and its screening led to successful selections of several particular targeted vectors. In the previous library construction method, the full length of an adenoviral genome was generated by a Cre-lox mediated in vitro recombination between a fiber-modified plasmid library and the enzyme-digested adenoviral DNA/terminal protein complex (DNA-TPC) before transfection to the producer cells. In this system, the procedures were complicated and time-consuming, and approximately 30% of the vectors in the library were defective with no displaying peptide. These may hinder further extensive exploration of cancer-targeting vectors. To resolve these problems, in this study, we developed a novel method with the transfection of a fiber-modified plasmid library and a fiberless adenoviral DNA-TPC in Cre-expressing 293 cells. The use of in-cell Cre recombination and fiberless adenovirus greatly simplified the library-making steps. The fiberless adenovirus was useful in suppressing the expansion of unnecessary adenovirus vectors. In addition, the complexity of the library was more than a 10(4) level in one well in a 6-well dish, which was 10-fold higher than that of the original method. The results demonstrated that this novel method is useful in producing a high quality live adenovirus library, which could facilitate the development of targeted adenovirus vectors for a variety of applications in medicine. PMID:24380399

  15. A physicochemical approach for predicting the effectiveness of peptide-based gene delivery systems for use in plasmid-based gene therapy.

    PubMed Central

    Duguid, J G; Li, C; Shi, M; Logan, M J; Alila, H; Rolland, A; Tomlinson, E; Sparrow, J T; Smith, L C

    1998-01-01

    Novel synthetic peptides, based on carrier peptide analogs (YKAKnWK) and an amphipathic peptide (GLFEALLELLESLWELLLEA), have been formulated with DNA plasmids to create peptide-based gene delivery systems. The carrier peptides are used to condense plasmids into nanoparticles with a hydrodynamic diameter (DH) ranging from 40 to 200 nm, which are sterically stable for over 100 h. Size and morphology of the carrier peptide/plasmid complex have been determined by photon correlation spectroscopy (PCS) and transmission electron microscopy (TEM), respectively. The amphipathic peptide is used as a pH-sensitive lytic agent to facilitate release of the plasmid from endosomes after endocytosis of the peptide/plasmid complex. Hemolysis assays have shown that the amphipathic peptide destabilizes lipid bilayers at low pH, mimicking the properties of viral fusogenic peptides. However, circular dichroism studies show that unlike the viral fusion peptides, this amphipathic peptide loses some of its alpha-helical structure at low pH in the presence of liposomes. The peptide-based gene delivery systems were tested for transfection efficiency in a variety of cell lines, including 14-day C2C12 mouse myotubes, using gene expression systems containing the beta-galactosidase reporter gene. Transfection data demonstrate a correlation between in vitro transfection efficiency and the combination of several physical properties of the peptide/plasmid complexes, including 1) DNA dose, 2) the zeta potential of the particle, 3) the requirement of both lytic and carrier peptides, and 4) the number of lysine residues associated with the carrier peptide. Transfection data on 14-day C2C12 myotubes utilizing the therapeutic human growth hormone gene formulated in an optimal peptide gene delivery system show an increase in gene expression over time, with a maximum in protein levels at 96 h (approximately 18 ng/ml). PMID:9635734

  16. The engine performance prediction by quasi-steady method

    NASA Astrophysics Data System (ADS)

    Ye, Ai-Yun; Zhang, Yanqin

    1995-01-01

    In this paper, the theory of Quasi-steady is applied to the calculations of turbochargers matching to the diesel engines and performance prediction. The engine performance prediction programs written in language C have been used for calculations of various turbocharged diesel engines. It has been confirmed by the comparisons with experimental data that the results of the calculation are reasonable, reliable and satisfied for the engineering applications.

  17. Comparison of Predictive Control Methods for High Consumption Industrial Furnace

    PubMed Central

    2013-01-01

    We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn. PMID:24319354

  18. Comparison of predictive control methods for high consumption industrial furnace.

    PubMed

    Stojanovski, Goran; Stankovski, Mile

    2013-01-01

    We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn.

  19. Qualitative and quantitative determination of peptides related to celiac disease in mixtures derived from different methods of simulated gastrointestinal digestion of wheat products.

    PubMed

    Prandi, Barbara; Faccini, Andrea; Tedeschi, Tullia; Cammerata, Alessandro; Sgrulletta, Daniela; D'Egidio, Maria Grazia; Galaverna, Gianni; Sforza, Stefano

    2014-07-01

    During wheat digestion, gluten-derived proteolytic resistant peptides are generated, some of them involved in celiac disease. In vitro digestion models able to mimic the peptides generated in the human gastrointestinal tract are extremely useful to assess the pathogenicity of wheat-derived products. In this paper, samples belonging to three different durum wheat varieties were taken at six different steps of the pasta production chain and two different digestion models present in the literature were assessed on the different samples: a more complex one using artificial fluids simulating the exact composition of digestive juices, and a simplified method based on a peptic-tryptic/chymotryptic treatment of wheat ethanolic extract. An extensive characterization of the peptides generated using two in vitro digestion models was performed through LC-MS/MS techniques and the two methods were compared in order to evaluate qualitative and quantitative differences and their possible implications for varietal screening. Strong differences in the type of peptides produced with the two methods were detected, indicating that the simplified method can still be used for a varietal screening but is not representative of the peptides really generated after physiological human digestion. Results indicate a clear necessity of physiologically accurate models for simulating human gastrointestinal digestion of wheat products.

  20. Combination of Urinary Sodium/Creatinine Ratio and Plasma Brain Natriuretic Peptide Level Predicts Successful Tolvaptan Therapy in Patients With Heart Failure and Volume Overload.

    PubMed

    Sato, Yuichi; Dohi, Kaoru; Watanabe, Kiyotaka; Tanimura, Muneyoshi; Takeuchi, Tetsushiro; Sugiura, Emiyo; Sugimoto, Tadafumi; Kumagai, Naoto; Ogura, Toru; Nakamori, Shiro; Fujimoto, Naoki; Yamada, Norikazu; Ito, Masaaki

    2016-01-01

    To evaluate the short-term clinical and hemodynamic effects of tolvaptan therapy and to identify predictors of the therapeutic outcomes, we retrospectively recruited 60 consecutive hospitalized heart failure (HF) patients (70 ± 11 years) with volume overload. The subjects were divided into two groups on the basis of the changes in HF symptom scores and hemodynamic status assessed by right heart catheterization after tolvaptan therapy (median: 7 days). The majority of patients were successfully treated (group 1). However, 22% of patients (group 2) were unsuccessfully treated, in whom 1) the HF symptom score worsened or 2) there was a stationary HF symptom score ≥ 6 points, and mean PCWP > 18 mmHg and mean RAP > 10 mmHg, after tolvaptan therapy. HF symptom scores, hemodynamic parameters, and plasma brain natriuretic peptide (BNP) level improved in group 1, but all of these parameters remained unchanged in group 2. Lower urine sodium/creatinine ratio (UNa/UCr) and higher BNP level at baseline were independently associated with unsuccessful tolvaptan therapy, and UNa/UCr best predicts unsuccessful tolvaptan therapy with a cut-off value of 46.5 mEq/g·Cr (AUC 0.847, 95% CI: 0.718-0.976, sensitivity 77%, specificity 81%, P < 0.01). Double-positive results of UNa/UCr < 46.5 mEq/g·Cr and plasma BNP level > 778 pg/mL predicted unsuccessful tolvaptan therapy with high diagnostic accuracy (sensitivity 54%, specificity 100%, positive predictive value 100%, negative predictive value 89%, and accuracy 90%). In summary, short-term tolvaptan therapy ameliorated HF symptoms and provided hemodynamic improvement in the majority of patients, and UNa/UCr and BNP level strongly predicted the therapeutic outcomes. PMID:26973271

  1. Screening Method for the Discovery of Potential Bioactive Cysteine-Containing Peptides Using 3D Mass Mapping

    NASA Astrophysics Data System (ADS)

    van Oosten, Luuk N.; Pieterse, Mervin; Pinkse, Martijn W. H.; Verhaert, Peter D. E. M.

    2015-12-01

    Animal venoms and toxins are a valuable source of bioactive peptides with pharmacologic relevance as potential drug leads. A large subset of biologically active peptides discovered up till now contain disulfide bridges that enhance stability and activity. To discover new members of this class of peptides, we developed a workflow screening specifically for those peptides that contain inter- and intra-molecular disulfide bonds by means of three-dimensional (3D) mass mapping. Two intrinsic properties of the sulfur atom, (1) its relatively large negative mass defect, and (2) its isotopic composition, allow for differentiation between cysteine-containing peptides and peptides lacking sulfur. High sulfur content in a peptide decreases the normalized nominal mass defect (NMD) and increases the normalized isotopic shift (NIS). Hence in a 3D plot of mass, NIS, and NMD, peptides with sulfur appear in this plot with a distinct spatial localization compared with peptides that lack sulfur. In this study we investigated the skin secretion of two frog species; Odorrana schmackeri and Bombina variegata. Peptides from the crude skin secretions were separated by nanoflow LC, and of all eluting peptides high resolution zoom scans were acquired in order to accurately determine both monoisotopic mass and average mass. Both the NMD and the NIS were calculated from the experimental data using an in-house developed MATLAB script. Candidate peptides exhibiting a low NMD and high NIS values were selected for targeted de novo sequencing, and this resulted in the identification of several novel inter- and intra-molecular disulfide bond containing peptides.

  2. Comparison of several methods for predicting separation in a compressible turbulent boundary layer

    NASA Technical Reports Server (NTRS)

    Gerhart, P. M.; Bober, L. J.

    1974-01-01

    Several methods for predicting the separation point for a compressible turbulent boundary layer were applied to the flow over a bump on a wind-tunnel wall. Measured pressure distributions were used as input. Two integral boundary-layer methods, three finite-difference boundary-layer methods, and three simple methods were applied at five free-stream Mach numbers ranging from 0.354 to 0.7325. Each of the boundary-layer methods failed to explicitly predict separation. However, by relaxing the theoretical separation criteria, several boundary-layer methods were made to yield reasonable separation predictions, but none of the methods accurately predicted the important boundary-layer parameters at separation. Only one of the simple methods consistently predicted separation with reasonable accuracy in a manner consistent with the theory. The other methods either indicated several possible separation locations or only sometimes predicted separation.

  3. A modern approach for epitope prediction: identification of foot-and-mouth disease virus peptides binding bovine leukocyte antigen (BoLA) class I molecules

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Major histocompatibility complex (MHC) class I molecules regulate adaptive immune responses through the presentation of antigenic peptides to CD8positive T-cells. Polymorphisms in the peptide binding region of class I molecules determine peptide binding affinity and stability during antigen presenta...

  4. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

    Hasselman, Timothy K.; Chrostowski, Jon D.

    1991-01-01

    Modeling uncertainty is defined in terms of the difference between predicted and measured eigenvalues and eigenvectors. Data compiled from 22 sets of analysis/test results was used to create statistical databases for large truss-type space structures and both pretest and posttest models of conventional satellite-type space structures. Modeling uncertainty is propagated through the model to produce intervals of uncertainty on frequency response functions, both amplitude and phase. This methodology was used successfully to evaluate the predictive accuracy of several structures, including the NASA CSI Evolutionary Structure tested at Langley Research Center. Test measurements for this structure were within + one-sigma intervals of predicted accuracy for the most part, demonstrating the validity of the methodology and computer code.

  5. Easy and Rapid Binding Assay for Functional Analysis of Disulfide-Containing Peptides by a Pull-Down Method Using a Puromycin-Linker and a Cell-Free Translation System

    PubMed Central

    Tanemura, Yutaro; Mochizuki, Yuki; Kumachi, Shigefumi; Nemoto, Naoto

    2015-01-01

    Constrained peptides are an attractive class as affinity reagents or drug leads owing to their excellent binding properties. Many kinds of these peptides, such as cyclic peptides containing disulfide bridges, are found in nature or designed artificially by directed evolution. However, confirming the binding properties of the disulfide-rich peptides can be generally difficult, because of oxidative folding problems in the preparation steps. Therefore, a method for evaluating the binding properties of such peptides rapidly and easily is required. Here, we report an easy and rapid method for preparing biotin-attached peptides containing disulfide bridges or a chemical cross-linker using a cell-free translation system and a puromycin-linker, which is applicable to pull-down assays for protein (or peptide) molecular interaction analysis. PMID:25738808

  6. Alignment-Free Methods for the Detection and Specificity Prediction of Adenylation Domains.

    PubMed

    Agüero-Chapin, Guillermin; Pérez-Machado, Gisselle; Sánchez-Rodríguez, Aminael; Santos, Miguel Machado; Antunes, Agostinho

    2016-01-01

    Identifying adenylation domains (A-domains) and their substrate specificity can aid the detection of nonribosomal peptide synthetases (NRPS) at genome/proteome level and allow inferring the structure of oligopeptides with relevant biological activities. However, that is challenging task due to the high sequence diversity of A-domains (~10-40 % of amino acid identity) and their selectivity for 50 different natural/unnatural amino acids. Altogether these characteristics make their detection and the prediction of their substrate specificity a real challenge when using traditional sequence alignment methods, e.g., BLAST searches. In this chapter we describe two workflows based on alignment-free methods intended for the identification and substrate specificity prediction of A-domains. To identify A-domains we introduce a graphical-numerical method, implemented in TI2BioP version 2.0 (topological indices to biopolymers), which in a first step uses protein four-color maps to represent A-domains. In a second step, simple topological indices (TIs), called spectral moments, are derived from the graphical representations of known A-domains (positive dataset) and of unrelated but well-characterized sequences (negative set). Spectral moments are then used as input predictors for statistical classification techniques to build alignment-free models. Finally, the resulting alignment-free models can be used to explore entire proteomes for unannotated A-domains. In addition, this graphical-numerical methodology works as a sequence-search method that can be ensemble with homology-based tools to deeply explore the A-domain signature and cope with the diversity of this class (Aguero-Chapin et al., PLoS One 8(7):e65926, 2013). The second workflow for the prediction of A-domain's substrate specificity is based on alignment-free models constructed by transductive support vector machines (TSVMs) that incorporate information of uncharacterized A-domains. The construction of the models was

  7. Alignment-Free Methods for the Detection and Specificity Prediction of Adenylation Domains.

    PubMed

    Agüero-Chapin, Guillermin; Pérez-Machado, Gisselle; Sánchez-Rodríguez, Aminael; Santos, Miguel Machado; Antunes, Agostinho

    2016-01-01

    Identifying adenylation domains (A-domains) and their substrate specificity can aid the detection of nonribosomal peptide synthetases (NRPS) at genome/proteome level and allow inferring the structure of oligopeptides with relevant biological activities. However, that is challenging task due to the high sequence diversity of A-domains (~10-40 % of amino acid identity) and their selectivity for 50 different natural/unnatural amino acids. Altogether these characteristics make their detection and the prediction of their substrate specificity a real challenge when using traditional sequence alignment methods, e.g., BLAST searches. In this chapter we describe two workflows based on alignment-free methods intended for the identification and substrate specificity prediction of A-domains. To identify A-domains we introduce a graphical-numerical method, implemented in TI2BioP version 2.0 (topological indices to biopolymers), which in a first step uses protein four-color maps to represent A-domains. In a second step, simple topological indices (TIs), called spectral moments, are derived from the graphical representations of known A-domains (positive dataset) and of unrelated but well-characterized sequences (negative set). Spectral moments are then used as input predictors for statistical classification techniques to build alignment-free models. Finally, the resulting alignment-free models can be used to explore entire proteomes for unannotated A-domains. In addition, this graphical-numerical methodology works as a sequence-search method that can be ensemble with homology-based tools to deeply explore the A-domain signature and cope with the diversity of this class (Aguero-Chapin et al., PLoS One 8(7):e65926, 2013). The second workflow for the prediction of A-domain's substrate specificity is based on alignment-free models constructed by transductive support vector machines (TSVMs) that incorporate information of uncharacterized A-domains. The construction of the models was

  8. Gastrointestinal Endogenous Proteins as a Source of Bioactive Peptides - An In Silico Study

    PubMed Central

    Dave, Lakshmi A.; Montoya, Carlos A.; Rutherfurd, Shane M.; Moughan, Paul J.

    2014-01-01

    Dietary proteins are known to contain bioactive peptides that are released during digestion. Endogenous proteins secreted into the gastrointestinal tract represent a quantitatively greater supply of protein to the gut lumen than those of dietary origin. Many of these endogenous proteins are digested in the gastrointestinal tract but the possibility that these are also a source of bioactive peptides has not been considered. An in silico prediction method was used to test if bioactive peptides could be derived from the gastrointestinal digestion of gut endogenous proteins. Twenty six gut endogenous proteins and seven dietary proteins were evaluated. The peptides present after gastric and intestinal digestion were predicted based on the amino acid sequence of the proteins and the known specificities of the major gastrointestinal proteases. The predicted resultant peptides possessing amino acid sequences identical to those of known bioactive peptides were identified. After gastrointestinal digestion (based on the in silico simulation), the total number of bioactive peptides predicted to be released ranged from 1 (gliadin) to 55 (myosin) for the selected dietary proteins and from 1 (secretin) to 39 (mucin-5AC) for the selected gut endogenous proteins. Within the intact proteins and after simulated gastrointestinal digestion, angiotensin converting enzyme (ACE)-inhibitory peptide sequences were the most frequently observed in both the dietary and endogenous proteins. Among the dietary proteins, after in silico simulated gastrointestinal digestion, myosin was found to have the highest number of ACE-inhibitory peptide sequences (49 peptides), while for the gut endogenous proteins, mucin-5AC had the greatest number of ACE-inhibitory peptide sequences (38 peptides). Gut endogenous proteins may be an important source of bioactive peptides in the gut particularly since gut endogenous proteins represent a quantitatively large and consistent source of protein. PMID:24901416

  9. What Predicts Method Effects in Child Behavior Ratings

    ERIC Educational Resources Information Center

    Low, Justin A.; Keith, Timothy Z.; Jensen, Megan

    2015-01-01

    The purpose of this research was to determine whether child, parent, and teacher characteristics such as sex, socioeconomic status (SES), parental depressive symptoms, the number of years of teaching experience, number of children in the classroom, and teachers' disciplinary self-efficacy predict deviations from maternal ratings in a…

  10. Methods and apparatus for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOEpatents

    Robertson, Eric P; Christiansen, Richard L.

    2007-05-29

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  11. Methods for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOEpatents

    Robertson, Eric P; Christiansen, Richard L.

    2007-10-23

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  12. A Simple Method for Predicting Transmembrane Proteins Based on Wavelet Transform

    PubMed Central

    Yu, Bin; Zhang, Yan

    2013-01-01

    The increasing protein sequences from the genome project require theoretical methods to predict transmembrane helical segments (TMHs). So far, several prediction methods have been reported, but there are some deficiencies in prediction accuracy and adaptability in these methods. In this paper, a method based on discrete wavelet transform (DWT) has been developed to predict the number and location of TMHs in membrane proteins. PDB coded as 1KQG is chosen as an example to describe the prediction process by this method. 80 proteins with known 3D structure from Mptopo database are chosen at random as data sets (including 325 TMHs) and 80 sequences are divided into 13 groups according to their function and type. TMHs prediction is carried out for each group of membrane protein sequences and obtain satisfactory result. To verify the feasibility of this method, 80 membrane protein sequences are treated as test sets, 308 TMHs can be predicted and the prediction accuracy is 96.3%. Compared with the main prediction results of seven popular prediction methods, the obtained results indicate that the proposed method in this paper has higher prediction accuracy. PMID:23289014

  13. DO TIE LABORATORY BASED ASSESSMENT METHODS REALLY PREDICT FIELD EFFECTS?

    EPA Science Inventory

    Sediment Toxicity Identification and Evaluation (TIE) methods have been developed for both porewaters and whole sediments. These relatively simple laboratory methods are designed to identify specific toxicants or classes of toxicants in sediments; however, the question of whethe...

  14. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    EPA Science Inventory

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  15. Correlation of Puma airloads: Evaluation of CFD prediction methods

    NASA Technical Reports Server (NTRS)

    Strawn, Roger C.; Desopper, Andre; Miller, Judith; Jones, Alan

    1989-01-01

    A cooperative program was undertaken by research organizations in England, France, Australia and the U.S. to study the capabilities of computational fluid dynamics codes (CFD) to predict the aerodynamic loading on helicopter rotor blades. The program goal is to compare predictions with experimental data for flight tests of a research Puma helicopter with rectangular and swept tip blades. Two topics are studied. First, computed results from three CFD codes are compared for flight test cases where all three codes use the same partial inflow-angle boundary conditions. Second, one of the CFD codes (FPR) is iteratively coupled with the CAMRAD/JA helicopter performance code. These results are compared with experimental data and with an uncoupled CAMRAD/JA solution. The influence of flow field unsteadiness is found to play an important role in the blade aerodynamics. Alternate boundary conditions are suggested in order to properly model this unsteadiness in the CFD codes.

  16. Correlation of Puma airfoils - Evaluation of CFD prediction methods

    NASA Technical Reports Server (NTRS)

    Strawn, Roger C.; Desopper, Andre; Miller, Judith; Jones, Alan

    1989-01-01

    A cooperative program was undertaken by research organizations in England, France, Australia and the U.S. to study the capabilities of computational fluid dynamics codes (CFD) to predict the aerodynamic loading on helicopter rotor blades. The program goal is to compare predictions with experimental data for flight tests of a research Puma helicopter with rectangular and swept tip blades. Two topics are studied. First, computed results from three CFD codes are compared for flight test cases where all three codes use the same partial inflow-angle boundary conditions. Second, one of the CFD codes (FPR) is iteratively coupled with the CAMRAD/JA heilcopter performance code. These results are compared with experimental data and with an uncoupled CAMRAD/JA solution. The influence of flow field unsteadiness is found to play an important role in the blade aerodynamics. Alternate boundary conditions are suggested in order to properly model this unsteadiness in the CFD codes.

  17. Pattern recognition methods for protein functional site prediction.

    PubMed

    Yang, Zheng Rong; Wang, Lipo; Young, Natasha; Trudgian, Dave; Chou, Kuo-Chen

    2005-10-01

    Protein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area. PMID:16248799

  18. Prediction of Protein-DNA binding by Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Deng, Yuefan; Eisenberg, Moises; Korobka, Alex

    1997-08-01

    We present an analysis and prediction of protein-DNA binding specificity based on the hydrogen bonding between DNA, protein, and auxillary clusters of water molecules. Zif268, glucocorticoid receptor, λ-repressor mutant, HIN-recombinase, and tramtrack protein-DNA complexes are studied. Hydrogen bonds are approximated by the Lennard-Jones potential with a cutoff distance between the hydrogen and the acceptor atoms set to 3.2 Åand an angular component based on a dipole-dipole interaction. We use a three-stage docking algorithm: geometric hashing that matches pairs of hydrogen bonding sites; (2) least-squares minimization of pairwise distances to filter out insignificant matches; and (3) Monte Carlo stochastic search to minimize the energy of the system. More information can be obtained from our first paper on this subject [Y.Deng et all, J.Computational Chemistry (1995)]. Results show that the biologically correct base pair is selected preferentially when there are two or more strong hydrogen bonds (with LJ potential lower than -0.20) that bind it to the protein. Predicted sequences are less stable in the case of weaker bonding sites. In general the inclusion of water bridges does increase the number of base pairs for which correct specificity is predicted.

  19. Antimicrobial peptides

    PubMed Central

    2014-01-01

    With increasing antibiotics resistance, there is an urgent need for novel infection therapeutics. Since antimicrobial peptides provide opportunities for this, identification and optimization of such peptides have attracted much interest during recent years. Here, a brief overview of antimicrobial peptides is provided, with focus placed on how selected hydrophobic modifications of antimicrobial peptides can be employed to combat also more demanding pathogens, including multi-resistant strains, without conferring unacceptable toxicity. PMID:24758244

  20. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    NASA Astrophysics Data System (ADS)

    Cho, Jaepil; Shin, Chang-Min; Choi, Hwan-Kyu; Kim, Kyong-Hyeon; Choi, Ji-Yong

    2016-10-01

    The APEC Climate Center (APCC) produces climate prediction information utilizing a multi-climate model ensemble (MME) technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1) the Simple Bias Correction (SBC) method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2) the Moving Window Regression (MWR) method, which indirectly utilizes dynamic prediction data; (3) the Climate Index Regression (CIR) method, which predominantly uses observation-based climate indices; and (4) the Integrated Time Regression (ITR) method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT) model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  1. Simple numerical method for predicting steady compressible flows

    NASA Technical Reports Server (NTRS)

    Vonlavante, Ernst; Nelson, N. Duane

    1986-01-01

    A numerical method for solving the isenthalpic form of the governing equations for compressible viscous and inviscid flows was developed. The method was based on the concept of flux vector splitting in its implicit form. The method was tested on several demanding inviscid and viscous configurations. Two different forms of the implicit operator were investigated. The time marching to steady state was accelerated by the implementation of the multigrid procedure. Its various forms very effectively increased the rate of convergence of the present scheme. High quality steady state results were obtained in most of the test cases; these required only short computational times due to the relative efficiency of the basic method.

  2. Underwater Sound Propagation Modeling Methods for Predicting Marine Animal Exposure.

    PubMed

    Hamm, Craig A; McCammon, Diana F; Taillefer, Martin L

    2016-01-01

    The offshore exploration and production (E&P) industry requires comprehensive and accurate ocean acoustic models for determining the exposure of marine life to the high levels of sound used in seismic surveys and other E&P activities. This paper reviews the types of acoustic models most useful for predicting the propagation of undersea noise sources and describes current exposure models. The severe problems caused by model sensitivity to the uncertainty in the environment are highlighted to support the conclusion that it is vital that risk assessments include transmission loss estimates with statistical measures of confidence.

  3. Method of predicting a change in an economy

    DOEpatents

    Pryor, Richard J; Basu, Nipa

    2006-01-10

    An economy whose activity is to be predicted comprises a plurality of decision makers. Decision makers include, for example, households, government, industry, and banks. The decision makers are represented by agents, where an agent can represent one or more decision makers. Each agent has decision rules that determine the agent's actions. Each agent can affect the economy by affecting variable conditions characteristic of the economy or the internal state of other agents. Agents can communicate actions through messages. On a multiprocessor computer, the agents can be assigned to processing elements.

  4. Underwater Sound Propagation Modeling Methods for Predicting Marine Animal Exposure.

    PubMed

    Hamm, Craig A; McCammon, Diana F; Taillefer, Martin L

    2016-01-01

    The offshore exploration and production (E&P) industry requires comprehensive and accurate ocean acoustic models for determining the exposure of marine life to the high levels of sound used in seismic surveys and other E&P activities. This paper reviews the types of acoustic models most useful for predicting the propagation of undersea noise sources and describes current exposure models. The severe problems caused by model sensitivity to the uncertainty in the environment are highlighted to support the conclusion that it is vital that risk assessments include transmission loss estimates with statistical measures of confidence. PMID:26610982

  5. Test battery with the human cell line activation test, direct peptide reactivity assay and DEREK based on a 139 chemical data set for predicting skin sensitizing potential and potency of chemicals.

    PubMed

    Takenouchi, Osamu; Fukui, Shiho; Okamoto, Kenji; Kurotani, Satoru; Imai, Noriyasu; Fujishiro, Miyuki; Kyotani, Daiki; Kato, Yoshinao; Kasahara, Toshihiko; Fujita, Masaharu; Toyoda, Akemi; Sekiya, Daisuke; Watanabe, Shinichi; Seto, Hirokazu; Hirota, Morihiko; Ashikaga, Takao; Miyazawa, Masaaki

    2015-11-01

    To develop a testing strategy incorporating the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and DEREK, we created an expanded data set of 139 chemicals (102 sensitizers and 37 non-sensitizers) by combining the existing data set of 101 chemicals through the collaborative projects of Japan Cosmetic Industry Association. Of the additional 38 chemicals, 15 chemicals with relatively low water solubility (log Kow > 3.5) were selected to clarify the limitation of testing strategies regarding the lipophilic chemicals. Predictivities of the h-CLAT, DPRA and DEREK, and the combinations thereof were evaluated by comparison to results of the local lymph node assay. When evaluating 139 chemicals using combinations of three methods based on integrated testing strategy (ITS) concept (ITS-based test battery) and a sequential testing strategy (STS) weighing the predictive performance of the h-CLAT and DPRA, overall similar predictivities were found as before on the 101 chemical data set. An analysis of false negative chemicals suggested a major limitation of our strategies was the testing of low water-soluble chemicals. When excluded the negative results for chemicals with log Kow > 3.5, the sensitivity and accuracy of ITS improved to 97% (91 of 94 chemicals) and 89% (114 of 128). Likewise, the sensitivity and accuracy of STS to 98% (92 of 94) and 85% (111 of 129). Moreover, the ITS and STS also showed good correlation with local lymph node assay on three potency classifications, yielding accuracies of 74% (ITS) and 73% (STS). Thus, the inclusion of log Kow in analysis could give both strategies a higher predictive performance. PMID:25820183

  6. Test battery with the human cell line activation test, direct peptide reactivity assay and DEREK based on a 139 chemical data set for predicting skin sensitizing potential and potency of chemicals.

    PubMed

    Takenouchi, Osamu; Fukui, Shiho; Okamoto, Kenji; Kurotani, Satoru; Imai, Noriyasu; Fujishiro, Miyuki; Kyotani, Daiki; Kato, Yoshinao; Kasahara, Toshihiko; Fujita, Masaharu; Toyoda, Akemi; Sekiya, Daisuke; Watanabe, Shinichi; Seto, Hirokazu; Hirota, Morihiko; Ashikaga, Takao; Miyazawa, Masaaki

    2015-11-01

    To develop a testing strategy incorporating the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and DEREK, we created an expanded data set of 139 chemicals (102 sensitizers and 37 non-sensitizers) by combining the existing data set of 101 chemicals through the collaborative projects of Japan Cosmetic Industry Association. Of the additional 38 chemicals, 15 chemicals with relatively low water solubility (log Kow > 3.5) were selected to clarify the limitation of testing strategies regarding the lipophilic chemicals. Predictivities of the h-CLAT, DPRA and DEREK, and the combinations thereof were evaluated by comparison to results of the local lymph node assay. When evaluating 139 chemicals using combinations of three methods based on integrated testing strategy (ITS) concept (ITS-based test battery) and a sequential testing strategy (STS) weighing the predictive performance of the h-CLAT and DPRA, overall similar predictivities were found as before on the 101 chemical data set. An analysis of false negative chemicals suggested a major limitation of our strategies was the testing of low water-soluble chemicals. When excluded the negative results for chemicals with log Kow > 3.5, the sensitivity and accuracy of ITS improved to 97% (91 of 94 chemicals) and 89% (114 of 128). Likewise, the sensitivity and accuracy of STS to 98% (92 of 94) and 85% (111 of 129). Moreover, the ITS and STS also showed good correlation with local lymph node assay on three potency classifications, yielding accuracies of 74% (ITS) and 73% (STS). Thus, the inclusion of log Kow in analysis could give both strategies a higher predictive performance.

  7. A Method of Analyzing Tests Using the Teacher's Predictions.

    ERIC Educational Resources Information Center

    Zehavi, Nurit; Bruckheimer, Maxim

    1981-01-01

    A method of evaluation that permits some penetration into the teaching/learning process that connects the student, teacher, and program is described. The conclusions reached by this method can be applied to improving teaching strategies, inservice training, curriculum development, and evaluation. (MP)

  8. Predicting Academic Library Circulations: A Forecasting Methods Competition.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.; Forys, John W., Jr.

    Based on sample data representing five years of monthly circulation totals from 50 academic libraries in Illinois, Iowa, Michigan, Minnesota, Missouri, and Ohio, a study was conducted to determine the most efficient smoothing forecasting methods for academic libraries. Smoothing forecasting methods were chosen because they have been characterized…

  9. Verifying a computational method for predicting extreme ground motion

    USGS Publications Warehouse

    Harris, R.A.; Barall, M.; Andrews, D.J.; Duan, B.; Ma, S.; Dunham, E.M.; Gabriel, A.-A.; Kaneko, Y.; Kase, Y.; Aagaard, B.T.; Oglesby, D.D.; Ampuero, J.-P.; Hanks, T.C.; Abrahamson, N.

    2011-01-01

    In situations where seismological data is rare or nonexistent, computer simulations may be used to predict ground motions caused by future earthquakes. This is particularly practical in the case of extreme ground motions, where engineers of special buildings may need to design for an event that has not been historically observed but which may occur in the far-distant future. Once the simulations have been performed, however, they still need to be tested. The SCEC-USGS dynamic rupture code verification exercise provides a testing mechanism for simulations that involve spontaneous earthquake rupture. We have performed this examination for the specific computer code that was used to predict maximum possible ground motion near Yucca Mountain. Our SCEC-USGS group exercises have demonstrated that the specific computer code that was used for the Yucca Mountain simulations produces similar results to those produced by other computer codes when tackling the same science problem. We also found that the 3D ground motion simulations produced smaller ground motions than the 2D simulations.

  10. A Nonlinear Reduced Order Method for Prediction of Acoustic Fatigue

    NASA Technical Reports Server (NTRS)

    Przekop, Adam; Rizzi, Stephen A.

    2006-01-01

    The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing geometrically nonlinear random vibrations. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

  11. An Improved Numerical Integration Method for Springback Predictions

    NASA Astrophysics Data System (ADS)

    Ibrahim, R.; Smith, L. M.; Golovashchenko, Sergey F.

    2011-08-01

    In this investigation, the focus is on the springback of steel sheets in V-die air bending. A full replication to a numerical integration algorithm presented rigorously in [1] to predict the springback in air bending was performed and confirmed successfully. Algorithm alteration and extensions were proposed here. The altered approach used in solving the moment equation numerically resulted in springback values much closer to the trend presented by the experimental data, Although investigation here extended to use a more realistic work-hardening model, the differences in the springback values obtained by both hardening models were almost negligible. The algorithm was extended to be applied on thin sheets down to 0.8 mm. Results show that this extension is possible as verified by FEA and other published experiments on TRIP steel sheets.

  12. Method for Predicting and Optimizing System Parameters for Electrospinning System

    NASA Technical Reports Server (NTRS)

    Wincheski, Russell A. (Inventor)

    2011-01-01

    An electrospinning system using a spinneret and a counter electrode is first operated for a fixed amount of time at known system and operational parameters to generate a fiber mat having a measured fiber mat width associated therewith. Next, acceleration of the fiberizable material at the spinneret is modeled to determine values of mass, drag, and surface tension associated with the fiberizable material at the spinneret output. The model is then applied in an inversion process to generate predicted values of an electric charge at the spinneret output and an electric field between the spinneret and electrode required to fabricate a selected fiber mat design. The electric charge and electric field are indicative of design values for system and operational parameters needed to fabricate the selected fiber mat design.

  13. Small Engine Technology (Set) Task 8 Aeroelastic Prediction Methods

    NASA Technical Reports Server (NTRS)

    Eick, Chris D.; Liu, Jong-Shang

    1998-01-01

    AlliedSignal Engines, in cooperation with NASA LeRC, completed an evaluation of recently developed aeroelastic computer codes using test cases from the AlliedSignal Engines fan blisk database. Test data for this task includes strain gage, light probe, performance, and steady-state pressure information obtained for conditions where synchronous or flutter vibratory conditions were found to occur. Aeroelastic codes evaluated include the quasi 3-D UNSFLO (developed at MIT and modified to include blade motion by AlliedSignal), the 2-D FREPS (developed by NASA LeRC), and the 3-D TURBO-AE (under development at NASA LeRC). Six test cases each where flutter and synchronous vibrations were found to occur were used for evaluation of UNSFLO and FREPS. In addition, one of the flutter cases was evaluated using TURBO-AE. The UNSFLO flutter evaluations were completed for 75 percent radial span and provided good agreement with the experimental test data. Synchronous evaluations were completed for UNSFLO but further enhancement needs to be added to the code before the unsteady pressures can be used to predict forced response vibratory stresses. The FREPS evaluations were hindered as the steady flow solver (SFLOW) was unable to converge to a solution for the transonic flow conditions in the fan blisk. This situation resulted in all FREPS test cases being attempted but no results were obtained during the present program. Currently, AlliedSignal is evaluating integrating FREPS with our existing steady flow solvers to bypass the SFLOW difficulties. ne TURBO-AE steady flow solution provided an excellent match with the AlliedSignal Engines calibrated DAWES 3-D viscous solver. Finally, the TURBO-AE unsteady analyses also matched experimental observations by predicting flutter for the single test case evaluated.

  14. The interface of hypothalamic-pituitary-adrenocortical axis and circulating brain natriuretic peptide in prediction of cardiopulmonary performance during physical stress.

    PubMed

    Popovic, Dejana; Popovic, Bojana; Plecas-Solarovic, Bosiljka; Pešić, Vesna; Markovic, Vidan; Stojiljkovic, Stanimir; Vukcevic, Vladan; Petrovic, Ivana; Banovic, Marko; Petrovic, Milan; Vujisic-Tesic, Bosiljka; Ostojic, Miodrag C; Ristic, Arsen; Damjanovic, Svetozar S

    2013-09-01

    Brain natriuretic peptide (NT-pro-BNP) was implicated in the regulation of hypothalamic-pituitary-adrenocortical (HPA) responses to psychological stressors. However, HPA axis activation in different physical stress models and its interface with NT-pro-BNP in the prediction of cardiopulmonary performance is unclear. Cardiopulmonary test on a treadmill was used to assess cardiopulmonary parameters in 16 elite male wrestlers (W), 21 water polo player (WP) and 20 sedentary age-matched subjects (C). Plasma levels of NT-pro-BNP, cortisol and adrenocorticotropic hormone (ACTH) were measured using immunoassay sandwich technique, radioimmunoassay and radioimmunometric techniques, respectively, 10min before test (1), at beginning (2), at maximal effort (3), at 3rdmin of recovery (4). In all groups, NT-pro-BNP decreased between 1 and 2; increased from 2 to 3; and remained unchanged until 4. ACTH increased from 1 to 4, whereas cortisol increased from 1 to 3 and stayed elevated at 4. In all groups together, ΔNT-pro-BNP2/1 predicted peak oxygen consumption (B=37.40, r=0.38, p=0.007); cortisol at 3 predicted heart rate increase between 2 and 3 (r=-0.38,B=-0.06, p=0.005); cortisol at 2 predicted peak carbon-dioxide output (B=2.27, r=0.35, p<0.001); ΔACTH3/2 predicted peak ventilatory equivalent for carbon-dioxide (B=0.03, r=0.33, p=0.003). The relation of cortisol at 1 with NT-pro-BNP at 1 and 3 was demonstrated using logistic function in all the participants together (for 1/cortisol at 1 B=63.40, 58.52; r=0.41, 0.34; p=0.003, 0.013, respectively). ΔNT-pro-BNP2/1 linearly correlated with ΔACTH4/3 in WP and W (r=-0.45, -0.48; p=0.04, 0.04, respectively). These results demonstrate for the first time that HPA axis and NT-pro-BNP interface in physical stress probably contribute to integrative regulation of cardiopulmonary performance.

  15. Antihypertensive peptides from food proteins.

    PubMed

    Aluko, Rotimi E

    2015-01-01

    Bioactive peptides are encrypted within the primary structure of food proteins where they remain inactive until released by enzymatic hydrolysis. Once released from the parent protein, certain peptides have the ability to modulate the renin-angiotensin system (RAS) because they decrease activities of renin or angiotensin-converting enzyme (ACE), the two main enzymes that regulate mammalian blood pressure. These antihypertensive peptides can also enhance the endothelial nitric oxide synthase (eNOS) pathway to increase nitric oxide (NO) levels within vascular walls and promote vasodilation. The peptides can block the interactions between angiotensin II (vasoconstrictor) and angiotensin receptors, which can contribute to reduced blood pressure. This review focuses on the methods that are involved in antihypertensive peptide production from food sources, including fractionation protocols that are used to enrich bioactive peptide content and enhance peptide activity. It also discusses mechanisms that are believed to be involved in the antihypertensive activity of these peptides.

  16. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    NASA Astrophysics Data System (ADS)

    Shibata, H.; Watanabe, Y.; Suzuki, K.

    2016-05-01

    In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

  17. Reduced Order Methods for Prediction of Thermal-Acoustic Fatigue

    NASA Technical Reports Server (NTRS)

    Przekop, A.; Rizzi, S. A.

    2004-01-01

    The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing random nonlinear vibrations in a presence of thermal loading. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

  18. Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

    1992-01-01

    Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

  19. Computer-assisted prediction of HLA-DR binding and experimental analysis for human promiscuous Th1-cell peptides in the 24 kDa secreted lipoprotein (LppX) of Mycobacterium tuberculosis.

    PubMed

    Al-Attiyah, R; Mustafa, A S

    2004-01-01

    The secreted 24 kDa lipoprotein (LppX) is an antigen that is specific for Mycobacterium tuberculosis complex and M. leprae. The present study was carried out to identify the promiscuous T helper 1 (Th1)-cell epitopes of the M. tuberculosis LppX (MT24, Rv2945c) antigen by using 15 overlapping synthetic peptides (25 mers overlapping by 10 residues) covering the sequence of the complete protein. The analysis of Rv2945c sequence for binding to 51 alleles of nine serologically defined HLA-DR molecules, by using a virtual matrix-based prediction program (propred), showed that eight of the 15 peptides of Rv2945c were predicted to bind promiscuously to >/=10 alleles from more than or equal to three serologically defined HLA-DR molecules. The Th1-cell reactivity of all the peptides was assessed in antigen-induced proliferation and interferon-gamma (IFN-gamma)-secretion assays with peripheral blood mononuclear cells (PBMCs) from 37 bacille Calmette-Guérin (BCG)-vaccinated healthy subjects. The results showed that 17 of the 37 donors, which represented an HLA-DR-heterogeneous group, responded to one or more peptides of Rv2945c in the Th1-cell assays. Although each peptide stimulated PBMCs from one or more donors in the above assays, the best positive responses (12/17 (71%) responders) were observed with the peptide p14 (aa 196-220). This suggested a highly promiscuous presentation of p14 to Th1 cells. In addition, the sequence of p14 is completely identical among the LppX of M. tuberculosis, M. bovis and M. leprae, which further supports the usefulness of Rv2945c and p14 in the subunit vaccine design against both tuberculosis and leprosy.

  20. Approximate methods for predicting interlaminar shear stiffness of laminated and sandwich beams

    NASA Astrophysics Data System (ADS)

    Roy, Ajit K.; Verchery, Georges

    1993-01-01

    Several approximate closed form expressions exist in the literature for predicting the effective interlaminar shear stiffness (G13) of laminated composite beams. The accuracy of these approximate methods depends on the number of layers present in the laminated beam, the relative layer thickness and layer stacking sequence, and the beam length to depth ratio. The objective of this work is to evaluate approximate methods for predicting G13 by comparing its predictions with that of an accurate method, and then find the range where the simple closed form expressions for predicting G13 can be applicable. A comparative study indicates that all the approximate methods included here give good prediction of G13 when the laminate is made of a large number of repeated sublaminates. Further, the parabolic shear stress distribution function yields a reasonably accurate prediction of G13 even for a relatively small number of layers in the laminate. A similar result is also presented for sandwich beams.

  1. EVALUATION OF TWO METHODS FOR PREDICTION OF BIOACCUMULATION FACTORS

    EPA Science Inventory

    Two methods for deriving bioaccumulation factors (BAFs) used by the U.S. Environmental Protection Agency (EPA) in development of water quality criteria were evaluated using polychlorinated biphenyls (PCB) data from the Hudson River and Green Bay ecosystems. Greater than 90% of th...

  2. Wing flutter boundary prediction using unsteady Euler aerodynamic method

    NASA Technical Reports Server (NTRS)

    Lee-Rausch, Elizabeth M.; Batina, John T.

    1993-01-01

    Modifications to an existing 3D implicit upwind Euler/Navier-Stokes code for the aeroelastic analysis of wings are described. These modifications include the incorporation of a deforming mesh algorithm and the addition of the structural equations of motion for their simultaneous time-integration with the governing flow equations. The paper gives a brief description of these modifications and presents unsteady calculations which check the modifications to the code. Euler flutter results for an isolated 45 deg swept-back wing are compared with experimental data for seven freestream Mach numbers which define the flutter boundary over a range of Mach number from 0.499 to 1.14. These comparisons show good agreement in flutter characteristics for freestream Mach numbers below unity. For freestream Mach numbers above unity, the computed aeroelastic results predict a premature rise in the flutter boundary as compared with the experimental boundary. Steady and unsteady contours of surface Mach number and pressure are included to illustrate the basic flow characteristics of the time-marching flutter calculations and to aid in identifying possible causes for the premature rise in the computational flutter boundary.

  3. Bridge Frost Prediction by Heat and Mass Transfer Methods

    NASA Astrophysics Data System (ADS)

    Greenfield, Tina M.; Takle, Eugene S.

    2006-03-01

    Frost on roadways and bridges can present hazardous conditions to motorists, particularly when it occurs in patches or on bridges when adjacent roadways are clear of frost. To minimize materials costs, vehicle corrosion, and negative environmental impacts, frost-suppression chemicals should be applied only when, where, and in the appropriate amounts needed to maintain roadways in a safe condition for motorists. Accurate forecasts of frost onset times, frost intensity, and frost disappearance (e.g., melting or sublimation) are needed to help roadway maintenance personnel decide when, where, and how much frost-suppression chemical to use. A finite-difference algorithm (BridgeT) has been developed that simulates vertical heat transfer in a bridge based on evolving meteorological conditions at its top and bottom as supplied by a weather forecast model. BridgeT simulates bridge temperatures at numerous points within the bridge (including its upper and lower surface) at each time step of the weather forecast model and calculates volume per unit area (i.e., depth) of deposited, melted, or sublimed frost. This model produces forecasts of bridge surface temperature, frost depth, and bridge condition (i.e., dry, wet, icy/snowy). Bridge frost predictions and bridge surface temperature are compared with observed and measured values to assess BridgeT's skill in forecasting bridge frost and associated conditions.

  4. Wing flutter boundary prediction using an unsteady Euler aerodynamic method

    NASA Technical Reports Server (NTRS)

    Lee-Rausch, Elizabeth M.; Batina, John T.

    1993-01-01

    Modifications to an existing three-dimensional, implicit, upwind Euler/Navier-Stokes code (CFL3D Version 2.1) for the aeroelastic analysis of wings are described. These modifications, which were previously added to CFL3D Version 1.0, include the incorporation of a deforming mesh algorithm and the addition of the structural equations of motion for their simultaneous time-integration with the government flow equations. The paper gives a brief description of these modifications and presents unsteady calculations which check the modifications to the code. Euler flutter results for an isolated 45 degree swept-back wing are compared with experimental data for seven freestream Mach numbers which define the flutter boundary over a range of Mach number from 0.499 to 1.14. These comparisons show good agreement in flutter characteristics for freestream Mach numbers below unity. For freestream Mach numbers above unity, the computed aeroelastic results predict a premature rise in the flutter boundary as compared with the experimental boundary. Steady and unsteady contours of surface Mach number and pressure are included to illustrate the basic flow characteristics of the time-marching flutter calculations and to aid in identifying possible causes for the premature rise in the computational flutter boundary.

  5. Accuracy assessment of the ERP prediction method based on analysis of 100-year ERP series

    NASA Astrophysics Data System (ADS)

    Malkin, Z.; Tissen, V. M.

    2012-12-01

    A new method has been developed at the Siberian Research Institute of Metrology (SNIIM) for highly accurate prediction of UT1 and Pole motion (PM). In this study, a detailed comparison was made of real-time UT1 predictions made in 2006-2011 and PMpredictions made in 2009-2011making use of the SNIIM method with simultaneous predictions computed at the International Earth Rotation and Reference Systems Service (IERS), USNO. Obtained results have shown that proposed method provides better accuracy at different prediction lengths.

  6. Comparison of measured efficiencies of nine turbine designs with efficiencies predicted by two empirical methods

    NASA Technical Reports Server (NTRS)

    English, Robert E; Cavicchi, Richard H

    1951-01-01

    Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.

  7. New method for predicting melting points of polynitro arene and polynitro heteroarene compounds.

    PubMed

    Keshavarz, Mohammad Hossein

    2009-11-15

    This work introduces a new method for prediction of melting points of nitroaromatic compounds, including polynitro arenes and polynitro heteroarenes, through their molecular structures. The new model extends earlier work, which was used for carbocyclic nitroaromatic compounds, to estimate melting points of heterocyclic aromatic compounds. Some specific functional groups and structural parameters can be used to improve the predicted values on the basis of the number of carbon, hydrogen and nitrogen atoms. The predicted results show that this method gives reliable prediction of melting points with respect to previous work and well-developed group additivity methods for different nitroaromatic explosives with complex molecular structures.

  8. Comparison between enhanced MALDI in-source decay by ammonium persulfate and N- or C-terminal derivatization methods for detailed peptide structure determination.

    PubMed

    Horvatić, Anita; Dodig, Ivana; Vuletić, Tomislav; Pavoković, Dubravko; Hameršak, Zdenko; Butorac, Ana; Cindrić, Mario

    2013-04-16

    Amino acid sequencing and more detailed structure elucidation analysis of peptides and small proteins is a very difficult task even if state-of-the-art mass spectrometry (MS) is employed. To make this task easier, chemical derivatization methods of the N terminus with 4-sulfophenyl-isothiocyanate (SPITC) or the C terminus with 2-methoxy-4,5-dihydro-1H-imidazole (Lys-tag) can enhance peptide fragmentation or fragment ionizability, via proton mobility/localization mechanisms making tandem MS (MS(2)) spectra more informative and less demanding for structural interpretation. Observed disadvantages related to both derivatization methods are sample- and time-consuming procedures and the increased number of reaction byproducts. A novel, sulfate radical in-source formation method of matrix-assisted laser desorption ionization (MALDI) MS based on chemically enhanced in-source decay (ISD) can be accomplished by simple addition of ammonium persulfate (APS) in the matrix solution. This method enables effective decomposition of peptide ions already in the first stage of MS analysis where a large number of fragment ions are produced. The resultant MALDI-ISD mass spectra (MS after APS → MALDI-ISD MS) are almost equivalent to conventional, collision-induced dissociation (CID) MS(2) spectra. These fragment ions are further subjected to the second stage of the MS, and consequently, MS(3) spectra are produced, which makes the sequence analysis more informative and complete (CID MS(2) is thus equivalent to CID MS(3)). Multiply stage MS after APS addition showed enhanced sensitivity, resolution, and mass accuracy compared to peptide derivatization (SPITC and Lys-tag) or conventional MS and MS(2) analyses and offered more detailed insight into peptide structure.

  9. A recursive method for updating apple firmness prediction models based on spectral scattering images

    NASA Astrophysics Data System (ADS)

    Peng, Yankun; Lu, Renfu

    2007-09-01

    Multispectral scattering is effective for nondestructive prediction of fruit firmness. However, the established prediction models for multispectral scattering are variety specific and may not perform appropriately for fruit harvested from different orchards or at different times. In this research, a recursive least squares method was proposed to update the existing prediction model by adding samples from a new population to assure good performance of the model for predicting fruit from the new population. Multispectral scattering images acquired by a multispectral imaging system from Golden Delicious apples that were harvested at the same time but had different postharvest storage time periods were used to develop the updating method. Radial scattering profiles were described by the modified Lorentzian distribution (MLD) function with four profile parameters for eight wavelengths. Multi-linear regression was performed on MLD parameters to establish prediction models for fruit firmness for each group. The prediction model established in the first group was then updated by using selected samples from the second group, and four different sampling methods were compared and validated with the rest apples. The prediction model corrected by the model-updating method gave good firmness predictions with the correlation coefficient (r) of 0.86 and the standard error of prediction (SEP) of 6.11 N. This model updating method is promising for implementing the spectral scattering technique for real-time prediction of apple fruit firmness.

  10. Prediction of skin sensitizers using alternative methods to animal experimentation.

    PubMed

    Johansson, Henrik; Lindstedt, Malin

    2014-07-01

    Regulatory frameworks within the European Union demand that chemical substances are investigated for their ability to induce sensitization, an adverse health effect caused by the human immune system in response to chemical exposure. A recent ban on the use of animal tests within the cosmetics industry has led to an urgent need for alternative animal-free test methods that can be used for assessment of chemical sensitizers. To date, no such alternative assay has yet completed formal validation. However, a number of assays are in development and the understanding of the biological mechanisms of chemical sensitization has greatly increased during the last decade. In this MiniReview, we aim to summarize and give our view on the recent progress of method development for alternative assessment of chemical sensitizers. We propose that integrated testing strategies should comprise complementary assays, providing measurements of a wide range of mechanistic events, to perform well-educated risk assessments based on weight of evidence. PMID:24548737

  11. Prediction of skin sensitizers using alternative methods to animal experimentation.

    PubMed

    Johansson, Henrik; Lindstedt, Malin

    2014-07-01

    Regulatory frameworks within the European Union demand that chemical substances are investigated for their ability to induce sensitization, an adverse health effect caused by the human immune system in response to chemical exposure. A recent ban on the use of animal tests within the cosmetics industry has led to an urgent need for alternative animal-free test methods that can be used for assessment of chemical sensitizers. To date, no such alternative assay has yet completed formal validation. However, a number of assays are in development and the understanding of the biological mechanisms of chemical sensitization has greatly increased during the last decade. In this MiniReview, we aim to summarize and give our view on the recent progress of method development for alternative assessment of chemical sensitizers. We propose that integrated testing strategies should comprise complementary assays, providing measurements of a wide range of mechanistic events, to perform well-educated risk assessments based on weight of evidence.

  12. Differential mass spectrometry: a label-free LC-MS method for finding significant differences in complex peptide and protein mixtures.

    PubMed

    Wiener, Matthew C; Sachs, Jeffrey R; Deyanova, Ekaterina G; Yates, Nathan A

    2004-10-15

    Efficiently identifying and quantifying disease- or treatment-related changes in the abundance of proteins is an important area of research for the pharmaceutical industry. Here we describe an automated, label-free method for finding differences in complex mixtures using complete LC-MS data sets, rather than subsets of extracted peaks or features. The method selectively finds statistically significant differences in the intensity of both high-abundance and low-abundance ions, accounting for the variability of measured intensities and the fact that true differences will persist in time. The method was used to compare two complex peptide mixtures with known peptide differences. This controlled experiment allowed us to assess the validity of each difference found and so to analyze the method's sensitivity and specificity. The method detects both presence versus absence and a 2-fold change in peptide concentration near the limit of detection of the instrument used, where chromatographic peaks may not be sufficiently well defined to be detected in individual samples. The method is more sensitive and gives fewer false positives than subtractive methods that ignore signal variability. Differential mass spectrometry combined with targeted MS/MS analysis of only identified differences may save both computation time and human effort compared to shotgun proteomics approaches. PMID:15481957

  13. Utilization of vortex methods for parachute aerodynamic predictions

    SciTech Connect

    Strickland, J.H.; Meyer, J.

    1986-01-01

    The purpose of this paper is to provide a brief review of vortex methods with application to parachute aerodynamics. A somewhat generalized discussion of analysis techniques which are applicable to development of both two- and three-dimensional numerical solutions will be presented. A brief review of results from several bluff body simulations will be presented along with very recent results from work being conducted by Sandia National Laboratories in this area. 32 refs.

  14. Method of Testing and Predicting Failures of Electronic Mechanical Systems

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; Patterson-Hine, Frances A.

    1996-01-01

    A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

  15. A data-driven epidemiological prediction method for dengue outbreaks using local and remote sensing data

    PubMed Central

    2012-01-01

    Background Dengue is the most common arboviral disease of humans, with more than one third of the world’s population at risk. Accurate prediction of dengue outbreaks may lead to public health interventions that mitigate the effect of the disease. Predicting infectious disease outbreaks is a challenging task; truly predictive methods are still in their infancy. Methods We describe a novel prediction method utilizing Fuzzy Association Rule Mining to extract relationships between clinical, meteorological, climatic, and socio-political data from Peru. These relationships are in the form of rules. The best set of rules is automatically chosen and forms a classifier. That classifier is then used to predict future dengue incidence as either HIGH (outbreak) or LOW (no outbreak), where these values are defined as being above and below the mean previous dengue incidence plus two standard deviations, respectively. Results Our automated method built three different fuzzy association rule models. Using the first two weekly models, we predicted dengue incidence three and four weeks in advance, respectively. The third prediction encompassed a four-week period, specifically four to seven weeks from time of prediction. Using previously unused test data for the period 4–7 weeks from time of prediction yielded a positive predictive value of 0.686, a negative predictive value of 0.976, a sensitivity of 0.615, and a specificity of 0.982. Conclusions We have developed a novel approach for dengue outbreak prediction. The method is general, could be extended for use in any geographical region, and has the potential to be extended to other environmentally influenced infections. The variables used in our method are widely available for most, if not all countries, enhancing the generalizability of our method. PMID:23126401

  16. A Peptide Filtering Relation Quantifies MHC Class I Peptide Optimization

    PubMed Central

    Goldstein, Leonard D.; Howarth, Mark; Cardelli, Luca; Emmott, Stephen; Elliott, Tim; Werner, Joern M.

    2011-01-01

    Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human

  17. Species identification of archaeological skin objects from Danish bogs: comparison between mass spectrometry-based peptide sequencing and microscopy-based methods.

    PubMed

    Brandt, Luise Ørsted; Schmidt, Anne Lisbeth; Mannering, Ulla; Sarret, Mathilde; Kelstrup, Christian D; Olsen, Jesper V; Cappellini, Enrico

    2014-01-01

    Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC - AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029.

  18. Species Identification of Archaeological Skin Objects from Danish Bogs: Comparison between Mass Spectrometry-Based Peptide Sequencing and Microscopy-Based Methods

    PubMed Central

    Brandt, Luise Ørsted; Schmidt, Anne Lisbeth; Mannering, Ulla; Sarret, Mathilde; Kelstrup, Christian D.; Olsen, Jesper V.; Cappellini, Enrico

    2014-01-01

    Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC – AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029. PMID:25260035

  19. Predicting Glass Transition Temperatures of Polyarylethersulphones Using QSPR Methods

    PubMed Central

    Hamerton, Ian; Howlin, Brendan J.; Kamyszek, Grzegorz

    2012-01-01

    The technique of Quantitative Structure Property Relationships has been applied to the glass transition temperatures of polyarylethersulphones. A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90–67%, indicating an error of 10–30% with regard to experimentally determined values) for a series of 42 reported polyarylethersulphones. This method is quite simple in assumption and relies on a relatively small number of parameters associated with the structural unit of the polymer: the number of rotatable bonds, the dipole moment, the heat of formation, the HOMO eigenvalue, the molar mass and molar volume. For smaller subsets of the main group (based on families of derivatives containing different substituents) the model can be simplified further to an equation that uses the volume of the substituents as the principal variable. PMID:22719884

  20. Photovoltaic system lifetime prediction using Petri networks method

    NASA Astrophysics Data System (ADS)

    Laronde, Rémi; Charki, Abderafi; Bigaud, David; Excoffier, Philippe

    2010-08-01

    Photovoltaic modules and systems lifetime and availability are difficult to determine and not really well-known. This information is an important data to insure the installation performance of such a system and to prepare its recycling. The aim of this article is to present a methodology for the availability and lifetime evaluation of a photovoltaic system using the Petri networks method. Each component - module, wires and inverter - is detailed in Petri networks and several laws are used in order to estimate the reliability. Several guides (FIDES, MIL-HDBK-217 ...) allow determining the reliability of electronic components using collections of data. For photovoltaic modules, accelerated life testing are carried out for the evaluation of the lifetime which is described by a Weibull distribution. Results obtained show that Petri networks are very useful to simulate lifetime thanks to its intrinsic modularity.

  1. Analytical Failure Prediction Method Developed for Woven and Braided Composites

    NASA Technical Reports Server (NTRS)

    Min, James B.

    2003-01-01

    Historically, advances in aerospace engine performance and durability have been linked to improvements in materials. Recent developments in ceramic matrix composites (CMCs) have led to increased interest in CMCs to achieve revolutionary gains in engine performance. The use of CMCs promises many advantages for advanced turbomachinery engine development and may be especially beneficial for aerospace engines. The most beneficial aspects of CMC material may be its ability to maintain its strength to over 2500 F, its internal material damping, and its relatively low density. Ceramic matrix composites reinforced with two-dimensional woven and braided fabric preforms are being considered for NASA s next-generation reusable rocket turbomachinery applications (for example, see the preceding figure). However, the architecture of a textile composite is complex, and therefore, the parameters controlling its strength properties are numerous. This necessitates the development of engineering approaches that combine analytical methods with limited testing to provide effective, validated design analyses for the textile composite structures development.

  2. The Structure-Activity Relationship of the Antioxidant Peptides from Natural Proteins.

    PubMed

    Zou, Tang-Bin; He, Tai-Ping; Li, Hua-Bin; Tang, Huan-Wen; Xia, En-Qin

    2016-01-12

    Peptides derived from dietary proteins, have been reported to display significant antioxidant activity, which may exert notably beneficial effects in promoting human health and in food processing. Recently, much research has focused on the generation, separation, purification and identification of novel peptides from various protein sources. Some researchers have tried to discover the structural characteristics of antioxidant peptides in order to lessen or avoid the tedious and aimless work involving the ongoing generated peptide preparation schemes. This review aims to summarize the current knowledge on the relationship between the structural features of peptides and their antioxidant activities. The relationship between the structure of the precursor proteins and their abilities to release antioxidant fragments will also be summarized and inferred. The preparation methods and antioxidant capacity evaluation assays of peptides and a prediction scheme of quantitative structure-activity relationship (QSAR) will also be pointed out and discussed.

  3. An evaluation of rise time characterization and prediction methods

    NASA Technical Reports Server (NTRS)

    Robinson, Leick D.

    1994-01-01

    One common method of extrapolating sonic boom waveforms from aircraft to ground is to calculate the nonlinear distortion, and then add a rise time to each shock by a simple empirical rule. One common rule is the '3 over P' rule which calculates the rise time in milliseconds as three divided by the shock amplitude in psf. This rule was compared with the results of ZEPHYRUS, a comprehensive algorithm which calculates sonic boom propagation and extrapolation with the combined effects of nonlinearity, attenuation, dispersion, geometric spreading, and refraction in a stratified atmosphere. It is shown there that the simple empirical rule considerably overestimates the rise time estimate. In addition, the empirical rule does not account for variations in the rise time due to humidity variation or propagation history. It is also demonstrated that the rise time is only an approximate indicator of perceived loudness. Three waveforms with identical characteristics (shock placement, amplitude, and rise time), but with different shock shapes, are shown to give different calculated loudness. This paper is based in part on work performed at the Applied Research Laboratories, the University of Texas at Austin, and supported by NASA Langley.

  4. Performance Prediction Method of CO2 Cycle for Air Cooling

    NASA Astrophysics Data System (ADS)

    Koyama, Shigeru; Xue, Jun; Kuwahara, Ken

    From the perspective of global environmental protection and energy-saving, the research and development on high-efficiency heat pump and refrigeration systems using environment-friendly refrigerants have become one of the most important issues in the air-conditioning and refrigeration sector. In the present work, a steady-state model of the CO2 transcritical cycle for air cooling, which consists of a rotary compressor, a fin-tube gas cooler,a fin-tube evaporator and an expansion valve, has been developed. The detailed model of fin-tube heat exchanger has been constructed by means of the finite volume method, in which the local heat transfer and flow characteristics are evaluated. It should be noted that the effects of the dew condensation generated on the cooling surface are considered in the evaporator model. As a calculation example, the effects of the indoor air wet-bulb temperature on the cycle performance have been examined with this developed simulator.

  5. Comprehensive peptide marker identification for the detection of multiple nut allergens using a non-targeted LC-HRMS multi-method.

    PubMed

    Korte, Robin; Lepski, Silke; Brockmeyer, Jens

    2016-05-01

    Food allergies have emerged as a global problem over the last few decades; therefore, reliable and sensitive analytical methods to ensure food safety for allergic consumers are required. The application of mass spectrometry is of growing interest in this field and several procedures based on low resolution tandem mass spectrometry using single tryptic peptides as analytical targets have recently been described. However, a comprehensive survey of marker peptides for the development of multi-methods is still missing, as is a consensus guide to marker identification. In this study, we therefore report a consistent approach to the development of liquid chromatography-mass spectrometry (LC-MS) multi-screening methods for the detection of allergens in food matrices. Proteotypic peptides were identified by a shotgun proteomics approach and verified through a thorough investigation of specificity and sensitivity. On the basis of this procedure, we identified 44 suitable tryptic marker peptides from six allergenic nut species and developed the first analytical LC-MS method for the detection of trace nut contaminations in processed foods using high resolution mass spectrometry (HRMS). The analysis of spiked matrix samples gave limits of detection (LODs) below 10 μg/g for several nuts; these LODs are comparable with routinely used methods such as ELISA and PCR. Notably, the HRMS approach can be used in an untargeted fashion to identify multiple allergens also retrospectively. In conclusion, we present here the so far largest consensus set of analytical markers from nut allergens and to the best of our knowledge the first multi-allergen method based on LC-HRMS.

  6. Comparative Study of Different Methods for the Prediction of Drug-Polymer Solubility.

    PubMed

    Knopp, Matthias Manne; Tajber, Lidia; Tian, Yiwei; Olesen, Niels Erik; Jones, David S; Kozyra, Agnieszka; Löbmann, Korbinian; Paluch, Krzysztof; Brennan, Claire Marie; Holm, René; Healy, Anne Marie; Andrews, Gavin P; Rades, Thomas

    2015-09-01

    In this study, a comparison of different methods to predict drug-polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug-polymer solubility at 25 °C was predicted using the Flory-Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine-PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug-polymer solubility. PMID:26214347

  7. Comparative Study of Different Methods for the Prediction of Drug-Polymer Solubility.

    PubMed

    Knopp, Matthias Manne; Tajber, Lidia; Tian, Yiwei; Olesen, Niels Erik; Jones, David S; Kozyra, Agnieszka; Löbmann, Korbinian; Paluch, Krzysztof; Brennan, Claire Marie; Holm, René; Healy, Anne Marie; Andrews, Gavin P; Rades, Thomas

    2015-09-01

    In this study, a comparison of different methods to predict drug-polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug-polymer solubility at 25 °C was predicted using the Flory-Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine-PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug-polymer solubility.

  8. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    SciTech Connect

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  9. Engineering cyclic peptide toxins.

    PubMed

    Clark, Richard J; Craik, David J

    2012-01-01

    Peptide-based toxins have attracted much attention in recent years for their exciting potential applications in drug design and development. This interest has arisen because toxins are highly potent and selectively target a range of physiologically important receptors. However, peptides suffer from a number of disadvantages, including poor in vivo stability and poor bioavailability. A number of naturally occurring cyclic peptides have been discovered in plants, animals, and bacteria that have exceptional stability and potentially ameliorate these disadvantages. The lessons learned from studies of the structures, stabilities, and biological activities of these cyclic peptides can be applied to the reengineering of toxins that are not naturally cyclic but are amenable to cyclization. In this chapter, we describe solid-phase chemical synthetic methods for the reengineering of peptide toxins to improve their suitability as therapeutic, diagnostic, or imaging agents. The focus is on small disulfide-rich peptides from the venoms of cone snails and scorpions, but the technology is potentially widely applicable to a number of other peptide-based toxins. PMID:22230565

  10. Detection of trans–cis flips and peptide-plane flips in protein structures

    PubMed Central

    Touw, Wouter G.; Joosten, Robbie P.; Vriend, Gert

    2015-01-01

    A coordinate-based method is presented to detect peptide bonds that need correction either by a peptide-plane flip or by a trans–cis inversion of the peptide bond. When applied to the whole Protein Data Bank, the method predicts 4617 trans–cis flips and many thousands of hitherto unknown peptide-plane flips. A few examples are highlighted for which a correction of the peptide-plane geometry leads to a correction of the understanding of the structure–function relation. All data, including 1088 manually validated cases, are freely available and the method is available from a web server, a web-service interface and through WHAT_CHECK. PMID:26249342

  11. Studies of the Raman spectra of cyclic and acyclic molecules: Combination and prediction spectrum methods

    NASA Astrophysics Data System (ADS)

    Kim, Taejin; Assary, Rajeev S.; Marshall, Christopher L.; Gosztola, David J.; Curtiss, Larry A.; Stair, Peter C.

    2012-04-01

    A combination of Raman spectroscopy and density functional methods was employed to investigate the spectral features of selected molecules: furfural, 5-hydroxymethyl furfural (HMF), methanol, acetone, acetic acid, and levulinic acid. The computed spectra and measured spectra are in excellent agreement, consistent with previous studies. Using the combination and prediction spectrum method (CPSM), we were able to predict the important spectral features of two platform chemicals, HMF and levulinic acid. The results have shown that CPSM is a useful alternative method for predicting vibrational spectra of complex molecules in the biomass transformation process.

  12. Studies of the Raman Spectra of Cyclic and Acyclic Molecules: Combination and Prediction Spectrum Methods

    SciTech Connect

    Kim, Taijin; Assary, Rajeev S.; Marshall, Christopher L.; Gosztola, David J.; Curtiss, Larry A.; Stair, Peter C.

    2012-04-02

    A combination of Raman spectroscopy and density functional methods was employed to investigate the spectral features of selected molecules: furfural, 5-hydroxymethyl furfural (HMF), methanol, acetone, acetic acid, and levulinic acid. The computed spectra and measured spectra are in excellent agreement, consistent with previous studies. Using the combination and prediction spectrum method (CPSM), we were able to predict the important spectral features of two platform chemicals, HMF and levulinic acid.The results have shown that CPSM is a useful alternative method for predicting vibrational spectra of complex molecules in the biomass transformation process.

  13. Trifluoroethanol and binding to model membranes stabilize a predicted turn in a peptide corresponding to the first extracellular loop of the angiotensin II AT(1A) receptor.

    PubMed

    Salinas, Roberto K; Shida, Cláudio S; Pertinhez, Thelma A; Spisni, Alberto; Nakaie, Clóvis R; Paiva, Antonio C M; Schreier, Shirley

    2002-10-01

    Homology modeling of the angiotensin II AT(1A) receptor based on rhodopsin's crystal structure has assigned the 92-100 (YRWPFGNHL) sequence of the receptor to its first extracellular loop. Solution and membrane-bound conformational properties of a peptide containing this sequence (EL1) were examined by CD, fluorescence, and (1)H-NMR. CD spectra in aqueous solution revealed an equilibrium between less organized and folded conformers. NMR spectra indicated the coexistence of trans and cis isomers of the Trp(3)-Pro(4) bond. A positive band at 226 nm in the CD spectra suggested aromatic ring stacking, modulated by EL1's ionization degree. CD spectra showed that trifluoroethanol (TFE), or binding to detergent micelles and phospholipid bilayers, shifted the equilibrium toward conformers with higher secondary structure content. Different media gave rise to spectra suggestive of different beta-turns. Chemical shift changes in the NMR spectra corroborated the stabilization of different conformations. Thus, environments of lower polarity or binding to interfaces probably favored the formation of hydrogen bonds, stabilizing beta-turns, predicted for this sequence in the whole receptor. Increases in Trp(3) fluorescence intensity and anisotropy, blue shifts of the maximum emission wavelength, and pK changes also evinced the interaction between EL1 and model membranes. Binding was seen to depend on both hydrophobic and electrostatic interactions, as well as lipid phase packing. Studies with water-soluble and membrane-bound fluorescence quenchers demonstrated that Trp(3) is located close to the water-membrane interface. The results are discussed with regard to possible implications in receptor folding and function.

  14. Sequencing Cyclic Peptides by Multistage Mass Spectrometry

    PubMed Central

    Mohimani, Hosein; Yang, Yu-Liang; Liu, Wei-Ting; Hsieh, Pei-Wen; Dorrestein, Pieter C.; Pevzner, Pavel A.

    2012-01-01

    Some of the most effective antibiotics (e.g., Vancomycin and Daptomycin) are cyclic peptides produced by non-ribosomal biosynthetic pathways. While hundreds of biomedically important cyclic peptides have been sequenced, the computational techniques for sequencing cyclic peptides are still in their infancy. Previous methods for sequencing peptide antibiotics and other cyclic peptides are based on Nuclear Magnetic Resonance spectroscopy, and require large amount (miligrams) of purified materials that, for most compounds, are not possible to obtain. Recently, development of mass spectrometry based methods has provided some hope for accurate sequencing of cyclic peptides using picograms of materials. In this paper we develop a method for sequencing of cyclic peptides by multistage mass spectrometry, and show its advantages over single stage mass spectrometry. The method is tested on known and new cyclic peptides from Bacillus brevis, Dianthus superbus and Streptomyces griseus, as well as a new family of cyclic peptides produced by marine bacteria. PMID:21751357

  15. Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Sankararaman, Shankar

    2013-01-01

    Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

  16. Exploring experimental and computational markers of cyclic peptides: Charting islands of permeability.

    PubMed

    Wang, Conan K; Northfield, Susan E; Swedberg, Joakim E; Colless, Barbara; Chaousis, Stephanie; Price, David A; Liras, Spiros; Craik, David J

    2015-06-01

    An increasing number of macrocyclic peptides that cross biological membranes are being reported, suggesting that it might be possible to develop peptides into orally bioavailable therapeutics; however, current understanding of what makes macrocyclic peptides cell permeable is still limited. Here, we synthesized 62 cyclic hexapeptides and characterized their permeability using in vitro assays commonly used to predict in vivo absorption rates, i.e. the Caco-2 and PAMPA assays. We correlated permeability with experimentally measured parameters of peptide conformation obtained using rapid methods based on chromatography and nuclear magnetic resonance spectroscopy. Based on these correlations, we propose a model describing the interplay between peptide permeability, lipophilicity and hydrogen bonding potential. Specifically, peptides with very high permeability have high lipophilicity and few solvent hydrogen bond interactions, whereas peptides with very low permeability have low lipophilicity or many solvent interactions. Our model is supported by molecular dynamics simulations of the cyclic peptides calculated in explicit solvent, providing a structural basis for the observed correlations. This prospective exploration into biomarkers of peptide permeability has the potential to unlock wider opportunities for development of peptides into drugs. PMID:25974856

  17. Fluorescence in situ Hybridization method using Peptide Nucleic Acid probes for rapid detection of Lactobacillus and Gardnerella spp.

    PubMed Central

    2013-01-01

    Background Bacterial vaginosis (BV) is a common vaginal infection occurring in women of reproductive age. It is widely accepted that the microbial switch from normal microflora to BV is characterized by a decrease in vaginal colonization by Lactobacillus species together with an increase of Gardnerella vaginalis and other anaerobes. Our goal was to develop and optimize a novel Peptide Nucleic Acid (PNA) Fluorescence in situ Hybridization assay (PNA FISH) for the detection of Lactobacillus spp. and G. vaginalis in mixed samples. Results Therefore, we evaluated and validated two specific PNA probes by using 36 representative Lactobacillus strains, 22 representative G. vaginalis strains and 27 other taxonomically related or pathogenic bacterial strains commonly found in vaginal samples. The probes were also tested at different concentrations of G. vaginalis and Lactobacillus species in vitro, in the presence of a HeLa cell line. Specificity and sensitivity of the PNA probes were found to be 98.0% (95% confidence interval (CI), from 87.8 to 99.9%) and 100% (95% CI, from 88.0 to 100.0%), for Lactobacillus spp.; and 100% (95% CI, from 92.8 to 100%) and 100% (95% CI, from 81.5 to 100.0%) for G. vaginalis. Moreover, the probes were evaluated in mixed samples mimicking women with BV or normal vaginal microflora, demonstrating efficiency and applicability of our PNA FISH. Conclusions This quick method accurately detects Lactobacillus spp. and G. vaginalis species in mixed samples, thus enabling efficient evaluation of the two bacterial groups, most frequently encountered in the vagina. PMID:23586331

  18. Classification of antimicrobial peptides with imbalanced datasets

    NASA Astrophysics Data System (ADS)

    Camacho, Francy L.; Torres, Rodrigo; Ramos Pollán, Raúl

    2015-12-01

    In the last years, pattern recognition has been applied to several fields for solving multiple problems in science and technology as for example in protein prediction. This methodology can be useful for prediction of activity of biological molecules, e.g. for determination of antimicrobial activity of synthetic and natural peptides. In this work, we evaluate the performance of different physico-chemical properties of peptides (descriptors groups) in the presence of imbalanced data sets, when facing the task of detecting whether a peptide has antimicrobial activity. We evaluate undersampling and class weighting techniques to deal with the class imbalance with different classification methods and descriptor groups. Our classification model showed an estimated precision of 96% showing that descriptors used to codify the amino acid sequences contain enough information to correlate the peptides sequences with their antimicrobial activity by means of learning machines. Moreover, we show how certain descriptor groups (pseudoaminoacid composition type I) work better with imbalanced datasets while others (dipeptide composition) work better with balanced ones.

  19. Prediction of the total cycle 24 of solar activity by several autoregressive methods and by the precursor method

    NASA Astrophysics Data System (ADS)

    Ozheredov, V. A.; Breus, T. K.; Obridko, V. N.

    2012-12-01

    As follows from the statement of the Third Official Solar Cycle 24 Prediction Panel created by the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the International Space Environment Service (ISES) based on the results of an analysis of many solar cycle 24 predictions, there has been no consensus on the amplitude and time of the maximum. There are two different scenarios: 90 units and August 2012 or 140 units and October 2011. The aim of our study is to revise the solar cycle 24 predictions by a comparative analysis of data obtained by three different methods: the singular spectral method, the nonlinear neural-based method, and the precursor method. As a precursor for solar cycle 24, we used the dynamics of the solar magnetic fields forming solar spots with Wolf numbers Rz. According to the prediction on the basis of the neural-based approach, it was established that the maximum of solar cycle 24 is expected to be 70. The precursor method predicted 50 units for the amplitude and April of 2012 for the time of the maximum. In view of the fact that the data used in the precursor method were averaged over 4.4 years, the amplitude of the maximum can be 20-30% larger (i.e., around 60-70 units), which is close to the values predicted by the neural-based method. The protracted minimum of solar cycle 23 and predicted low values of the maximum of solar cycle 24 are reminiscent of the historical Dalton minimum.

  20. Clinical utility of natriuretic peptides and troponins in hypertrophic cardiomyopathy.

    PubMed

    Kehl, Devin W; Buttan, Anshu; Siegel, Robert J; Rader, Florian

    2016-09-01

    The diagnosis of hypertrophic cardiomyopathy (HCM) is based on clinical, echocardiographic and in some cases genetic findings. However, prognostication remains limited except in the subset of patients with high-risk indicators for sudden cardiac death. Additional methods are needed for risk stratification and to guide clinical management in HCM. We reviewed the available data regarding natriuretic peptides and troponins in HCM. Plasma levels of natriuretic peptides, and to a lesser extent serum levels of troponins, correlate with established disease markers, including left ventricular thickness, symptom status, and left ventricular hemodynamics by Doppler measurements. As a reflection of left ventricular filling pressure, natriuretic peptides may provide an objective measure of the efficacy of a specific therapy. Both natriuretic peptides and troponins predict clinical risk in HCM independently of established risk factors, and their prognostic power is additive. Routine measurement of biomarker levels therefore may be useful in the clinical evaluation and management of patients with HCM.

  1. Development and validation of a rapid HPLC method for the quantification of GSE4 peptide in biodegradable PEI-PLGA nanoparticles.

    PubMed

    Egusquiaguirre, Susana P; Manguán-García, Cristina; Perona, Rosario; Pedraz, José Luís; Hernández, Rosa Maria; Igartua, Manuela

    2014-12-01

    In this work a high performance liquid chromatographic (HPLC) method has been developed and validated for the content determination of GSE4 peptide in PEI-PLGA nanoparticles. Chromatographic separation was performed on a C18 column, and a gradient elution with a mobile phase composed of methanol and 0.1% aqueous trifluoroacetic acid (TFA) solution, at a flow rate of 1ml/min, was used. GSE4 peptide identification was made by fluorescence detection at 290nm. The elution of methanol:TFA was initially maintained at (20:80, v/v) for one min and the gradient changed to (80:20, v/v) in 6min. This ratio was then followed by isocratic elution at (80:20, v/v) during another min and for further 3min it was linearly modified to (20:80, v/v). The developed method was validated according to the ICH guidelines, being specific, linear in the range 10-100μg/ml (R(2)=0.9996), precise, exhibiting good inter-day and intra-day precision reflected by the relative standard deviation values (less than 3.88%), accurate, with a recovery rate of 100.18±0.95%, and stable for 48h at 5°C or at RT when encapsulated in nanoparticles. The method was simple, fast, and successfully used to determine the peptide content in GSE4-loaded PEI-PLGA nanoparticles.

  2. The prediction of in-hospital mortality by amino terminal pro-brain natriuretic peptide (NT-proBNP) levels and other independent variables in acutely ill patients with suspected heart disease.

    PubMed

    Kellett, John

    2005-06-01

    BACKGROUND: Amino terminal pro-brain natriuretic peptide (NT-proBNP) measurement can detect and assess heart failure. However, compared with traditional clinical parameters, its value in predicting the in-hospital mortality of patients with suspected heart disease has not been reported. METHODS: We examined the ability of 11 continuous and 21 categorical variables, including NT-proBNP levels measured at the time of admission, to predict in-hospital mortality. The setting was a small Irish rural hospital where 342 consecutive patients with suspected heart disease were admitted as acute medical emergencies. RESULTS: The 31 patients who died while in hospital had significantly higher NT-proBNP levels on admission than patients discharged alive (11,548+/-13,531 vs. 3805+/-6914 pg/mL, p<0.0001). Patients who died in-hospital were older, had significantly higher white cell counts, blood urea and modified early warning (MEW) scores, and lower temperatures, blood pressures and oxygen saturation. Four variables were found to be independent predictors of in-hospital mortality: a systolic blood pressure equal to or below 100 mm Hg, a urea level above 13 mmol/L, a white cell count greater than 13*10(9)/L and a NT-proBNP level greater than or equal to 11,500 pg/mL. The presence of three of these variables was associated with an in-hospital mortality rate of 54%. CONCLUSIONS: Four variables (i.e. hypotension, elevated urea, leukocytosis and elevated NT-proBNP levels) are comparable independent predictors of in-hospital mortality.

  3. Effective thermal conductivity method for predicting spent nuclear fuel cladding temperatures in a dry fill gas

    SciTech Connect

    Bahney, Robert

    1997-12-19

    This paper summarizes the development of a reliable methodology for the prediction of peak spent nuclear fuel cladding temperature within the waste disposal package. The effective thermal conductivity method replaces other older methodologies.

  4. New Computational Methods for the Prediction and Analysis of Helicopter Noise

    NASA Technical Reports Server (NTRS)

    Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

    1996-01-01

    This paper describes several new methods to predict and analyze rotorcraft noise. These methods are: 1) a combined com