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Sample records for tertiary structure prediction

  1. AB Initio Protein Tertiary Structure Prediction: Comparative-Genetic Algorithm with Graph Theoretical Methods

    Energy Technology Data Exchange (ETDEWEB)

    Gregurick, S. K.

    2001-04-20

    During the period from September 1, 1998 until September 1, 2000 I was awarded a Sloan/DOE postdoctoral fellowship to work in collaboration with Professor John Moult at the Center for Advanced Research in Biotechnology (CARB). Our research project, ''Ab Initio Protein Tertiary Structure Prediction and a Comparative Genetic algorithm'', yielded promising initial results. In short, the project is designed to predict the native fold, or native tertiary structure, of a given protein by inputting only the primary sequence of the protein (one or three letter code). The algorithm is based on a general learning, or evolutionary algorithm and is called Genetic Algorithm (GAS). In our particular application of GAS, we search for native folds, or lowest energy structures, using two different descriptions for the interactions of the atoms and residues in a given protein sequence. One potential energy function is based on a free energy description, while the other function is a threading potential derived by Moult and Samudrala. This modified genetic algorithm was loosely termed a Comparative Genetic Algorithm and was designed to search for native folded structures on both potential energy surfaces, simultaneously. We tested the algorithm on a series of peptides ranging from 11 to 15 residues in length, which are thought to be independent folding units and thereby will fold to native structures independent of the larger protein environment. Our initial results indicated a modest increase in accuracy, as compared to a standard Genetic Algorithm. We are now in the process of improving the algorithm to increase the sensitivity to other inputs, such as secondary structure requirements. The project did not involve additional students and as of yet, the work has not been published.

  2. Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

    Science.gov (United States)

    Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

    2017-01-01

    As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  3. Prediction and Analysis of Surface Hydrophobic Residues in Tertiary Structure of Proteins

    Science.gov (United States)

    Malleshappa Gowder, Shambhu; Chaudhuri, Tanusree; Paul, Kusum

    2014-01-01

    The analysis of protein structures provides plenty of information about the factors governing the folding and stability of proteins, the preferred amino acids in the protein environment, the location of the residues in the interior/surface of a protein and so forth. In general, hydrophobic residues such as Val, Leu, Ile, Phe, and Met tend to be buried in the interior and polar side chains exposed to solvent. The present work depends on sequence as well as structural information of the protein and aims to understand nature of hydrophobic residues on the protein surfaces. It is based on the nonredundant data set of 218 monomeric proteins. Solvent accessibility of each protein was determined using NACCESS software and then obtained the homologous sequences to understand how well solvent exposed and buried hydrophobic residues are evolutionarily conserved and assigned the confidence scores to hydrophobic residues to be buried or solvent exposed based on the information obtained from conservation score and knowledge of flanking regions of hydrophobic residues. In the absence of a three-dimensional structure, the ability to predict surface accessibility of hydrophobic residues directly from the sequence is of great help in choosing the sites of chemical modification or specific mutations and in the studies of protein stability and molecular interactions. PMID:24672404

  4. Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi-automated metrics.

    Science.gov (United States)

    Abriata, Luciano A; Kinch, Lisa N; Tamò, Giorgio E; Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Dal Peraro, Matteo

    2017-10-16

    For assessment purposes, CASP targets are split into evaluation units. We herein present the official definition of CASP12 evaluation units (EUs) and their classification into difficulty categories. Each target can be evaluated as one EU (the whole target) or/and several EUs (separate structural domains or groups of structural domains). The specific scenario for a target split is determined by the domain organization of available templates, the difference in server performance on separate domains versus combination of the domains, and visual inspection. In the end, 71 targets were split into 96 EUs. Classification of the EUs into difficulty categories was done semi-automatically with the assistance of metrics provided by the Prediction Center. These metrics account for sequence and structural similarities of the EUs to potential structural templates from the Protein Data Bank, and for the baseline performance of automated server predictions. The metrics readily separate the 96 EUs into 38 EUs that should be straightforward for template-based modeling (TBM) and 39 that are expected to be hard for homology modeling and are thus left for free modeling (FM). The remaining 19 borderline evaluation units were dubbed FM/TBM, and were inspected case by case. The article also overviews structural and evolutionary features of selected targets relevant to our accompanying article presenting the assessment of FM and FM/TBM predictions, and overviews structural features of the hardest evaluation units from the FM category. We finally suggest improvements for the EU definition and classification procedures. © 2017 Wiley Periodicals, Inc.

  5. In silico Prediction and Docking of Tertiary Structure of LuxI, an Inducer Synthase of Vibrio fischeri

    Directory of Open Access Journals (Sweden)

    Mohammed Zaghlool Saeed Al-Khayyat

    2016-05-01

    Full Text Available Background: LuxI is a component of the quorum sensing signaling pathway in Vibrio fischeri responsible for the inducer synthesis that is essential for bioluminescence. Methods: Homology modeling of LuxI was carried out using Phyre2 and refined with the GalaxyWEB server. Five models were generated and evaluated by ERRAT, ANOLEA, QMEAN6, and Procheck. Results: Five refined models were generated by the GalaxyWEB server, with Model 4 having the greatest quality based on the QMEAN6 score of 0.732. ERRAT analysis revealed an overall quality of 98.9%, while the overall quality of the initial model was 54%. The mean force potential energy, as analyzed by ANOLEA, were better compared to the initial model. Sterochemical quality estimation by Procheck showed that the refined Model 4 had a reliable structure, and was therefore submitted to the protein model database. Drug Discovery Workbench V.2 was used to screen 2700 experimental compounds from the DrugBank database to identify inhibitors that can bind to the active site between amino acids 24 and 110. Ten compounds with high negative scores were selected as the best in binding. Conclusion: The model produced, and the predicted acteyltransferase binding site, could be useful in modeling homologous sequences from other microorganisms and the design of new antimicrobials.

  6. Modelling the harmonized tertiary Institutions Salary Structure ...

    African Journals Online (AJOL)

    This paper analyses the Harmonized Tertiary Institution Salary Structure (HATISS IV) used in Nigeria. The irregularities in the structure are highlighted. A model that assumes a polynomial trend for the zero step salary, and exponential trend for the incremental rates, is suggested for the regularization of the structure.

  7. Tertiary alphabet for the observable protein structural universe.

    Science.gov (United States)

    Mackenzie, Craig O; Zhou, Jianfu; Grigoryan, Gevorg

    2016-11-22

    Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.

  8. Salt Contribution to RNA Tertiary Structure Folding Stability

    Science.gov (United States)

    Tan, Zhi-Jie; Chen, Shi-Jie

    2011-01-01

    Accurate quantification of the ionic contribution to RNA folding stability could greatly enhance our ability to understand and predict RNA functions. Recently, motivated by the potential importance of ion correlation and fluctuation in RNA folding, we developed the tightly bound ion (TBI) model. Extensive experimental tests showed that the TBI model can lead to better treatment of multivalent ions than the Poisson-Boltzmann equation. In this study, we use the model to quantify the contribution of salt (Na+ and Mg2+) to the RNA tertiary structure folding free energy. Folding of the RNA tertiary structure often involves intermediates. We focus on the folding transition from an intermediate state to the native state, and compute the electrostatic folding free energy of the RNA. Based on systematic calculations for a variety of RNA molecules, we derive a set of formulas for the electrostatic free energy for tertiary structural folding as a function of the sequence length and compactness of the RNA and the Na+ and Mg2+ concentrations. Extensive comparisons with experimental data suggest that our model and the extracted empirical formulas are quite reliable. PMID:21723828

  9. From Ramachandran Maps to Tertiary Structures of Proteins.

    Science.gov (United States)

    DasGupta, Debarati; Kaushik, Rahul; Jayaram, B

    2015-08-27

    Sequence to structure of proteins is an unsolved problem. A possible coarse grained resolution to this entails specification of all the torsional (Φ, Ψ) angles along the backbone of the polypeptide chain. The Ramachandran map quite elegantly depicts the allowed conformational (Φ, Ψ) space of proteins which is still very large for the purposes of accurate structure generation. We have divided the allowed (Φ, Ψ) space in Ramachandran maps into 27 distinct conformations sufficient to regenerate a structure to within 5 Å from the native, at least for small proteins, thus reducing the structure prediction problem to a specification of an alphanumeric string, i.e., the amino acid sequence together with one of the 27 conformations preferred by each amino acid residue. This still theoretically results in 27(n) conformations for a protein comprising "n" amino acids. We then investigated the spatial correlations at the two-residue (dipeptide) and three-residue (tripeptide) levels in what may be described as higher order Ramachandran maps, with the premise that the allowed conformational space starts to shrink as we introduce neighborhood effects. We found, for instance, for a tripeptide which potentially can exist in any of the 27(3) "allowed" conformations, three-fourths of these conformations are redundant to the 95% confidence level, suggesting sequence context dependent preferred conformations. We then created a look-up table of preferred conformations at the tripeptide level and correlated them with energetically favorable conformations. We found in particular that Boltzmann probabilities calculated from van der Waals energies for each conformation of tripeptides correlate well with the observed populations in the structural database (the average correlation coefficient is ∼0.8). An alpha-numeric string and hence the tertiary structure can be generated for any sequence from the look-up table within minutes on a single processor and to a higher level of accuracy

  10. ProTSAV: A protein tertiary structure analysis and validation server.

    Science.gov (United States)

    Singh, Ankita; Kaushik, Rahul; Mishra, Avinash; Shanker, Asheesh; Jayaram, B

    2016-01-01

    Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Analysis of Management Practices in Lagos State Tertiary Institutions through Total Quality Management Structural Framework

    Science.gov (United States)

    AbdulAzeez, Abbas Tunde

    2016-01-01

    This research investigated total quality management practices and quality teacher education in public tertiary institutions in Lagos State. The study was therefore designed to analyse management practices in Lagos state tertiary institutions through total quality management structural framework. The selected public tertiary institutions in Lagos…

  12. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A

    2011-01-01

    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  13. The MULTICOM toolbox for protein structure prediction

    Directory of Open Access Journals (Sweden)

    Cheng Jianlin

    2012-04-01

    Full Text Available Abstract Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9 from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  14. Topological constraints are major determinants of tRNA tertiary structure and dynamics and provide basis for tertiary folding cooperativity.

    Science.gov (United States)

    Mustoe, Anthony M; Brooks, Charles L; Al-Hashimi, Hashim M

    2014-10-01

    Recent studies have shown that basic steric and connectivity constraints encoded at the secondary structure level are key determinants of 3D structure and dynamics in simple two-way RNA junctions. However, the role of these topological constraints in higher order RNA junctions remains poorly understood. Here, we use a specialized coarse-grained molecular dynamics model to directly probe the thermodynamic contributions of topological constraints in defining the 3D architecture and dynamics of transfer RNA (tRNA). Topological constraints alone restrict tRNA's allowed conformational space by over an order of magnitude and strongly discriminate against formation of non-native tertiary contacts, providing a sequence independent source of folding specificity. Topological constraints also give rise to long-range correlations between the relative orientation of tRNA's helices, which in turn provides a mechanism for encoding thermodynamic cooperativity between distinct tertiary interactions. These aspects of topological constraints make it such that only several tertiary interactions are needed to confine tRNA to its native global structure and specify functionally important 3D dynamics. We further show that topological constraints are conserved across tRNA's different naturally occurring secondary structures. Taken together, our results emphasize the central role of secondary-structure-encoded topological constraints in defining RNA 3D structure, dynamics and folding. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Characteristics and Prediction of RNA Structure

    Directory of Open Access Journals (Sweden)

    Hengwu Li

    2014-01-01

    Full Text Available RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, and L, where L is the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.

  16. Prediction of the secondary structure of HIV-1 gp120

    DEFF Research Database (Denmark)

    Hansen, J E; Lund, O; Nielsen, Jens Ole

    1996-01-01

    strain BH10 gp120, as well as in 27 other HIV-1 strains examined. Two helical segments were predicted in regions displaying profound sequence variation, one in a region suggested to be critical for CD4 binding. The predicted content of helix, beta-strand, and coil was consistent with estimates from......The secondary structure of HIV-1 gp120 was predicted using multiple alignment and a combination of two independent methods based on neural network and nearest-neighbor algorithms. The methods agreed on the secondary structure for 80% of the residues in BH10 gp120. Six helices were predicted in HIV...... Fourier transform infrared spectroscopy. The predicted secondary structure of gp120 compared well with data from NMR analysis of synthetic peptides from the V3 loop and the C4 region. As a first step towards modeling the tertiary structure of gp120, the predicted secondary structure may guide the design...

  17. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G

    1996-01-01

    Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a number...... of proteins of biological interest using ab initio pre!diction of fold recognition methods. 112 protein sequences were collected via an open invitation for target submissions. 17 were selected for prediction during the workshop and for 11 of these a prediction of some reliability could be made. We believe...

  18. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

    Sommer, I.; Rahnenfuhrer, J.; de Lichtenberg, Ulrik

    2004-01-01

    We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given...... query sequences these probabilities are obtained by a neural net that has previously been trained on a variety of functionally important features. On a training set of sequences we assess the relevance of individual functional categories for identifying a given structural family. Using a combination...... of the most relevant categories, the likelihood of a query sequence to belong to a specific family can be estimated. Results: The performance of the method is evaluated using cross-validation. For a fixed structural family and for every sequence, a score is calculated that measures the evidence for family...

  19. Hypochlorous acid-mediated protein oxidation: how important are chloramine transfer reactions and protein tertiary structure?

    Science.gov (United States)

    Pattison, David I; Hawkins, Clare L; Davies, Michael J

    2007-08-28

    Hypochlorous acid (HOCl) is a powerful oxidant generated from H2O2 and Cl- by the heme enzyme myeloperoxidase, which is released from activated leukocytes. HOCl possesses potent antibacterial properties, but excessive production can lead to host tissue damage that occurs in numerous human pathologies. As proteins and amino acids are highly abundant in vivo and react rapidly with HOCl, they are likely to be major targets for HOCl. In this study, two small globular proteins, lysozyme and insulin, have been oxidized with increasing excesses of HOCl to determine whether the pattern of HOCl-mediated amino acid consumption is consistent with reported kinetic data for isolated amino acids and model compounds. Identical experiments have been carried out with mixtures of N-acetyl amino acids (to prevent reaction at the alpha-amino groups) that mimic the protein composition to examine the role of protein structure on reactivity. The results indicate that tertiary structure facilitates secondary chlorine transfer reactions of chloramines formed on His and Lys side chains. In light of these data, second-order rate constants for reactions of Lys side chain and Gly chloramines with Trp side chains and disulfide bonds have been determined, together with those for further oxidation of Met sulfoxide by HOCl and His side chain chloramines. Computational kinetic models incorporating these additional rate constants closely predict the experimentally observed amino acid consumption. These studies provide insight into the roles of chloramine formation and three-dimensional structure on the reactions of HOCl with isolated proteins and demonstrate that kinetic models can predict the outcome of HOCl-mediated protein oxidation.

  20. Do health complaints in adolescence negatively predict the chance of entering tertiary education in young adulthood?

    Science.gov (United States)

    Låftman, Sara B; Magnusson, Charlotta

    2017-12-01

    Self-reported psychological and psychosomatic health complaints, such as nervousness, sadness, headache and stomach-ache, are common among adolescents, particularly among girls, and studies suggest that the prevalence has risen among adolescent girls during the last few decades. However, only a limited number of studies have investigated the potential long-term consequences of such health complaints. The aim of the current study was to assess whether psychological and psychosomatic health complaints in adolescence predict the chance of entering tertiary education in young adulthood among women and men. The data used are from the Swedish Young-LNU, which is based on a nationally representative sample with self-reported survey information from adolescents aged 10-18 years in 2000 and from the same individuals at ages 20-28 in 2010 ( n=783). Information was also collected from parents and from official registers. Linear probability models showed that self-reported psychological complaints in adolescence were associated with a lower chance of having entered tertiary education 10 years later. This association was accounted for by differences in grade point average (GPA), suggesting that GPA may mediate the association between psychological complaints and later education. The pattern was similar for both genders. Furthermore, among men, psychosomatic complaints in adolescence were significantly associated with a lower likelihood of having entered tertiary education 10 years later when adjusting for GPA and social class in adolescence. A similar but non-significant tendency was found among women. The findings suggest that health complaints in adolescence may have long-term consequences in terms of lower educational attainment.

  1. Prediction of molecular crystal structures

    CERN Document Server

    Beyer, T

    2001-01-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of parac...

  2. Toward Protein Tertiary Structure Recognition by means of Associative Memory Hamiltonians

    Science.gov (United States)

    Friedrichs, Mark S.; Wolynes, Peter G.

    1989-10-01

    The statistical mechanics of associative memories and spin glasses suggests ways to design Hamiltonians for protein folding. An associative memory Hamiltonian based on hydrophobicity patterns is shown to have a large capacity for recall and to be capable of recognizing tertiary structure for moderately variant sequences.

  3. A physical approach to protein structure prediction: CASP4 results

    Energy Technology Data Exchange (ETDEWEB)

    Crivelli, Silvia; Eskow, Elizabeth; Bader, Brett; Lamberti, Vincent; Byrd, Richard; Schnabel, Robert; Head-Gordon, Teresa

    2001-02-27

    We describe our global optimization method called Stochastic Perturbation with Soft Constraints (SPSC), which uses information from known proteins to predict secondary structure, but not in the tertiary structure predictions or in generating the terms of the physics-based energy function. Our approach is also characterized by the use of an all atom energy function that includes a novel hydrophobic solvation function derived from experiments that shows promising ability for energy discrimination against misfolded structures. We present the results obtained using our SPSC method and energy function for blind prediction in the 4th Critical Assessment of Techniques for Protein Structure Prediction (CASP4) competition, and show that our approach is more effective on targets for which less information from known proteins is available. In fact our SPSC method produced the best prediction for one of the most difficult targets of the competition, a new fold protein of 240 amino acids.

  4. Structure-Function Study of Tertiary Amines as Switchable Polarity Solvents

    Energy Technology Data Exchange (ETDEWEB)

    Aaron D. Wilson; Frederick F. Stewart

    2014-02-01

    A series of tertiary amines have been screened for their function as switchable polarity solvents (SPS). The relative ratios of tertiary amine and carbonate species as well as maximum possible concentration were determined through quantitative 1H and 13C NMR spectroscopy. The viscosities of the polar SPS solutions were measured and ranged from near water in dilute systems through to gel formation at high concentrations. The van't Hoff indices for SPS solutions were measured through freezing point depression studies as a proxy for osmotic pressures. A new form of SPS with an amine : carbonate ratio significantly greater than unity has been identified. Tertiary amines that function as SPS at ambient pressures appear to be limited to molecules with fewer than 12 carbons. The N,N-dimethyl-n-alkylamine structure has been identified as important to the function of an SPS.

  5. The roles of tertiary amine structure, background organic matter and chloramine species on NDMA formation.

    Science.gov (United States)

    Selbes, Meric; Kim, Daekyun; Ates, Nuray; Karanfil, Tanju

    2013-02-01

    N-nitrosodimethylamine (NDMA), a probable human carcinogen, is a disinfection by-product that has been detected in chloraminated and chlorinated drinking waters and wastewaters. Formation mechanisms and precursors of NDMA are still not well understood. The main objectives of this study were to systematically investigate (i) the effect of tertiary amine structure, (ii) the effect of background natural organic matter (NOM), and (iii) the roles of mono vs. dichloramine species on the NDMA formation. Dimethylamine (DMA) and 20 different tertiary aliphatic and aromatic amines were carefully examined based on their functional groups attached to the basic DMA structure. The wide range (0.02-83.9%) of observed NDMA yields indicated the importance of the structure of tertiary amines, and both stability and electron distribution of the leaving group of tertiary amines on NDMA formation. DMA associated with branched alkyl groups or benzyl like structures having only one carbon between the ring and DMA structure consistently gave higher NDMA yields. Compounds with electron withdrawing groups (EWG) reacted preferentially with monochloramine, whereas compounds with electron donating group (EDG) showed tendency to react with dichloramine to form NDMA. When the selected amines were present in NOM solutions, NDMA formation increased for compounds with EWG while decreased for compounds with EDG. This impact was attributed to the competitions between NOM and amines for chloramine species. The results provided additional information to the commonly accepted mechanism for NDMA formation including chloramine species reacting with tertiary amines and the role of the leaving group on overall NDMA conversion. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. PROGRAM SYSTEM AND INFORMATION METADATA BANK OF TERTIARY PROTEIN STRUCTURES

    Directory of Open Access Journals (Sweden)

    T. A. Nikitin

    2013-01-01

    Full Text Available The article deals with the architecture of metadata storage model for check results of three-dimensional protein structures. Concept database model was built. The service and procedure of database update as well as data transformation algorithms for protein structures and their quality were presented. Most important information about entries and their submission forms to store, access, and delivery to users were highlighted. Software suite was developed for the implementation of functional tasks using Java programming language in the NetBeans v.7.0 environment and JQL to query and interact with the database JavaDB. The service was tested and results have shown system effectiveness while protein structures filtration.

  7. Prediction of molecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, Theresa

    2001-07-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  8. Quaternion representation of RNA sequences and tertiary structures.

    Science.gov (United States)

    Magarshak, Y

    1993-01-01

    A quaternion representation of nucleotides is proposed, with representation of RNA sequences by vectors whose elements are quaternions. Structure and transition matrices in quaternion representation are defined. Correspondence between diagrammatic technique in complex-number and quaternion representation of nucleotides is delineated.

  9. Thermodynamics and kinetics of RNA tertiary structure formation in the junctionless hairpin ribozyme.

    Science.gov (United States)

    White, Neil A; Hoogstraten, Charles G

    2017-09-01

    The hairpin ribozyme consists of two RNA internal loops that interact to form the catalytically active structure. This docking transition is a rare example of intermolecular formation of RNA tertiary structure without coupling to helix annealing. We have used temperature-dependent surface plasmon resonance (SPR) to characterize the thermodynamics and kinetics of RNA tertiary structure formation for the junctionless form of the ribozyme, in which loops A and B reside on separate molecules. We find docking to be strongly enthalpy-driven and to be accompanied by substantial activation barriers for association and dissociation, consistent with the structural reorganization of both internal loops upon complex formation. Comparisons with the parallel analysis of a ribozyme variant carrying a 2'-O-methyl modification at the self-cleavage site and with published data in other systems reveal a surprising diversity of thermodynamic signatures, emphasizing the delicate balance of contributions to the free energy of formation of RNA tertiary structure. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Noncanonical secondary structure stabilizes mitochondrial tRNA(Ser(UCN)) by reducing the entropic cost of tertiary folding.

    Science.gov (United States)

    Mustoe, Anthony M; Liu, Xin; Lin, Paul J; Al-Hashimi, Hashim M; Fierke, Carol A; Brooks, Charles L

    2015-03-18

    Mammalian mitochondrial tRNA(Ser(UCN)) (mt-tRNA(Ser)) and pyrrolysine tRNA (tRNA(Pyl)) fold to near-canonical three-dimensional structures despite having noncanonical secondary structures with shortened interhelical loops that disrupt the conserved tRNA tertiary interaction network. How these noncanonical tRNAs compensate for their loss of tertiary interactions remains unclear. Furthermore, in human mt-tRNA(Ser), lengthening the variable loop by the 7472insC mutation reduces mt-tRNA(Ser) concentration in vivo through poorly understood mechanisms and is strongly associated with diseases such as deafness and epilepsy. Using simulations of the TOPRNA coarse-grained model, we show that increased topological constraints encoded by the unique secondary structure of wild-type mt-tRNA(Ser) decrease the entropic cost of folding by ∼2.5 kcal/mol compared to canonical tRNA, offsetting its loss of tertiary interactions. Further simulations show that the pathogenic 7472insC mutation disrupts topological constraints and hence destabilizes the mutant mt-tRNA(Ser) by ∼0.6 kcal/mol relative to wild-type. UV melting experiments confirm that insertion mutations lower mt-tRNA(Ser) melting temperature by 6-9 °C and increase the folding free energy by 0.8-1.7 kcal/mol in a largely sequence- and salt-independent manner, in quantitative agreement with our simulation predictions. Our results show that topological constraints provide a quantitative framework for describing key aspects of RNA folding behavior and also provide the first evidence of a pathogenic mutation that is due to disruption of topological constraints.

  11. Factors predicting quality of work life among nurses in tertiary-level hospitals, Bangladesh.

    Science.gov (United States)

    Akter, N; Akkadechanunt, T; Chontawan, R; Klunklin, A

    2017-11-03

    This study examined the level of quality of work life and predictability of years of education, monthly income, years of experience, job stress, organizational commitment and work environment on quality of work life among nurses in tertiary-level hospitals in the People's Republic of Bangladesh. There is an acute shortage of nurses worldwide including Bangladesh. Quality of work life is important for quality of patient care and nurse retention. Nurses in Bangladesh are fighting to provide quality care for emerging health problems for the achievement of sustainable development goals. We collected data from 288 randomly selected registered nurses, from six tertiary-level hospitals. All nurses were requested to fill questionnaire consisted of Demographic Data Sheet, Quality of Nursing Work Life Survey, Expanded Nursing Stress Scale, Questionnaire of Organizational Commitment and Practice Environment Scale of the Nursing Work Index. Data were analysed by descriptive statistics and multiple regression. The quality of work life as perceived by nurses in Bangladesh was at moderate level. Monthly income was found as the best predictor followed by work environment, organizational commitment and job stress. A higher monthly income helps nurses to fulfil their personal needs; positive work environment helps to provide quality care to the patients. Quality of work life and predictors measured by self-report only may not reflect the original picture of the quality of work life among nurses. Findings provide information for nursing and health policymakers to develop policies to improve quality of work life among nurses that can contribute to quality of nursing care. This includes the working environment, commitment to the organization and measures to reduce job stress. © 2017 International Council of Nurses.

  12. Depression and catastrophizing predict suicidal ideation in tertiary care patients with interstitial cystitis/bladder pain syndrome

    DEFF Research Database (Denmark)

    Tripp, Dean A; Nickel, J Curtis; Krsmanovic, Adrijana

    2016-01-01

    Introduction: We sought to evaluate psychosocial factors as predictors of suicidal ideation (SI) in a tertiary care outpatient sample of women suffering from interstitial cystitis/bladder pain syndrome (IC/BPS). Methods: The patients are women managed at tertiary care centres (n=190). Controls were...... is the first to implicate multiple psychosocial risk factors over and above IC/BPS-specific symptoms and patient pain experience in SI in women with IC/BPS. Depression in particular is uniquely important in predicting suicidality. These results support a multidisciplinary, proactive approach to IC...

  13. High-throughput NMR assessment of the tertiary structure of food allergens.

    Directory of Open Access Journals (Sweden)

    Stefano Alessandri

    Full Text Available In vitro component-resolved diagnosis of food allergy requires purified allergens that have to meet high standards of quality. These include the authentication of their conformation, which is relevant for the recognition by specific IgE antibodies from allergic patients. Therefore, highly sensitive and reliable screening methods for the analysis of proteins/allergens are required to assess their structural integrity. In the present study one-dimensional 1H Nuclear Magnetic Resonance (1D 1H-NMR analysis was adopted for the assessment of overall structural and dynamic properties and authentication of a set of relevant food allergens, including non-specific lipid transfer proteins from apple, peach and hazelnut, 7/8S seed storage globulins from hazelnut and peanut, 11S seed storage globulins from hazelnut and peanut, caseins from cows' and goats' milk and tropomyosin from shrimp.Two sets of 1D 1H-NMR experiments, using 700 MHz and 600 MHz instruments at 298 K were carried out to determine the presence and the extent of tertiary structure. Structural similarity among members of the individual allergen families was also assessed and changes under thermal stress investigated. The nuclear magnetic resonance (NMR results were compared with structural information available either from the literature, Protein Data Bank entries, or derived from molecular models.1D (1H-NMR analysis of food allergens allowed their classification into molecules with rigid, extended and ordered tertiary structures, molecules without a rigid tertiary structure and molecules which displayed both features. Differences in thermal stability were also detected. In summary, 1D (1H-NMR gives insights into molecular fold of proteins and offers an independent method for assessing structural properties of proteins.

  14. The predictive validity of selection criteria for personnel management students at a tertiary institution

    Directory of Open Access Journals (Sweden)

    S. Swanepoel

    1998-06-01

    Full Text Available Tertiary institutions are confronted daily with the issues surrounding the creation of admission requirements for prospective students that ensure academic success. In a changing South Africa, with its increasing emphasis on individual rights, fair and equitable selection techniques are a priority. The target population for this investigation was four consecutive groups of first-year Personnel Management students who were enrolled for the National Diploma: Personnel Management. The survey population consisted of 293 students. The aim of the study has been achieved by the proof that specific fa :tors of fields of the measure instruments do have prediction validity. These findings can be used with fruit in search of a selection model for academic achievement. Opsomming Tersiere instellings word daagliks gekonfronteer met die kwessies betreffende die daarstel van toelatingsvereistes vir voomemende studente wat akademiese sukses sal verseker. In 'n veranderende Suid-Afnka, met die toenemende klem op mdividuele regte, is regverdige en billike keuringskriteria 'n prioriteit. Die teikenpopulasie vir hierdie ondersoek was vier agtereenvolgende groepe eerstej'aarpersoneelbestuur- studente wat vir die Nasionale Diploma: Personeelbestuur ingeskrvf was. Die opnamepopulasie het uit 293 studente bestaan. Die doel van die studie is bereik deur die bewys dat spesifieke faktore of velde van die meetinstrumente voorspellingsgeldigheid besit. Hierdie bevmdinge kan met vrug gebruik word in die soeke na 'n keuringsmodel vir akademiese prestasies.

  15. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    ) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower......The problem of predicting the three-dimensional structure of a protein given its amino acid sequence is one of the most important open problems in bioinformatics. One of the carbon atoms in amino acids is the C-atom and the overall structure of a protein is often represented by a so-called C......-trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE...

  16. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  17. Alteration of human serum albumin tertiary structure induced by glycation. Spectroscopic study

    Science.gov (United States)

    Szkudlarek, A.; Maciążek-Jurczyk, M.; Chudzik, M.; Równicka-Zubik, J.; Sułkowska, A.

    2016-01-01

    The modification of human serum albumin (HSA) structure by non-enzymatic glycation is one of the underlying factors that contribute to the development of complications of diabetes and neurodegenerative diseases. The aim of the present work was to estimate how glycation of HSA altered its tertiary structure. Changes of albumin conformation were investigated by comparison of glycated (gHSA) and non-glycated human serum albumin (HSA) absorption spectra, red edge excitation shift (REES) and synchronous spectra. Effect of glycation on human serum albumin tertiary structure was also investigated by 1H NMR spectroscopy. Formation of gHSA Advanced Glycation End-products (AGEs) caused absorption of UV-VIS light between 310 nm and 400 nm while for non-glycated HSA in this region no absorbance has been registered. Analysis of red edge excitation shift effect allowed for observation of structural changes of gHSA in the hydrophobic pocket containing the tryptophanyl residue. Moreover changes in the microenvironment of tryptophanyl and tyrosyl residues brought about AGEs on the basis of synchronous fluorescence spectroscopy have been confirmed. The influence of glycation process on serum albumin binding to 5-dimethylaminonaphthalene-1-sulfonamide (DNSA), 2-(p-toluidino) naphthalene-6-sulfonic acid (TNS), has been studied. Fluorescence analysis showed that environment of both binding site I and II is modified by galactose glycation.

  18. Application of Divide and Conquer Extended Genetic Algorithm to Tertiary Protein Structure of Chymotrypsin Inhibitor-2

    Directory of Open Access Journals (Sweden)

    A. Alfaro

    2006-01-01

    Full Text Available Determining the method by which a protein thermodynamically folds and unfolds in three-dimension is one of the most complex and least understood problems in modern biochemistry. Misfolded proteins have been recently linked to diseases including Amyotrophic Lateral Sclerosis and Alzheimer's disease. Because of the large number of parameters involved in defining the tertiary structure of proteins, based on free energy global minimisation, we have developed a new Divide and Conquer (DAC Extended Genetic Algorithm. The approach was applied to explore and verify the energy landscape of protein chymotrypsin inhibitor-2.

  19. Predicting RNA 3D structure using a coarse-grain helix-centered model

    Science.gov (United States)

    Kerpedjiev, Peter; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

    2015-01-01

    A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. PMID:25904133

  20. Steady-state tryptophan fluorescence spectroscopy study to probe tertiary structure of proteins in solid powders.

    Science.gov (United States)

    Sharma, Vikas K; Kalonia, Devendra S

    2003-04-01

    The purpose of this work was to obtain information about protein tertiary structure in solid state by using steady state tryptophan (Trp) fluorescence emission spectroscopy on protein powders. Beta-lactoglobulin (betaLg) and interferon alpha-2a (IFN) powder samples were studied by fluorescence spectroscopy using a front surface sample holder. Two different sets of dried betaLg samples were prepared by vacuum drying of solutions: one containing betaLg, and the other containing a mixture of betaLg and guanidine hydrochloride. Dried IFN samples were prepared by vacuum drying of IFN solutions and by vacuum drying of polyethylene glycol precipitated IFN. The results obtained from solid samples were compared with the emission scans of these proteins in solutions. The emission scans obtained from protein powders were slightly blue-shifted compared to the solution spectra due to the absence of water. The emission scans were red-shifted for betaLg samples dried from solutions containing GuHCl. The magnitude of the shifts in lambda(max) depended on the extent of drying of the samples, which was attributed to the crystallization of GuHCl during the drying process. The shifts in the lambda(max) of the Trp emission spectrum are associated with the changes in the tertiary structure of betaLg. In the case of IFN, the emission scans obtained from PEG-precipitated and dried sample were different compared to the emission scans obtained from IFN in solution and from vacuum dried IFN. The double peaks observed in this sample were attributed to the unfolding of the protein. In the presence of trehalose, the two peaks converged to form a single peak, which was similar to solution emission spectra, whereas no change was observed in the presence of mannitol. We conclude that Trp fluorescence spectroscopy provides a simple and reliable means to characterize Trp microenvironment in protein powders that is related to the tertiary conformation of proteins in the solid state. This study shows

  1. De Novo Chromosome Structure Prediction

    Science.gov (United States)

    di Pierro, Michele; Cheng, Ryan R.; Lieberman-Aiden, Erez; Wolynes, Peter G.; Onuchic, Jose'n.

    Chromatin consists of DNA and hundreds of proteins that interact with the genetic material. In vivo, chromatin folds into nonrandom structures. The physical mechanism leading to these characteristic conformations, however, remains poorly understood. We recently introduced MiChroM, a model that generates chromosome conformations by using the idea that chromatin can be subdivided into types based on its biochemical interactions. Here we extend and complete our previous finding by showing that structural chromatin types can be inferred from ChIP-Seq data. Chromatin types, which are distinct from DNA sequence, are partially epigenetically controlled and change during cell differentiation, thus constituting a link between epigenetics, chromosomal organization, and cell development. We show that, for GM12878 lymphoblastoid cells we are able to predict accurate chromosome structures with the only input of genomic data. The degree of accuracy achieved by our prediction supports the viability of the proposed physical mechanism of chromatin folding and makes the computational model a powerful tool for future investigations.

  2. Predictive structural dynamic network analysis.

    Science.gov (United States)

    Chen, Rong; Herskovits, Edward H

    2015-04-30

    Classifying individuals based on magnetic resonance data is an important task in neuroscience. Existing brain network-based methods to classify subjects analyze data from a cross-sectional study and these methods cannot classify subjects based on longitudinal data. We propose a network-based predictive modeling method to classify subjects based on longitudinal magnetic resonance data. Our method generates a dynamic Bayesian network model for each group which represents complex spatiotemporal interactions among brain regions, and then calculates a score representing that subject's deviation from expected network patterns. This network-derived score, along with other candidate predictors, are used to construct predictive models. We validated the proposed method based on simulated data and the Alzheimer's Disease Neuroimaging Initiative study. For the Alzheimer's Disease Neuroimaging Initiative study, we built a predictive model based on the baseline biomarker characterizing the baseline state and the network-based score which was constructed based on the state transition probability matrix. We found that this combined model achieved 0.86 accuracy, 0.85 sensitivity, and 0.87 specificity. For the Alzheimer's Disease Neuroimaging Initiative study, the model based on the baseline biomarkers achieved 0.77 accuracy. The accuracy of our model is significantly better than the model based on the baseline biomarkers (p-value=0.002). We have presented a method to classify subjects based on structural dynamic network model based scores. This method is of great importance to distinguish subjects based on structural network dynamics and the understanding of the network architecture of brain processes and disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Influence of tertiary structure domain properties on the functionality of apolipoprotein A-I.

    Science.gov (United States)

    Tanaka, Masafumi; Koyama, Mao; Dhanasekaran, Padmaja; Nguyen, David; Nickel, Margaret; Lund-Katz, Sissel; Saito, Hiroyuki; Phillips, Michael C

    2008-02-19

    The tertiary structure of apolipoprotein (apo) A-I and the contributions of structural domains to the properties of the protein molecule are not well defined. We used a series of engineered human and mouse apoA-I molecules in a range of physical-biochemical measurements to address this issue. Circular dichroism measurements of alpha-helix thermal unfolding and fluorescence spectroscopy measurements of 8-anilino-1-napthalenesulfonic acid binding indicate that removal of the C-terminal 54 amino acid residues from human and mouse apoA-I has similar effects; the molecules are only slightly destabilized, and there is a decrease in hydrophobic surface exposure. These results are consistent with both human and mouse apoA-I adopting a two-domain tertiary structure, comprising an N-terminal antiparallel helix bundle domain and a separate less ordered C-terminal domain. Mouse apoA-I is significantly less resistant than human apoA-I to thermal and chemical denaturation; the midpoint of thermal unfolding of mouse apoA-I at 45 degrees C is 15 degrees C lower and the midpoint of guanidine hydrochloride denaturation (D1/2) occurs at 0.5 M as compared to 1.0 M for human apoA-I. These differences reflect the overall greater stability of the helix bundle formed by residues 1-189 in human apoA-I. Measurements of the heats of binding to egg phosphatidylcholine (PC) small unilamellar vesicles and the kinetics of solubilization of dimyristoyl PC multilamellar vesicles indicate that the more stable human helix bundle interacts poorly with lipids as compared to the equivalent mouse N-terminal domain. The C-terminal domain of human apoA-I is much more hydrophobic than that of mouse apoA-I; in the lipid-free state the human C-terminal domain (residues 190-243) is partially alpha-helical and undergoes cooperative unfolding (D1/2 = 0.3 M) whereas the isolated mouse C-terminal domain (residues 187-240) is disordered in dilute solution. The human C-terminal domain binds to lipid surfaces much

  4. Combining PSSM and physicochemical feature for protein structure prediction with support vector machine

    Science.gov (United States)

    Kurniawan, I.; Haryanto, T.; Hasibuan, L. S.; Agmalaro, M. A.

    2017-05-01

    Protein is one of the giant biomolecules that act as the main component of the organism. Protein is formed from building blocks namely amino acids. Hierarchically, the structure of protein is divided into four levels: primary, secondary, tertiary, and quaternary structure. Protein secondary structure is formed by amino acid sequences that would form three-dimensional structures and have information about the tertiary structure and function of proteins. This study used 277,389 protein residue data from enzyme categories. Position-specific scoring matrix (PSSM) profile and physicochemical are used for features. This study developed support vector machine models to predict the protein secondary structure by recognizing patterns of amino acid sequences. The Q3 results showed that the best scores obtained are 93.16% from the dataset that has 260 features with the radial kernel. Combining PSSM and physicochemical feature additions can be used for prediction.

  5. An analytical framework for assessing drug and therapeutics committee structure and work processes in tertiary Brazilian hospitals.

    Science.gov (United States)

    Lima-Dellamora, Elisangela da Costa; Caetano, Rosângela; Gustafsson, Lars L; Godman, Brian B; Patterson, Ken; Osorio-de-Castro, Claudia Garcia Serpa

    2014-09-01

    University teaching hospitals usually provide tertiary care and are subject to early adoption of new technologies, which may compromise healthcare systems when uncritically adopted. Knowledge on the decision-making process - drug selection by drug selection committees or DTCs - is crucial to improve the quality of care. There are no models for studying the selection of drugs in Brazilian healthcare services. This study aims to discuss DTC structure and the processes regarding adoption of medicines in tertiary university hospitals in Brazil and to propose an analytical structure for providing direction for the future. State of the art content regarding drug selection processes and DTC procedures was reviewed in three databases. Information on the medicine selection process in a Brazilian gold standard teaching hospital was collected through observations and a review of existing procedures. A structured discussion on medicine selection and DTC procedures in tertiary hospitals ensued. This discussion resulted in findings that were organized in three dimensions, composing an analytical framework for the application in tertiary Brazilian hospitals (i) motivations for the adoption of drugs; (ii) necessary structural and organizational aspects for decision-making; and (iii) criteria and methods employed by the decision-making process. We believe that the suggested framework is compatible with tertiary Brazilian hospitals, because a gold standard in the country was able to conduct all its procedures in the light of WHO and international recommendations. We hope to contribute in producing knowledge which may hopefully be adopted in tertiary hospitals across Brazil. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

  6. Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images.

    Science.gov (United States)

    Kamal, Md Sarwar; Chowdhury, Linkon; Khan, Mohammad Ibrahim; Ashour, Amira S; Tavares, João Manuel R S; Dey, Nilanjan

    2017-06-01

    Protein structure prediction and analysis are more significant for living organs to perfect asses the living organ functionalities. Several protein structure prediction methods use neural network (NN). However, the Hidden Markov model is more interpretable and effective for more biological data analysis compared to the NN. It employs statistical data analysis to enhance the prediction accuracy. The current work proposed a protein prediction approach from protein images based on Hidden Markov Model and Chapman Kolmogrov equation. Initially, a preprocessing stage was applied for protein images' binarization using Otsu technique in order to convert the protein image into binary matrix. Subsequently, two counting algorithms, namely the Flood fill and Warshall are employed to classify the protein structures. Finally, Hidden Markov model and Chapman Kolmogrov equation are applied on the classified structures for predicting the protein structure. The execution time and algorithmic performances are measured to evaluate the primary, secondary and tertiary protein structure prediction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. The role of precursory structures on Tertiary deformation in the Black Forest—Hegau region

    Science.gov (United States)

    Egli, Daniel; Mosar, Jon; Ibele, Tobias; Madritsch, Herfried

    2017-10-01

    Structural inheritance of preexisting crustal discontinuities is widely accepted to have played a crucial role during the Cenozoic tectonic evolution of the northern Alpine foreland. It is recognised as a process that can strongly influence local fault kinematics and strain patterns. The case study presented herein is dedicated to the tectonic analysis of the Freiburg-Bonndorf-Bodensee Fault Zone (FBBFZ) located at the external margin of the northern Alpine Molasse Basin and extending into the crystalline Black Forest Massif. The structure and kinematics of this crustal-scale fault zone are investigated by means of a regional analysis of locally mapped faults, kinematic analysis of outcrop-scale fractures and slip vector modelling. The exceptional possibility of analysing the fault zone exposed from basement to cover allowed for an evaluation of interaction between precursory structures and subsequent deformation features. The results of this study show that the crystalline basement structures exposed along the FBBFZ had a strong imprint on the map-scale fault pattern observable in the Mesozoic and Tertiary sequences. Kinematic analysis of outcrop-scale fracture systems in the latter units yields evidence for local multi-directional extension and strike-slip faulting during Miocene to recent times. While these observations may evoke the interpretation of a multistage palaeostress history along the FBBFZ, slip vector modelling of a very well exposed FBBFZ segment suggests that the various strain records can alternatively be explained by one single regional stress tensor and be related to superordinate deep-seated strike-slip deformation.

  8. Probing tertiary structure of proteins using single Trp mutations with circular dichroism at low temperature.

    Science.gov (United States)

    Gasymov, Oktay K; Abduragimov, Adil R; Glasgow, Ben J

    2014-01-30

    Trp is the most spectroscopically informative aromatic amino acid of proteins. However, the near-UV circular dichroism (CD) spectrum of Trp is complicated because the intensity and sign of (1)La and (1)Lb bands vary independently. To resolve vibronic structure and gain site-specific information from complex spectra, deconvolution was combined with cooling and site-directed tryptophan substitution. Low temperature near-UV CD was used to probe the local tertiary structure of a loop and α-helix in tear lipocalin. Upon cooling, the enhancement of the intensities of the near-UV CD was not uniform, but depends on the position of Trp in the protein structure. The most enhanced (1)Lb band was observed for Trp at position 124 in the α-helix segment matching the known increased conformational mobility during ligand binding. Some aspects of the CD spectra of W28 and W130 were successfully linked to specific rotamers of Trp previously obtained from fluorescence lifetime measurements. The discussion was based on a framework that the magnitude of the energy differences in local conformations governs the changes in the CD intensities at low temperature. The Trp CD spectral classification of Strickland was modified to facilitate the recognition of pseudo peaks. Near-UV CD spectra harbor abundant information about the conformation of proteins that site directed Trp CD can report.

  9. Probing Tertiary Structure of Proteins Using Single Trp Mutations with Circular Dichroism at Low Temperature

    Science.gov (United States)

    2015-01-01

    Trp is the most spectroscopically informative aromatic amino acid of proteins. However, the near-UV circular dichroism (CD) spectrum of Trp is complicated because the intensity and sign of 1La and 1Lb bands vary independently. To resolve vibronic structure and gain site-specific information from complex spectra, deconvolution was combined with cooling and site-directed tryptophan substitution. Low temperature near-UV CD was used to probe the local tertiary structure of a loop and α-helix in tear lipocalin. Upon cooling, the enhancement of the intensities of the near-UV CD was not uniform, but depends on the position of Trp in the protein structure. The most enhanced 1Lb band was observed for Trp at position 124 in the α-helix segment matching the known increased conformational mobility during ligand binding. Some aspects of the CD spectra of W28 and W130 were successfully linked to specific rotamers of Trp previously obtained from fluorescence lifetime measurements. The discussion was based on a framework that the magnitude of the energy differences in local conformations governs the changes in the CD intensities at low temperature. The Trp CD spectral classification of Strickland was modified to facilitate the recognition of pseudo peaks. Near-UV CD spectra harbor abundant information about the conformation of proteins that site directed Trp CD can report. PMID:24404774

  10. Interaction Of Calcium Phosphate Nanoparticles With Human Chorionic Gonadotropin Modifies Secondary And Tertiary Protein Structure

    Directory of Open Access Journals (Sweden)

    Al-Hakeim Hussein K

    2015-12-01

    Full Text Available Calcium phosphate nanoparticles (CaPNP have good biocompatibility and bioactivity inside human body. In this study, the interaction between CaPNP and human chorionic gonadotropin (hCG was analyzed to determine the changes in the protein structure in the presence of CaPNP and the quantity of protein adsorbed on the CaPNP surface. The results showed a significant adsorption of hCG on the CaPNP nanoparticle surface. The optimal fit was achieved using the Sips isotherm equation with a maximum adsorption capacity of 68.23 µg/mg. The thermodynamic parameters, including ∆H° and ∆G°, of the adsorption process are positive, whereas ∆S° is negative. The circular dichroism results of the adsorption of hCG on CaPNP showed the changes in its secondary structure; such changes include the decomposition of α-helix strand and the increase in β-pleated sheet and random coil percentages. Fluorescence study indicated minimal changes in the tertiary structure near the microenvironment of the aromatic amino acids such as tyrosine and phenyl alanine caused by the interaction forces between the CaPNP and hCG protein. The desorption process showed that the quantity of the hCG desorbed significantly increases as temperature increases, which indicates the weak forces between hCG and the surface.

  11. Stratigraphic structure of the B1 Tertiary tectonostratigraphic unit in eastern Slovenia

    Directory of Open Access Journals (Sweden)

    Bogomir Jelen

    2002-06-01

    Full Text Available High inconsistency and incoherence in the stratigraphy of the Slovenian upper Paleogene and lower Miocene have remained unsolved in the past 150 years. To solve the problem, we tried to rigorously conduct the authentic Galilei’s scientific method. Steps of logical and empirical verification confirmed the existence of the posited B1 Tertiary tectonostratigraphic unit, and a general chronostratigraphic model of new positional relationships of lithologic units resulted from rather good biochronostratigraphic resolution achieved by nannoplankton and planktonic foraminifera biostratigraphy. The application of principles of newly developed fields in science helped us to avoid errors in transmission of messages (to reduce noise from the source (rock to the concept formation,which had been done previously. This in turn has strongly reduced inconsistency andincoherence (high information entropy = uncertainty. The released amount of information enabled us to answer also questions that reached beyond the original difficulty, e.g.: is the tectonostratigraphic structure of eastern Slovenia a manifestation of plate tectonics processes, and of which ones, are theories of continental escape in the Alps and associated dissection and offset of the formerly uniform Slovenian-Hungarian Paleogene basin tenableor not, are then there in the B1 stratigraphic equivalents of the Hungarian Paleogene basin formations, where are the important Eocene / Oligocene, Paleogene / Neogene, Rupelian / Chattian and Kiscellian / Egerian boundaries in Slovenia, and is there acontinuation of the B1 in Croatia and in the Mid-Hungarian tectonic zone?

  12. Predicting RNA 3D structure using a coarse-grain helix-centered model.

    Science.gov (United States)

    Kerpedjiev, Peter; Höner Zu Siederdissen, Christian; Hofacker, Ivo L

    2015-06-01

    A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. © 2015 Kerpedjiev et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  13. Are clinical features able to predict Helicobacter pylori gastritis patterns? Evidence from tertiary centers.

    Science.gov (United States)

    Carabotti, Marilia; Lahner, Edith; Porowska, Barbara; Colacci, Enzo; Trentino, Paolo; Annibale, Bruno; Severi, Carola

    2014-12-01

    Outcome of Helicobacter pylori infection is different according to gastritis extension (i.e. antrum-restricted gastritis or pangastritis). The aim of this study is to evaluate whether different gastritis patterns are associated with specific gastrointestinal symptoms or clinical signs that could be suggestive of the topography of gastritis. 236 consecutive symptomatic outpatients were recruited in two tertiary centers. They filled in a validated and self-administered Rome III modular symptomatic questionnaire, and underwent gastroscopy with histological sampling. 154 patients with Helicobacter pylori infection were included. Clinical presentation did not differ between antrum-restricted gastritis and pangastritis, gastro-esophageal reflux disease being present in 48.2 and 54.1 % of patients and dyspepsia in 51.8 and 45.9 %, respectively. However, pangastritis statistically differed from antrum-restricted gastritis in that the presence of clinical signs (p gastritis pattern whereas their association with signs, accurately detected, is indicative for the presence of pangastritis.

  14. Applications of contact predictions to structural biology

    Directory of Open Access Journals (Sweden)

    Felix Simkovic

    2017-05-01

    Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

  15. The role of big five factors on predicting job crafting propensities amongst administrative employees in a South African tertiary institution

    Directory of Open Access Journals (Sweden)

    Clement Bell

    2016-02-01

    Full Text Available Orientation: Personality provides a foundation for understanding employee job behaviours. It determines and reflects how they respond to their work situations. There is a shortage of previous researches that have specifically dealt with the predictive role of personality on job crafting. Job crafting is also a significantly new concept in the South African work context. It has both positive and negative consequences on employee job behaviours.Research purpose: The present study investigated the role of big five factors on predicting job crafting propensities amongst administrative employees in Alice, South Africa.Motivation for the study: The present study aimed to determine the role of big five factors on predicting job crafting propensities amongst administrative employees. It was premised on previous research that the big five factors are associated with many employee job behaviours.Research approach, design and method: The present study employed a quantitative, crosssectional research design with a sample of 246 administrative employees in Alice, South Africa. A biographical questionnaire, a Big Five Inventory, and a job crafting questionnaire were used to collect data.Main findings: The findings showed that big five factors of Conscientiousness, Extraversion, Agreeableness, Openness to experience and Neuroticism play a significant role in predicting job crafting propensities.Practical implications: The present study suggests that big five factors of Conscientiousness, Extraversion, Agreeableness, Openness to experience and Neuroticism have a predictive role on job crafting behaviours. Managers of tertiary institutions can therefore consider these big five personalities to understand and predict the impacts of their job design strategies on administrative employees’ behaviours.Contribution: The contribution of the study was significant in that it contributed to research literature representing the influence of the big five factors in

  16. Reverse Polarity Magnetized Melt Rocks from the Cretaceous/Tertiary Chicxulub Structure, Yucatan Peninsula, Mexico

    Science.gov (United States)

    Urrutia-Fucugauchi, J.; Marin, Luis; Sharpton, Virgil L.

    1994-01-01

    We report paleomagnetic results for core samples of the breccia and andesitic rocks recovered from the Yucatan-6 Petrolcos Mexicanos exploratory well within the Chicxulub structure (about 60 km SSW from its center), northern Yucatan, Mexico. A previous study has shown that the rocks studied contain high iridium levels and shocked breccia clasts and an Ar/Ar date of 65.2 +/- 0.4 Ma. Andesitic rocks are characterized by stable single-component magnetizations with a mean inclination of -42.6 deg +/- 2.4 deg. Breccias present a complex paleomagnetic record characterized by multivectorial magnetizations with widely different initial NRM inclinations. However, after alternating field demagnetization, well defined characteristic components with upward inclinations are defined. IRM acquisition experiments, comparison of IRM and NRM coercivity spectra and the single component magnetization of the andesitic rocks indicate the occurrence of iron-rich titanomagnetites of single or pseudo-single domain states as the dominant magnetic carriers. Mean inclinations from the andesitic rocks and most of the breccia samples give a mean inclination of about -40 deg to -45 deg, indicating a reverse polarity for the characteristic magnetization that is consistent with geomagnetic chron 29R, which spans the Cretaceous/Tertiary (K/T) boundary. The inclination is also consistent with the expected value (and corresponding paleolatitude) for the site estimated from the reference polar wander curve for North America. We suggest that the characteristic magnetizations for the andesitic and breccia rocks are the result of shock heating at the time of formation of the impact structure and that the age, polarity and pateolatitude are consistent with a time at the K/T boundary.

  17. Tertiary lymphoid structure-associated B cells are key players in anti-tumor immunity

    Directory of Open Access Journals (Sweden)

    Claire eGermain

    2015-02-01

    Full Text Available It is now admitted that the immune system plays a major role in tumor control. Besides the existence of tumor-specific T cells and B cells, many studies have demonstrated that high numbers of tumor-infiltrating lymphocytes are associated with good clinical outcome. In addition, not only the density but also the organization of tumor-infiltrating immune cells has been shown to determine patient survival. Indeed, more and more studies describe the development within the tumor microenvironment of tertiary lymphoid structures (TLS, whose presence has a positive impact on tumor prognosis. TLS are transient ectopic lymphoid aggregates displaying the same organization and functionality as canonical secondary lymphoid organs, with T cell-rich and B cell-rich areas that are sites for the differentiation of effector and memory T cells and B cells. However, factors favoring the emergence of such structures within tumors still need to be fully characterized. In this review, we survey the state of the art of what is known about the general organization, induction and functionality of TLS during chronic inflammation, and more especially in cancer, with a particular focus on the B cell compartment. We detail the role played by TLS B cells in anti-tumor immunity, both as antigen-presenting cells and tumor antigen-specific antibody-secreting cells, and raise the question of the capacity of chemotherapeutic and immunotherapeutic agents to induce the development of TLS within tumors. Finally, we explore how to take advantage of our knowledge on TLS B cells to develop new therapeutic tools.

  18. Tertiary Lymphoid Structure-Associated B Cells are Key Players in Anti-Tumor Immunity.

    Science.gov (United States)

    Germain, Claire; Gnjatic, Sacha; Dieu-Nosjean, Marie-Caroline

    2015-01-01

    It is now admitted that the immune system plays a major role in tumor control. Besides the existence of tumor-specific T cells and B cells, many studies have demonstrated that high numbers of tumor-infiltrating lymphocytes are associated with good clinical outcome. In addition, not only the density but also the organization of tumor-infiltrating immune cells has been shown to determine patient survival. Indeed, more and more studies describe the development within the tumor microenvironment of tertiary lymphoid structures (TLS), whose presence has a positive impact on tumor prognosis. TLS are transient ectopic lymphoid aggregates displaying the same organization and functionality as canonical secondary lymphoid organs, with T-cell-rich and B-cell-rich areas that are sites for the differentiation of effector and memory T cells and B cells. However, factors favoring the emergence of such structures within tumors still need to be fully characterized. In this review, we survey the state of the art of what is known about the general organization, induction, and functionality of TLS during chronic inflammation, and more especially in cancer, with a particular focus on the B-cell compartment. We detail the role played by TLS B cells in anti-tumor immunity, both as antigen-presenting cells and tumor antigen-specific antibody-secreting cells, and raise the question of the capacity of chemotherapeutic and immunotherapeutic agents to induce the development of TLS within tumors. Finally, we explore how to take advantage of our knowledge on TLS B cells to develop new therapeutic tools.

  19. Reverse polarity magnetized melt rocks from the cretaceous/tertiary chicxulub structure, Yucatan peninsula, Mexico

    Science.gov (United States)

    Urrutia-Fucugauchi, J.; Marin, Luis; Sharpton, Virgil L.

    1994-10-01

    We report paleomagnetic results for core samples of the breccia and andesitic rocks recovered from the Yucatan-6 Petroleos Mexicanos exploratory well within the Chicxulub structure (about 60 km SSW from its center), northern Yucatan, Mexico. A previous study has shown that the rocks studied contain high iridium levels and shocked breccia clasts and an Ar/Ar date of 65.2 ± 0.4 Ma (Sharpton et al., 1992). Andesitic rocks are characterized by stable single-component magnetizations with a mean inclination of -42.6° ± 2.4°. Breccias present a complex paleomagnetic record characterized by multivectorial magnetizations with widely different initial NRM inclinations. However, after alternating field demagnetization, well defined characteristic components with upward inclinations are defined. IRM acquisition experiments, comparison of IRM and NRM coercivity spectra and the single component magnetization of the andesitic rocks indicate the occurrence of iron-rich titanomagnetites of single or pseudo-single domain states as the dominant magnetic carriers. Mean inclinations from the andesitic rocks and most of the breccia samples give a mean inclination of about -40° to -45°, indicating a reverse polarity for the characteristic magnetization that is consistent with geomagnetic chron 29R, which spans the Cretaceous/Tertiary (K/T) boundary. The inclination is also consistent with the expected value (and corresponding paleolatitude) for the site estimated from the reference polar wander curve for North America. We suggest that the characteristic magnetizations for the andesitic and breccia rocks are the result of shock heating at the time of formation of the impact structure and that the age, polarity and paleolatitude are consistent with a time at the K/T boundary.

  20. Facilities management: Structuring a body of knowledge for continuing and tertiary education in South Africa

    Directory of Open Access Journals (Sweden)

    A. C. Hauptfleisch

    2010-01-01

    is exacerbated by the fact that very little is being done at the level of continuing education and formal tertiary education in South Africa. The limited attempts in this regard are furthermore taking place in isolation, with practically no dialogue between the limited facilities management industry and the providers of the limited education that is available.Although the study that was undertaken did not have the objective to create comprehensive interaction between the existing role-players, the stated problems were addressed by involving the industry, participants in continuing education programmes and other role-players in the condensed research problem as stated below. The problem at hand is firstly to extract, from the present practice of facilities management, a knowledge framework and secondly to formulate the results in terms of suitable continuing and tertiary education programmes to address the shortcomings in South Africa. Research was therefore undertaken to address the structuring of educational programmes. The methodology applied comprised a comprehensive literature survey and three quantified and qualified data surveys, the latter conducted amongst facilities management practitioners, primarily the perceived beneficiaries of such programmes. These surveys provided information that led to the resultant educational activities stated below. The most important aspects that were determined were the following: It was possible to create and test amongst facilities management practitioners a diagrammatic presentation that contextualised facilities management. The literature survey, including international and South African sources, contributed towards compiling a primary knowledge framework for facilities management. The perceived value of the contents of a continuing education programme that had been attended by numerous groups of delegates over a number of years was established. A proposed tertiary education programme was presented to practitioners

  1. Computational predictions of zinc oxide hollow structures

    Science.gov (United States)

    Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

    2018-03-01

    Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

  2. Stochastic Extreme Load Predictions for Marine Structures

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    1999-01-01

    Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non-linearity of the ......Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non...

  3. Structure Prediction of Membrane Proteins

    Science.gov (United States)

    Hu, Xiche

    Membrane proteins play a central role in many cellular and physiological processes. It is estimated that integral membrane proteins make up about 20-30% of the proteome (Krogh et al., 2001b; Stevens and Arkin, 2000; von Heijne, 1999). They are essential mediators of material and information transfer across cell membranes. Their functions include active and passive transport of molecules into and out of cells and organelles; transduction of energy among various forms (light, electrical, and chemical energy); as well as reception and transduction of chemical and electrical signals across membranes (Avdonin, 2005; Bockaert et al., 2002; Pahl, 1999; Rehling et al., 2004; Stack et al., 1995). Identifying these transmembrane (TM) proteins and deciphering their molecular mechanisms, then, is of great importance, particularly as applied to biomedicine. Membrane proteins are the targets of a large number of pharmacologically and toxicologically active substances, and are directly involved in their uptake, metabolism, and clearance (Bettler et al., 1998; Cohen, 2002; Heusser and Jardieu, 1997; Tibes et al., 2005; Xu et al., 2005). Despite the importance of membrane proteins, the knowledge of their high-resolution structures and mechanisms of action has lagged far behind in comparison to that of water-soluble proteins: less than 1% of all three-dimensional structures deposited in the Protein Data Bank are of membrane proteins. This unfortunate disparity stems from difficulties in overexpression and the crystallization of membrane proteins (Grisshammer and Tate, 1995; Michel, 1991).

  4. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

    Andersen, Claus A.; Bohr, Henrik; Brunak, Søren

    2001-01-01

    structures. Single sequence prediction of the new three category assignment gives an overall prediction improvement of 3.1% and 5.1%, compared to the DSSP assignment and schemes where the helix category consists of a-helix and 3(10)-helix, respectively. These results were achieved using a standard feed-forward...

  5. Structural information from OH stretching frequencies—IV. The fixation effect in saturated tertiary alcohols

    NARCIS (Netherlands)

    Lutz, E.T.G.; Maas, J.H. van der

    1980-01-01

    The OH stretching bands of several tertiary alcohols with a (partly) rigid skeleton have been investigated. It is demonstrated that in CCl4 the observed OH vibration is related to the distances OH … X, where X stands for atoms close to OH. The effect of fixation of β-CH2 groups proves to be

  6. Predicting complex mineral structures using genetic algorithms.

    Science.gov (United States)

    Mohn, Chris E; Kob, Walter

    2015-10-28

    We show that symmetry-adapted genetic algorithms are capable of finding the ground state of a range of complex crystalline phases including layered- and incommensurate super-structures. This opens the way for the atomistic prediction of complex crystal structures of functional materials and mineral phases.

  7. Phocid Seal Leptin: Tertiary Structure and Hydrophobic Receptor Binding Site Preservation during Distinct Leptin Gene Evolution

    Science.gov (United States)

    Hammond, John A.; Hauton, Chris; Bennett, Kimberley A.; Hall, Ailsa J.

    2012-01-01

    The cytokine hormone leptin is a key signalling molecule in many pathways that control physiological functions. Although leptin demonstrates structural conservation in mammals, there is evidence of positive selection in primates, lagomorphs and chiropterans. We previously reported that the leptin genes of the grey and harbour seals (phocids) have significantly diverged from other mammals. Therefore we further investigated the diversification of leptin in phocids, other marine mammals and terrestrial taxa by sequencing the leptin genes of representative species. Phylogenetic reconstruction revealed that leptin diversification was pronounced within the phocid seals with a high dN/dS ratio of 2.8, indicating positive selection. We found significant evidence of positive selection along the branch leading to the phocids, within the phocid clade, but not over the dataset as a whole. Structural predictions indicate that the individual residues under selection are away from the leptin receptor (LEPR) binding site. Predictions of the surface electrostatic potential indicate that phocid seal leptin is notably different to other mammalian leptins, including the otariids. Cloning the grey seal leptin binding domain of LEPR confirmed that this was structurally conserved. These data, viewed in toto, support a hypothesis that phocid leptin divergence is unlikely to have arisen by random mutation. Based upon these phylogenetic and structural assessments, and considering the comparative physiology and varying life histories among species, we postulate that the unique phocid diving behaviour has produced this selection pressure. The Phocidae includes some of the deepest diving species, yet have the least modified lung structure to cope with pressure and volume changes experienced at depth. Therefore, greater surfactant production is required to facilitate rapid lung re-inflation upon surfacing, while maintaining patent airways. We suggest that this additional surfactant requirement

  8. Phocid seal leptin: tertiary structure and hydrophobic receptor binding site preservation during distinct leptin gene evolution.

    Directory of Open Access Journals (Sweden)

    John A Hammond

    Full Text Available The cytokine hormone leptin is a key signalling molecule in many pathways that control physiological functions. Although leptin demonstrates structural conservation in mammals, there is evidence of positive selection in primates, lagomorphs and chiropterans. We previously reported that the leptin genes of the grey and harbour seals (phocids have significantly diverged from other mammals. Therefore we further investigated the diversification of leptin in phocids, other marine mammals and terrestrial taxa by sequencing the leptin genes of representative species. Phylogenetic reconstruction revealed that leptin diversification was pronounced within the phocid seals with a high dN/dS ratio of 2.8, indicating positive selection. We found significant evidence of positive selection along the branch leading to the phocids, within the phocid clade, but not over the dataset as a whole. Structural predictions indicate that the individual residues under selection are away from the leptin receptor (LEPR binding site. Predictions of the surface electrostatic potential indicate that phocid seal leptin is notably different to other mammalian leptins, including the otariids. Cloning the grey seal leptin binding domain of LEPR confirmed that this was structurally conserved. These data, viewed in toto, support a hypothesis that phocid leptin divergence is unlikely to have arisen by random mutation. Based upon these phylogenetic and structural assessments, and considering the comparative physiology and varying life histories among species, we postulate that the unique phocid diving behaviour has produced this selection pressure. The Phocidae includes some of the deepest diving species, yet have the least modified lung structure to cope with pressure and volume changes experienced at depth. Therefore, greater surfactant production is required to facilitate rapid lung re-inflation upon surfacing, while maintaining patent airways. We suggest that this additional

  9. Computational Methods for Protein Structure Prediction and Modeling Volume 2: Structure Prediction

    CERN Document Server

    Xu, Ying; Liang, Jie

    2007-01-01

    Volume 2 of this two-volume sequence focuses on protein structure prediction and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

  10. Alpha complexes in protein structure prediction

    DEFF Research Database (Denmark)

    Winter, Pawel; Fonseca, Rasmus

    2015-01-01

    Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computations......-complexes and kinetic a-complexes in protein related problems (e.g., protein structure prediction and protein-ligand docking) deserves furhter investigation.)......-complexes from scratch for every configuration encountered during the search for the native structure would make this approach hopelessly slow. However, it is argued that kinetic a-complexes can be used to reduce the computational effort of determining the potential energy when "moving" from one configuration...

  11. Predicting structure in nonsymmetric sparse matrix factorizations

    Energy Technology Data Exchange (ETDEWEB)

    Gilbert, J.R. (Xerox Palo Alto Research Center, CA (United States)); Ng, E.G. (Oak Ridge National Lab., TN (United States))

    1992-10-01

    Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

  12. Predicting RNA Structure Using Mutual Information

    DEFF Research Database (Denmark)

    Freyhult, E.; Moulton, V.; Gardner, P. P.

    2005-01-01

    Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...... is often conserved in evolution, the well known, but underused, mutual information measure for identifying covarying sites in an alignment can be useful for identifying structural elements. This article presents MIfold, a MATLAB(R) toolbox that employs mutual information, or a related covariation measure......, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...

  13. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...

  14. Prevalence of Ventilatory Conditions for Dynamic Fluid Responsiveness Prediction in 2 Tertiary Intensive Care Units.

    Science.gov (United States)

    Mendes, Pedro V; Rodrigues, Bruno N; Miranda, Leandro C; Zampieri, Fernando G; Queiroz, Eduardo L; Schettino, Guilherme; Azevedo, Luciano C; Park, Marcelo; Taniguchi, Leandro U

    2016-05-01

    Dynamic parameters for fluid responsiveness obtained from heart-lung interaction during invasive mechanical ventilation require specific conditions not always present in intensive care unit (ICU) patients. The aim of this study was to examine the prevalence of these conditions in critically ill patients. We conducted a prospective observational study in 2 medical-surgical ICUs. We evaluated whether it would be possible to measure dynamic indices of fluid responsiveness when fluid expansion was administered. We recorded whether the patients were in controlled invasive mechanical ventilation with tidal volume >8 mL/kg and without arrhythmias. The proportion of patients who fulfilled these conditions was recorded. A post hoc subgroup analyses by terciles of Simplified Acute Physiology Score 3 (SAPS3) were performed. A total of 826 fluid challenges were undertaken in 424 patients during the study. The use of controlled mechanical ventilation with tidal volume > 8 mL/kg and without arrhythmias occurred in only 2.9% of the patients at the time of fluid challenge episodes. There was an increase in the prevalence of these conditions as the severity of the patients also increased: lower tercile of SAPS3 (0%), intermediate tercile (2%), and higher tercile (6.9%; P parameters for predicting fluid responsiveness in ICU may have restricted applicability in daily practice, even in more severe patients, due to low prevalence of required conditions. © The Author(s) 2014.

  15. Prediction of Wound Healing in Diabetic Foot Ulcers: an Observational Study in Tertiary Hospital in Indonesia

    Directory of Open Access Journals (Sweden)

    Pradana Soewondo

    2017-04-01

    Full Text Available Aim: to evaluate the role of clinical characteristics, functional markers of vasodilation, inflammatory response, and atherosclerosis in predicting wound healing in diabetic foot ulcer. Methods: a cohort study (February – October 2010 was conducted from 40 subjects with acute diabetic foot ulcer at clinical ward of Dr. Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia. Each subject underwent at least two variable measurements, i.e. during inflammatory phase and proliferation phase. The studied variables were clinical characteristics, complete peripheral blood count (CBC and differential count, levels of HbA1c, ureum, creatinine, lipid profile, fasting blood glucose (FBG, marker of endothelial dysfunction (asymmetric dimethylarginine/ADMA, endothelin-1/ET-1, and flow-mediated dilation/FMD of brachial artery, and marker of vascular calcification (osteoprotegerin/OPG. Results: median of time achieving 50% granulation tissue in our study was 21 days. There were nine factors that contribute in the development of 50% granulation tissue, i.e. family history of diabetes mellitus (DM, previous history of wound, wound area, duration of existing wound, captopril and simvastatin medications, levels of ADMA, ET-1, and OPG. There were three out of the nine factors that significantly correlated with wound healing, i.e. wound area, OPG levels, and simvastatin medications. Conclusion: in acute diabetic foot ulcers, wound area and OPG levels had positive correlation with wound healing, whereas simvastatin medications had negative correlation with wound healing.

  16. Major structural controls on the distribution of pre-Tertiary rocks, Nevada Test Site vicinity, southern Nevada

    Energy Technology Data Exchange (ETDEWEB)

    Cole, J.C.

    1998-10-23

    The lateral and vertical distributions of Proterozoic and Paleozoic sedimentary rocks in southern Nevada are the combined products of original stratigraphic relationships and post-depositional faults and folds. This map compilation shows the distribution of the pre-Tertiary rocks in the region including and surrounding the Nevada Test Site. It is based on considerable new evidence from detailed geologic mapping, biostratigraphic control, sedimentological analysis, and a review of regional map relationships. Proterozoic and Paleozoic rocks of the region record paleogeographic transitions between continental shelf depositional environments on the east and deeper-water slope-facies depositional environments on the west. Middle Devonian and Mississippian sequences, in particular, show strong lateral facies variations caused by contemporaneous changes in the western margin of North America during the Antler orogeny. Sections of rock that were originally deposited in widely separated facies localities presently lie in close proximity. These spatial relationships chiefly result from major east- and southeast-directed thrusts that deformed the region in Permian or later time. Somewhat younger contractional structures are identified within two irregular zones that traverse the region. These folds and thrusts typically verge toward the west and northwest and overprint the relatively simple pattern of the older contractional terranes. Local structural complications are significant near these younger structures due to the opposing vergence and due to irregularities in the previously folded and faulted crustal section. Structural and stratigraphic discontinuities are identified on opposing sides of two north-trending fault zones in the central part of the compilation region north of Yucca Flat. The origin and significance of these zones are enigmatic because they are largely covered b Tertiary and younger deposits. These faults most likely results from significant lateral

  17. GRASr2 evaluation of aliphatic acyclic and alicyclic terpenoid tertiary alcohols and structurally related substances used as flavoring ingredients.

    Science.gov (United States)

    Marnett, Lawrence J; Cohen, Samuel M; Fukushima, Shoji; Gooderham, Nigel J; Hecht, Stephen S; Rietjens, Ivonne M C M; Smith, Robert L; Adams, Timothy B; Bastaki, Maria; Harman, Christie L; McGowen, Margaret M; Taylor, Sean V

    2014-04-01

    This publication is the 1st in a series of publications by the Expert Panel of the Flavor and Extract Manufacturers Assoc. summarizing the Panel's 3rd re-evaluation of Generally Recognized as Safe (GRAS) status referred to as the GRASr2 program. In 2011, the Panel initiated a comprehensive program to re-evaluate the safety of more than 2700 flavor ingredients that have previously met the criteria for GRAS status under conditions of intended use as flavor ingredients. Elements that are fundamental to the safety evaluation of flavor ingredients include exposure, structural analogy, metabolism, pharmacokinetics, and toxicology. Flavor ingredients are evaluated individually and in the context of the available scientific information on the group of structurally related substances. Scientific data relevant to the safety evaluation of the use of aliphatic acyclic and alicyclic terpenoid tertiary alcohols and structurally related substances as flavoring ingredients are evaluated. The group of aliphatic acyclic and alicyclic terpenoid tertiary alcohols and structurally related substances was reaffirmed as GRAS (GRASr2) based, in part, on their rapid absorption, metabolic detoxication, and excretion in humans and other animals; their low level of flavor use; the wide margins of safety between the conservative estimates of intake and the no-observed-adverse effect levels determined from subchronic studies and the lack of significant genotoxic and mutagenic potential. © 2014 Institute of Food Technologists®

  18. Contact prediction for beta and alpha-beta proteins using integer linear optimization and its impact on the first principles 3D structure prediction method ASTRO-FOLD.

    Science.gov (United States)

    Rajgaria, R; Wei, Y; Floudas, C A

    2010-06-01

    An integer linear optimization model is presented to predict residue contacts in beta, alpha + beta, and alpha/beta proteins. The total energy of a protein is expressed as sum of a C(alpha)-C(alpha) distance dependent contact energy contribution and a hydrophobic contribution. The model selects contact that assign lowest energy to the protein structure as satisfying a set of constraints that are included to enforce certain physically observed topological information. A new method based on hydrophobicity is proposed to find the beta-sheet alignments. These beta-sheet alignments are used as constraints for contacts between residues of beta-sheets. This model was tested on three independent protein test sets and CASP8 test proteins consisting of beta, alpha + beta, alpha/beta proteins and it was found to perform very well. The average accuracy of the predictions (separated by at least six residues) was approximately 61%. The average true positive and false positive distances were also calculated for each of the test sets and they are 7.58 A and 15.88 A, respectively. Residue contact prediction can be directly used to facilitate the protein tertiary structure prediction. This proposed residue contact prediction model is incorporated into the first principles protein tertiary structure prediction approach, ASTRO-FOLD. The effectiveness of the contact prediction model was further demonstrated by the improvement in the quality of the protein structure ensemble generated using the predicted residue contacts for a test set of 10 proteins.

  19. Contact Prediction for Beta and Alpha-Beta Proteins Using Integer Linear Optimization and its Impact on the First Principles 3D Structure Prediction Method ASTRO-FOLD

    Science.gov (United States)

    Rajgaria, R.; Wei, Y.; Floudas, C. A.

    2010-01-01

    An integer linear optimization model is presented to predict residue contacts in β, α + β, and α/β proteins. The total energy of a protein is expressed as sum of a Cα – Cα distance dependent contact energy contribution and a hydrophobic contribution. The model selects contacts that assign lowest energy to the protein structure while satisfying a set of constraints that are included to enforce certain physically observed topological information. A new method based on hydrophobicity is proposed to find the β-sheet alignments. These β-sheet alignments are used as constraints for contacts between residues of β-sheets. This model was tested on three independent protein test sets and CASP8 test proteins consisting of β, α + β, α/β proteins and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) was approximately 61%. The average true positive and false positive distances were also calculated for each of the test sets and they are 7.58 Å and 15.88 Å, respectively. Residue contact prediction can be directly used to facilitate the protein tertiary structure prediction. This proposed residue contact prediction model is incorporated into the first principles protein tertiary structure prediction approach, ASTRO-FOLD. The effectiveness of the contact prediction model was further demonstrated by the improvement in the quality of the protein structure ensemble generated using the predicted residue contacts for a test set of 10 proteins. PMID:20225257

  20. Comparative Sequence and Structure Analysis Reveals the Conservation and Diversity of Nucleotide Positions and Their Associated Tertiary Interactions in the Riboswitches

    Science.gov (United States)

    Appasamy, Sri D.; Ramlan, Effirul Ikhwan; Firdaus-Raih, Mohd

    2013-01-01

    The tertiary motifs in complex RNA molecules play vital roles to either stabilize the formation of RNA 3D structure or to provide important biological functionality to the molecule. In order to better understand the roles of these tertiary motifs in riboswitches, we examined 11 representative riboswitch PDB structures for potential agreement of both motif occurrences and conservations. A total of 61 unique tertiary interactions were found in the reference structures. In addition to the expected common A-minor motifs and base-triples mainly involved in linking distant regions the riboswitch structures three highly conserved variants of A-minor interactions called G-minors were found in the SAM-I and FMN riboswitches where they appear to be involved in the recognition of the respective ligand’s functional groups. From our structural survey as well as corresponding structure and sequence alignments, the agreement between motif occurrences and conservations are very prominent across the representative riboswitches. Our analysis provide evidence that some of these tertiary interactions are essential components to form the structure where their sequence positions are conserved despite a high degree of diversity in other parts of the respective riboswitches sequences. This is indicative of a vital role for these tertiary interactions in determining the specific biological function of riboswitch. PMID:24040136

  1. Protein Structure Prediction with Evolutionary Algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Hart, W.E.; Krasnogor, N.; Pelta, D.A.; Smith, J.

    1999-02-08

    Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

  2. Prevalence and predictive factors of birth traumas in neonates presenting to the children emergency center of a tertiary center in Southwest, Nigeria

    OpenAIRE

    Babayemi O Osinaike; Labake O.O Akinseye; Olubusola R Akiyode; Chinwe Anyaebunam; Olusola Kushimo

    2017-01-01

    Background: Although the majority of birth injuries are minor and often unreported, occasionally birth injuries may be so severe as to be fatal or leave the child with a permanent disability or even death.Objective: This study aimed to document the patterns and predictive factors of birth injuries in neonates presenting at the emergency center of a tertiary hospital in South west, Nigeria. Patients And Methods: This was a cross-sectional study of neonates who presented at the Olikoye Ransome-...

  3. Prediction of backbone dihedral angles and protein secondary structure using support vector machines

    Directory of Open Access Journals (Sweden)

    Hirst Jonathan D

    2009-12-01

    Full Text Available Abstract Background The prediction of the secondary structure of a protein is a critical step in the prediction of its tertiary structure and, potentially, its function. Moreover, the backbone dihedral angles, highly correlated with secondary structures, provide crucial information about the local three-dimensional structure. Results We predict independently both the secondary structure and the backbone dihedral angles and combine the results in a loop to enhance each prediction reciprocally. Support vector machines, a state-of-the-art supervised classification technique, achieve secondary structure predictive accuracy of 80% on a non-redundant set of 513 proteins, significantly higher than other methods on the same dataset. The dihedral angle space is divided into a number of regions using two unsupervised clustering techniques in order to predict the region in which a new residue belongs. The performance of our method is comparable to, and in some cases more accurate than, other multi-class dihedral prediction methods. Conclusions We have created an accurate predictor of backbone dihedral angles and secondary structure. Our method, called DISSPred, is available online at http://comp.chem.nottingham.ac.uk/disspred/.

  4. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    DEFF Research Database (Denmark)

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna

    2014-01-01

    Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful appl...... on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together....

  5. Does sleep duration predict metabolic risk in obese adolescents attending tertiary services? A cross-sectional study.

    Science.gov (United States)

    Sung, Valerie; Beebe, Dean W; Vandyke, Rhonda; Fenchel, Matthew C; Crimmins, Nancy A; Kirk, Shelley; Hiscock, Harriet; Amin, Raouf; Wake, Melissa

    2011-07-01

    To determine, in a clinical sample of obese adolescents, whether shorter sleep duration is associated with metabolic risk and obesity severity. Cross-sectional study. Tertiary care weight-management clinic in Cincinnati, OH, USA. 133 obese adolescents aged 10-16.9 years. N/A. Multifaceted sleep duration data were examined with fasting venipuncture and anthropometric data collected during clinical care. presence of metabolic syndrome. waist circumference, triglycerides, HDL-cholesterol, blood pressure, glucose, insulin resistance (HOMA-IR), and body mass index (BMI). Sleep duration by (1) parent-report, (2) self-report, and (3) multi-night actigraphy. Relationships between sleep duration and each outcome were examined via regression models, adjusted for potential confounders. Regardless of how measured, sleep duration showed no strong association with metabolic syndrome (OR 1.1 to 1.5, P = 0.2 to 0.8), BMI (β -0.03 to -0.01, P = 0.2 to 0.8), or most other outcomes. Lower triglycerides were predicted by shorter sleep duration by self-report (β 12.3, P = 0.01) and actigraphy (β 13.6, P = 0.03), and shorter parent-reported sleep duration was associated with higher HDL-cholesterol (β = -2.7, P = 0.002). Contrary to expectations, sleep duration was not associated with metabolic outcomes, and showed limited associations with lipid profiles. Although inadequate sleep may affect other areas of functioning, it appears premature to expect that lengthening sleep will improve BMI or metabolic outcomes in clinical samples of obese adolescents.

  6. Structural network efficiency predicts conversion to dementia

    NARCIS (Netherlands)

    Tuladhar, A.; van Uden, I.W.M.; Rutten-Jacobs, L.C.A.; van der Holst, H.; van Norden, A.; de Laat, K.; Dijk, E.; Claassen, J.A.H.R.; Kessels, R.P.C.; Markus, H.S.; Norris, David Gordon; de Leeuw, F.E.

    2016-01-01

    Objective: To examine whether structural network connectivity at baseline predicts incident all-cause dementia in a prospective hospital-based cohort of elderly participants with MRI evidence of small vessel disease (SVD). Methods: A total of 436 participants from the Radboud University Nijmegen

  7. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Aboul-Magd Mohammed O

    2009-07-01

    protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition. Conclusion Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3 is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline.

  8. RNA secondary structure prediction using soft computing.

    Science.gov (United States)

    Ray, Shubhra Sankar; Pal, Sankar K

    2013-01-01

    Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

  9. Prevalence and factors predictive of intraocular fungal infection in patients with fungemia at an academic urban tertiary care center

    Directory of Open Access Journals (Sweden)

    Geraymovych E

    2015-09-01

    Full Text Available Elena Geraymovych,1 Joseph H Conduff,2 Puneet S Braich,3 Christopher T Leffler,3 Vikram S Brar3 1Department of Ophthalmology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 2Virginia Commonwealth University School of Medicine, 3Department of Ophthalmology, Virginia Commonwealth University, Richmond, VA, USA Objective: To report the prevalence and to identify factors predictive of intraocular infection in patients with fungemia receiving prophylactic antifungal therapy. Methods: A retrospective review of patients who received prophylactic antifungal therapy and a dilated fundus examination at an academic urban tertiary care center from 2000 to 2007. Basic demographic information, fungal species grown, antifungal agent(s used, number of positive blood culture specimens, visual acuity, visual symptoms, and known risks of disseminated candidiasis were noted. Logistic regression analysis was used to determine the factors significantly associated with intraocular fungal infection. Results: A total of 132 patients with positive fungemia culture were requested to have ophthalmology consults. The prevalence of ocular infection was 6.9% (N=9. All nine patients were infected with Candida species. Undergoing gastrointestinal (GI surgery within the prior 6 months was significantly related to developing intraocular infection, with an odds ratio of 18.5 (95% confidence interval, 15.1–24.3; P=0.002. Having ≥3 positive fungal blood cultures was also a significant risk factor, with an odds ratio of 2.6 (95% confidence interval, 1.8–3.7; P=0.03. Among 40 patients having GI surgery, eight (20.0% had intraocular fungal disease, compared with one of 92 patients (1.1% not having GI surgery. Among 125 patients with a negative baseline examination result, two of 32 patients (6.3%, who had recent GI surgery, subsequently developed fungal ocular disease, compared with 0 of 93 patients (0%, who did not have recent GI surgery. Conclusion

  10. VfoldCPX Server: Predicting RNA-RNA Complex Structure and Stability.

    Science.gov (United States)

    Xu, Xiaojun; Chen, Shi-Jie

    RNA-RNA interactions are essential for genomic RNA dimerization, mRNA splicing, and many RNA-related gene expression and regulation processes. The prediction of the structure and folding stability of RNA-RNA complexes is a problem of significant biological importance and receives substantial interest in the biological community. The VfoldCPX server provides a new web interface to predict the two-dimensional (2D) structures of RNA-RNA complexes from the nucleotide sequences. The VfoldCPX server has several novel advantages including the ability to treat RNAs with tertiary contacts (crossing base pairs) such as loop-loop kissing interactions and the use of physical loop entropy parameters. Based on a partition function-based algorithm, the server enables prediction for structure with and without tertiary contacts. Furthermore, the server outputs a set of energetically stable structures, ranked by their stabilities. The results allow users to gain extensive physical insights into RNA-RNA interactions and their roles in RNA function. The web server is freely accessible at "http://rna.physics.missouri.edu/vfoldCPX".

  11. Predicting structured metadata from unstructured metadata.

    Science.gov (United States)

    Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

    2016-01-01

    Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data-defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. © The Author(s) 2016. Published by Oxford University Press.

  12. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    KAUST Repository

    Marcatili, Paolo

    2014-11-06

    © 2014 Nature America, Inc. All rights reserved. Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (~10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

  13. Energy efficiency trends in the tertiary sector impact of structural changes. Study case from France (1986-1997)

    Energy Technology Data Exchange (ETDEWEB)

    Bosseboeuf, D. [Agence de l' Environnement et de la Maitrise de l' Energie, ADEME, 75 - Paris (France); Chateau, B. [ENERDATA SA, 38 - Gieres - Grenoble (France)

    2000-02-01

    The tertiary (service) sector is the one that experienced the most rapid growth of its energy consumption since 1986, along with the transport sector. But electricity alone has captured almost all the energy consumption increase on that period, resulting in a quasi stabilisation of the CO2 emissions of this sector. Very few policy measures to improve energy efficiency have been taken in that sector, except the implementation of insulation standards for new buildings in 1989 (standards currently under revision; new standards expected in January 2001). From an economic viewpoint, the tertiary sector has been the driving force of the GDP and employment since 1986. The objective of this paper is to review the energy consumption patterns in that sector and presents a diagnosis on the energy efficiency trends. To which extent energy consumption growth is explained by the economic growth of the sector? Are there significant differences among sub-sectors as to the economic and energy growth? How the structural changes in this sector do explain the modification of its energy consumption pattern? Which consequences can be drawn as to the energy efficiency evolution? Supported by which technical and behavioural changes? (authors)

  14. Defining proximity relationships in the tertiary structure of the dopamine transporter. Identification of a conserved glutamic acid as a third coordinate in the endogenous Zn(2+)-binding site

    DEFF Research Database (Denmark)

    Løland, Claus Juul; Norregaard, L; Gether, U

    1999-01-01

    , high affinity Zn(2+)-binding site. To achieve further insight into the tertiary organization of hDAT, we set out to identify additional residues involved in Zn(2+) binding and subsequently to engineer artificial Zn(2+)-binding sites. Ten aspartic acids and glutamic acids, predicted...

  15. Protein-protein complex structure predictions by multimeric threading and template recombination

    Science.gov (United States)

    Mukherjee, Srayanta; Zhang, Yang

    2011-01-01

    Summary The number of protein-protein complex structures is nearly 6-times smaller than that of tertiary structures in PDB which limits the power of homology-based approaches to complex structure modeling. We present a new threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 non-homologous dimeric proteins, which can successfully detect correct templates for half of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from non-homologous templates. PMID:21742262

  16. A Structured Approach to Sediment Transport Prediction

    Science.gov (United States)

    Wilcock, Peter

    2013-04-01

    There are two types of sediment transport problem. One, flow competence, concerns the conditions that initiate motion of grains on the bed surface. The other, transport capacity, concerns the rate at which sediment is transported and involves sediment found locally on the bed as well as sediment delivered from upstream. The two problems can be linked by the critical stress for incipient motion. A model for critical stress is used directly to predict flow competence. The Ashida/Parker similarity hypothesis provides a useful approximation of transport rates and incorporates local sediment effects entirely via the reference stress, a surrogate for critical stress. Although critical stress is key to both predictions, its application is quite different. The difficult problem of wash load - sizes found in transport in quantities much larger than would be predicted by their presence in the bed - makes the distinction clear and challenges any attempt to predict transport rate from a competence-like approach based on hydraulics and bed material alone. The Shields Diagram and a hiding function provide models for critical stress for uni-size and mixed-size sediment. In addition to grain size - both absolute and relative - other factors alter the critical stress of bed material. These include the proportion of fine-grained material, the aging or freshening of bed material via biologically mediated processes, and the development of bed structure at flows close to the critical stress. Although these factors directly influence the prediction of competent flows, their effect on transport rate is less clear. As flow increases, to what extent does bed strengthening through structuring and other mechanisms persist in dampening transport rate? The answer involves the condition of partial transport in which some grains in a size fraction are active and others remain inactive. Tracing of grains in the flume and field provide guidance on the domain of partial transport and thus on the

  17. Predictive modeling of post bioprinting structure formation.

    Science.gov (United States)

    McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

    2014-03-21

    Cellular particle dynamics (CPD) is an effective computational method to describe the shape evolution and biomechanical relaxation processes in systems composed of micro tissues such as multicellular aggregates. Therefore, CPD is a useful tool to predict the outcome of postprinting structure formation in bioprinting. The predictive power of CPD has been demonstrated for multicellular systems composed of identical volume-conserving spherical and cylindrical bioink units. Experiments and computer simulations were related through an independently developed theoretical formalism based on continuum mechanics. Here we generalize the CPD formalism to (i) include non-identical bioink particles often used in specific bioprinting applications, (ii) describe the more realistic experimental situation in which during the post-printing structure formation via the fusion of spherical bioink units the volume of the system decreases, and (iii) directly connect CPD simulations to the corresponding experiments without the need of the intermediate continuum theory inherently based on simplifying assumptions.

  18. Prediction of secondary structural content of proteins from their amino acid composition alone. II. The paradox with secondary structural class.

    Science.gov (United States)

    Eisenhaber, F; Frömmel, C; Argos, P

    1996-06-01

    The success rates reported for secondary structural class prediction with different methods are contradictory. On one side, the problem of recognizing the secondary structural class of a protein knowing only its amino acid composition appears completely solved by simply applying jury decision with an elliptically scaled distance function. Chou and coworkers repeatedly (see Crit. Rev. Biochem. Mol. Biol. 30:275-349, 1995) published prediction accuracies near 100%. On the other hand, traditional secondary structure prediction techniques achieve success rates of about 70% for the secondary structural state per residue and about 75% for structural class only with extensive input information (full sequence of the query protein, its amino acid composition and length, multiple alignments with homologous sequences). In this article, we resolve the paradox and consider (1) the question of the secondary structural class definition, (2) the role of the representativity of the test set of protein tertiary structure for the current state of the Protein Data Bank (PDB); and (3) we estimate the real impact of amino acid composition on secondary structural class. We formulate three objective criteria for a reasonable definition of secondary structural classes and show that only the criterion of Nakashima et al. (J. Biochem. 99:153-162, 1986) complies with all of them. Only this definition matches the distribution of secondary structural content in representative PDB subsets, whereas other criteria leave many proteins (up to 65% of all PDB entries) simply unassigned. We review critically specialized secondary-structural class prediction methods, especially those of Chou and coworkers, which claim almost 100% accuracy using only amino acid composition, and resolve the paradox that these prediction accuracies are better than those from secondary structure predictions from multiple alignments. We show (i) that these techniques rely on a preselection of test sets which removes

  19. Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

    Science.gov (United States)

    Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

    2018-01-01

    T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

  20. Upgrading and downgrading of prostate cancer from biopsy to radical prostatectomy: incidence and predictive factors using the modified Gleason grading system and factoring in tertiary grades.

    Science.gov (United States)

    Epstein, Jonathan I; Feng, Zhaoyong; Trock, Bruce J; Pierorazio, Phillip M

    2012-05-01

    Prior studies assessing the correlation of Gleason score (GS) at needle biopsy and corresponding radical prostatectomy (RP) predated the use of the modified Gleason scoring system and did not factor in tertiary grade patterns. To assess the relation of biopsy and RP grade in the largest study to date. A total of 7643 totally embedded RP and corresponding needle biopsies (2004-2010) were analyzed according to the updated Gleason system. All patients underwent prostate biopsy prior to RP. The relation of upgrading or downgrading to patient and cancer characteristics was compared using the chi-square test, Student t test, and multivariable logistic regression. A total of 36.3% of cases were upgraded from a needle biopsy GS 5-6 to a higher grade at RP (11.2% with GS 6 plus tertiary). Half of the cases had matching GS 3+4=7 at biopsy and RP with an approximately equal number of cases downgraded and upgraded at RP. With biopsy GS 4+3=7, RP GS was almost equally 3+4=7 and 4+3=7. Biopsy GS 8 led to an almost equal distribution between RP GS 4+3=7, 8, and 9-10. A total of 58% of the cases had matching GS 9-10 at biopsy and RP. In multivariable analysis, increasing age (pfactoring in multiple variables including the number of positive cores and the maximum percentage of cancer per core, the concordance indexes were not sufficiently high to justify the use of nomograms for predicting upgrading and downgrading for the individual patient. Almost 20% of RP cases have tertiary patterns. A needle biopsy can sample a tertiary higher Gleason pattern in the RP, which is then not recorded in the standard GS reporting, resulting in an apparent overgrading on the needle biopsy. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  1. A protein structural classes prediction method based on predicted secondary structure and PSI-BLAST profile.

    Science.gov (United States)

    Ding, Shuyan; Li, Yan; Shi, Zhuoxing; Yan, Shoujiang

    2014-02-01

    Knowledge of protein secondary structural classes plays an important role in understanding protein folding patterns. In this paper, 25 features based on position-specific scoring matrices are selected to reflect evolutionary information. In combination with other 11 rational features based on predicted protein secondary structure sequences proposed by the previous researchers, a 36-dimensional representation feature vector is presented to predict protein secondary structural classes for low-similarity sequences. ASTRALtraining dataset is used to train and design our method, other three low-similarity datasets ASTRALtest, 25PDB and 1189 are used to test the proposed method. Comparisons with other methods show that our method is effective to predict protein secondary structural classes. Stand alone version of the proposed method (PSSS-PSSM) is written in MATLAB language and it can be downloaded from http://letsgob.com/bioinfo_PSSS_PSSM/. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  2. Predicting structures in the Zone of Avoidance

    Science.gov (United States)

    Sorce, Jenny G.; Colless, Matthew; Kraan-Korteweg, Renée C.; Gottlöber, Stefan

    2017-11-01

    The Zone of Avoidance (ZOA), whose emptiness is an artefact of our Galaxy dust, has been challenging observers as well as theorists for many years. Multiple attempts have been made on the observational side to map this region in order to better understand the local flows. On the theoretical side, however, this region is often simply statistically populated with structures but no real attempt has been made to confront theoretical and observed matter distributions. This paper takes a step forward using constrained realizations (CRs) of the local Universe shown to be perfect substitutes of local Universe-like simulations for smoothed high-density peak studies. Far from generating completely `random' structures in the ZOA, the reconstruction technique arranges matter according to the surrounding environment of this region. More precisely, the mean distributions of structures in a series of constrained and random realizations (RRs) differ: while densities annihilate each other when averaging over 200 RRs, structures persist when summing 200 CRs. The probability distribution function of ZOA grid cells to be highly overdense is a Gaussian with a 15 per cent mean in the random case, while that of the constrained case exhibits large tails. This implies that areas with the largest probabilities host most likely a structure. Comparisons between these predictions and observations, like those of the Puppis 3 cluster, show a remarkable agreement and allow us to assert the presence of the, recently highlighted by observations, Vela supercluster at about 180 h-1 Mpc, right behind the thickest dust layers of our Galaxy.

  3. De novo membrane protein structure prediction.

    Science.gov (United States)

    Nugent, Timothy

    2015-01-01

    Recent advances in identifying residue-residue contacts from large multiple sequence alignments have enabled impressive gains to be made in the field of protein structure prediction. In this chapter, we discuss these advances and provide a step-by-step guide to applying the latest tools to the de novo modelling of alpha-helical transmembrane proteins. As a practical example, we demonstrate the process of building an accurate 3D model of a G protein-coupled receptor, correctly orientated in the membrane, using only its primary protein sequence.

  4. Predictive Models for Normal Fetal Cardiac Structures.

    Science.gov (United States)

    Krishnan, Anita; Pike, Jodi I; McCarter, Robert; Fulgium, Amanda L; Wilson, Emmanuel; Donofrio, Mary T; Sable, Craig A

    2016-12-01

    Clinicians rely on age- and size-specific measures of cardiac structures to diagnose cardiac disease. No universally accepted normative data exist for fetal cardiac structures, and most fetal cardiac centers do not use the same standards. The aim of this study was to derive predictive models for Z scores for 13 commonly evaluated fetal cardiac structures using a large heterogeneous population of fetuses without structural cardiac defects. The study used archived normal fetal echocardiograms in representative fetuses aged 12 to 39 weeks. Thirteen cardiac dimensions were remeasured by a blinded echocardiographer from digitally stored clips. Studies with inadequate imaging views were excluded. Regression models were developed to relate each dimension to estimated gestational age (EGA) by dates, biparietal diameter, femur length, and estimated fetal weight by the Hadlock formula. Dimension outcomes were transformed (e.g., using the logarithm or square root) as necessary to meet the normality assumption. Higher order terms, quadratic or cubic, were added as needed to improve model fit. Information criteria and adjusted R 2 values were used to guide final model selection. Each Z-score equation is based on measurements derived from 296 to 414 unique fetuses. EGA yielded the best predictive model for the majority of dimensions; adjusted R 2 values ranged from 0.72 to 0.893. However, each of the other highly correlated (r > 0.94) biometric parameters was an acceptable surrogate for EGA. In most cases, the best fitting model included squared and cubic terms to introduce curvilinearity. For each dimension, models based on EGA provided the best fit for determining normal measurements of fetal cardiac structures. Nevertheless, other biometric parameters, including femur length, biparietal diameter, and estimated fetal weight provided results that were nearly as good. Comprehensive Z-score results are available on the basis of highly predictive models derived from gestational

  5. Evidence for the residual tertiary structure in the urea-unfolded form of bacteriophage T5 endolysin.

    Science.gov (United States)

    Kutyshenko, Victor P; Prokhorov, Dmitry A; Mikoulinskaia, Galina V; Molochkov, Nikolai V; Paskevich, Svetlana I; Uversky, Vladimir N

    2017-05-01

    Using high-resolution NMR spectroscopy, we studied peculiarities of the unfolding process of the bacteriophage T5 endolysin (EndoT5) by strong denaturants. It was shown that in the absence of zinc ions this protein is mostly unfolded in the solution of 8 M urea or 6 M guanidine hydrochloride. However, in the presence of zinc ions EndoT5 unfolding can be achieved only in acidic solutions (at pH  4.0 NMR spectra of the metal-bound protein (Zn 2+ -Ca 2+ -EndoT5 or Zn 2+ -EndoT5 complexes) exhibit a few chemical shifts characteristic of the native or native-like proteins. Our data, including the pH-titration curve with the pK of ~5, suggested involvement of the zinc-binding histidines in the stabilization of this protein. Up-field signals that appear in the NMR spectra of apo-EndoT5 in the presence of high concentrations of strong denaturants are probably derived from the amino acid residues included in the formation of structured hydrophobic cluster, which likely corresponds to the 81-93 region of EndoT5 and contains some residual tertiary structure. It is possible also that this hydrophobic fragment serves as a foundation for the formation of structured cluster in the unfolded state.

  6. Crystal structure prediction supported with diffraction data

    Science.gov (United States)

    Tsujimoto, Naoto; Adachi, Daiki; Todo, Synge; Akashi, Ryosuke; Tsuneyuki, Shinji

    Atomistic computer simulation is of growing importance in the study of unidentified crystals, although prediction or determination of complicated structure is still a challenging problem due to its many degrees of freedom. Here we propose to utilize experimentally available data of powder diffraction to support and accelerate the structure simulation. In so-called direct-space methods for structure determination from powder diffraction, simplified interatomic potential energy or some other physical constraints are often used in combination with the cost function defined by diffraction data. On the other hand, we formulate a cost function called ``crystallinity'' to support simulation with accurate interatomic potential energy. Since the crystallinity here is defined as the sum of the diffraction intensities only at the peak positions detected in experiments, this method is applicable to low-quality diffraction data such as those obtained at high pressures. We apply this method to well-known polymorphs of SiO2 with up to 96 atoms in the simulation cell to find that it reproduces the correct structures efficiently with information of a very limited number of diffraction peaks.

  7. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information.

    Science.gov (United States)

    Biasini, Marco; Bienert, Stefan; Waterhouse, Andrew; Arnold, Konstantin; Studer, Gabriel; Schmidt, Tobias; Kiefer, Florian; Gallo Cassarino, Tiziano; Bertoni, Martino; Bordoli, Lorenza; Schwede, Torsten

    2014-07-01

    Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces generate reliable models without the need for complex software packages or downloading large databases. Here, we describe the latest version of the SWISS-MODEL expert system for protein structure modelling. The SWISS-MODEL template library provides annotation of quaternary structure and essential ligands and co-factors to allow for building of complete structural models, including their oligomeric structure. The improved SWISS-MODEL pipeline makes extensive use of model quality estimation for selection of the most suitable templates and provides estimates of the expected accuracy of the resulting models. The accuracy of the models generated by SWISS-MODEL is continuously evaluated by the CAMEO system. The new web site allows users to interactively search for templates, cluster them by sequence similarity, structurally compare alternative templates and select the ones to be used for model building. In cases where multiple alternative template structures are available for a protein of interest, a user-guided template selection step allows building models in different functional states. SWISS-MODEL is available at http://swissmodel.expasy.org/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Making the bend: DNA tertiary structure and protein-DNA interactions.

    Science.gov (United States)

    Harteis, Sabrina; Schneider, Sabine

    2014-07-14

    DNA structure functions as an overlapping code to the DNA sequence. Rapid progress in understanding the role of DNA structure in gene regulation, DNA damage recognition and genome stability has been made. The three dimensional structure of both proteins and DNA plays a crucial role for their specific interaction, and proteins can recognise the chemical signature of DNA sequence ("base readout") as well as the intrinsic DNA structure ("shape recognition"). These recognition mechanisms do not exist in isolation but, depending on the individual interaction partners, are combined to various extents. Driving force for the interaction between protein and DNA remain the unique thermodynamics of each individual DNA-protein pair. In this review we focus on the structures and conformations adopted by DNA, both influenced by and influencing the specific interaction with the corresponding protein binding partner, as well as their underlying thermodynamics.

  9. Theoretical prediction of familial amyotrophic lateral sclerosis missense mutation effects on Cu/Zn superoxide dismutase structural stability

    Energy Technology Data Exchange (ETDEWEB)

    Potier, M.; Tu, Y. [Universite de Montreal, Quebec (Canada)

    1994-09-01

    Cu/Zn superoxide dismutase (SOD) deficiency is associated with the progressive paralytic disorder familial amyotrophic lateral sclerosis (FALS). Fifteen missense mutations in the SOD gene were identified in several patients. These mutations may prevent correct promoter folding or hamper homodimer formation necessary for SOD activity. To understand the effect of the missense mutations on SOD structure and function, we used a theoretical analysis of structural effects based on two predictive methods using the modeled tertiary structure of human SOD. The first method uses the TORSO program which optimizes amino acid side-chains repacking in both wild-type and mutant SODs and calculates protein internal packing energy. The second method uses a hydrophobicity scale of the amino acid residues and considers both solvent accessibility and hydrophobic nature of residue substitutions to compute a stabilization energy change ({delta}E). These predictive methods have been tested in 187 single and multiple missense mutants of 8 proteins (T4 lysozyme, human carbonic anhydrase II, chymotrypsin inhibitor 2, f1 gene V protein, barnase, {lambda}-repressor, chicken and human lysozymes) with experimentally determined thermostability. The overall prediction accuracy with these proteins was 88%. Analysis of FALS missense mutations {delta}E predicts that 14 of 15 mutations destabilize the SOD structure. The other missense mutation is located at the homodimer interface and may hinder dimer formation. This approach is applicable to any protein with known tertiary structure to predict missense mutation effects on protein stability.

  10. A Nuclear Magnetic Resonance Study of Secondary and Tertiary Structure in Yeast tRNAPhe

    NARCIS (Netherlands)

    Robillard, G.T.; Tarr, C.E.; Vosman, F.; Reid, B.R.

    1977-01-01

    We present experimental evidence which confirms recently proposed ring current prediction methods for assigning hydrogen-bond proton nuclear magnetic resonance (NMR) spectra from tRNA. The evidence is a series of temperature-dependent studies on yeast tRNAPhe monitoring both the high- and low-field

  11. Knowledge base and neural network approach for protein secondary structure prediction.

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. A comprehensive comparison of comparative RNA structure prediction approaches

    DEFF Research Database (Denmark)

    Gardner, P. P.; Giegerich, R.

    2004-01-01

    Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene...

  13. Predictive learning with structured (grouped) data.

    Science.gov (United States)

    Liang, Lichen; Cai, Feng; Cherkassky, Vladimir

    2009-01-01

    Many applications of machine learning involve sparse and heterogeneous data. For example, estimation of diagnostic models using patients' data from clinical studies requires effective integration of genetic, clinical and demographic data. Typically all heterogeneous inputs are properly encoded and mapped onto a single feature vector, used for estimating a classifier. This approach, known as standard inductive learning, is used in most application studies. Recently, several new learning methodologies have emerged. For instance, when training data can be naturally separated into several groups (or structured), we can view model estimation for each group as a separate task, leading to a Multi-Task Learning framework. Similarly, a setting where the training data are structured, but the objective is to estimate a single predictive model (for all groups), leads to the Learning with Structured Data and SVM+ methodology recently proposed by Vapnik [(2006). Empirical inference science afterword of 2006. Springer]. This paper describes a biomedical application of these new data modeling approaches for modeling heterogeneous data using several medical data sets. The characteristics of group variables are analyzed. Our comparisons demonstrate the advantages and limitations of these new approaches, relative to standard inductive SVM classifiers.

  14. Protein structure prediction using basin-hopping

    Science.gov (United States)

    Prentiss, Michael C.; Wales, David J.; Wolynes, Peter G.

    2008-06-01

    Associative memory Hamiltonian structure prediction potentials are not overly rugged, thereby suggesting their landscapes are like those of actual proteins. In the present contribution we show how basin-hopping global optimization can identify low-lying minima for the corresponding mildly frustrated energy landscapes. For small systems the basin-hopping algorithm succeeds in locating both lower minima and conformations closer to the experimental structure than does molecular dynamics with simulated annealing. For large systems the efficiency of basin-hopping decreases for our initial implementation, where the steps consist of random perturbations to the Cartesian coordinates. We implemented umbrella sampling using basin-hopping to further confirm when the global minima are reached. We have also improved the energy surface by employing bioinformatic techniques for reducing the roughness or variance of the energy surface. Finally, the basin-hopping calculations have guided improvements in the excluded volume of the Hamiltonian, producing better structures. These results suggest a novel and transferable optimization scheme for future energy function development.

  15. A protocol for computer-based protein structure and function prediction.

    Science.gov (United States)

    Roy, Ambrish; Xu, Dong; Poisson, Jonathan; Zhang, Yang

    2011-11-03

    Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

  16. Tertiary rifting and its related structural development of the southern offshore Korea

    Science.gov (United States)

    Sunwoo, Don

    2017-04-01

    Analysis of regional multi-channel seismic data integrated with exploratory wells has helped to investigate the structural and stratigraphic evolution of the southern offshore Korea. The northeast-southwest trending Taiwan Sinzi Fold Belt separates the area into two regions, the northern East China Sea Shelf Basin and the northern Okinawa Trough, with different structural features. The northern East China Sea Shelf Basin is characterized by Hupijiao Rise and Oligocene and late Miocene folded structures, whereas no uplifted and folded structures exist in the northern Okinawa Trough. However, the basement structure in both regions is much similar. The structure is characterized by a series of half-grabens and tilted fault blocks bounded by listric faults associated with rifting activity. These structures are more distinct in the northern Okinawa Trough. Rifting and extension in the northern East China Sea Shelf Basin, probably initiated in the Paleogene, resulted in a series of grabens and half-grabens. In the late Oligocene, the area west of the Hupijiao Rise experienced compressional tectonism and subsequent erosion flattened the area. In the early Miocene, extension and rifting resumed and the Hupijiao Rise uplifted locally. A second phase of compression, probably triggered by changes in plate motions caused large-scale uplift and folding in the eastern part of the area during the late Miocene. Subsequent erosion leveled the area including the Taiwan Sinzi Fold Belt, resulting in a significant regional unconformity. In contrast, the rifting and extension in the northern Okinawa Trough probably began in late Miocene and continued until early Pleistocene. The most active rifting occurred during early Pliocene and the rifting seems to become weaker during late Pliocene and early Pleistocene. The late Miocene unconformity that eroded the Taiwan Sinzi Fold Belt forms a conformable surface in the northern Okinawa Trough

  17. Structure Prediction for Multicomponent Materials Using Biminima

    Science.gov (United States)

    Schebarchov, D.; Wales, D. J.

    2014-10-01

    The potential energy surface of a heteroparticle system will contain points that are local minima in both coordinate space and permutation space for the different species. We introduce the term biminima to describe these special points, and we formulate a deterministic scheme for finding them. Our search algorithm generates a converging sequence of particle-identity swaps, each accompanied by a number of local geometry relaxations. For selected binary atomic clusters of size N=NA+NB≤98, convergence to a biminimum on average takes 3NANB relaxations, and the number of biminima grows with the preference for mixing. The new framework unifies continuous and combinatorial optimization, providing a powerful tool for structure prediction and rational design of multicomponent materials.

  18. Incorporation of crystallographic temperature factors in the statistical analysis of protein tertiary structures.

    Science.gov (United States)

    Bott, R; Frane, J

    1990-08-01

    A method to identify statistically significant differences between equivalent atoms in two closely related protein X-ray crystallographic structures is described. This method uses the linear relationship found between the logarithm of the distance between equivalent atoms and their mean temperature factor to determine, by linear regression, the expected difference and variance.

  19. Pneumococcal capsular polysaccharide structure predicts serotype prevalence.

    Directory of Open Access Journals (Sweden)

    Daniel M Weinberger

    2009-06-01

    Full Text Available There are 91 known capsular serotypes of Streptococcus pneumoniae. The nasopharyngeal carriage prevalence of particular serotypes is relatively stable worldwide, but the host and bacterial factors that maintain these patterns are poorly understood. Given the possibility of serotype replacement following vaccination against seven clinically important serotypes, it is increasingly important to understand these factors. We hypothesized that the biochemical structure of the capsular polysaccharides could influence the degree of encapsulation of different serotypes, their susceptibility to killing by neutrophils, and ultimately their success during nasopharyngeal carriage. We sought to measure biological differences among capsular serotypes that may account for epidemiological patterns. Using an in vitro assay with both isogenic capsule-switch variants and clinical carriage isolates, we found an association between increased carriage prevalence and resistance to non-opsonic neutrophil-mediated killing, and serotypes that were resistant to neutrophil-mediated killing tended to be more heavily encapsulated, as determined by FITC-dextran exclusion. Next, we identified a link between polysaccharide structure and carriage prevalence. Significantly, non-vaccine serotypes that have become common in vaccinated populations tend to be those with fewer carbons per repeat unit and low energy expended per repeat unit, suggesting a novel biological principle to explain patterns of serotype replacement. More prevalent serotypes are more heavily encapsulated and more resistant to neutrophil-mediated killing, and these phenotypes are associated with the structure of the capsular polysaccharide, suggesting a direct relationship between polysaccharide biochemistry and the success of a serotype during nasopharyngeal carriage and potentially providing a method for predicting serotype replacement.

  20. PredictProtein--an open resource for online prediction of protein structural and functional features

    NARCIS (Netherlands)

    Yachdav, G.; Kloppmann, E.; Kajan, L.; Hecht, M.; Goldberg, T.; Hamp, T.; Honigschmid, P.; Schafferhans, A.; Roos, M.; Bernhofer, M.; Richter, L.; Ashkenazy, H.; Punta, M.; Schlessinger, A.; Bromberg, Y.; Schneider, R.; Vriend, G.; Sander, C.; Ben-Tal, N.; Rost, B.

    2014-01-01

    PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility,

  1. Regulation of Neurexin 1[beta] Tertiary Structure and Ligand Binding through Alternative Splicing

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Kaiser C.; Kuczynska, Dorota A.; Wu, Irene J.; Murray, Beverly H.; Sheckler, Lauren R.; Rudenko, Gabby (Michigan)

    2008-08-04

    Neurexins and neuroligins play an essential role in synapse function, and their alterations are linked to autistic spectrum disorder. Interactions between neurexins and neuroligins regulate inhibitory and excitatory synaptogenesis in vitro through a splice-insert signaling code. In particular, neurexin 1{beta} carrying an alternative splice insert at site SS{number_sign}4 interacts with neuroligin 2 (found predominantly at inhibitory synapses) but much less so with other neuroligins (those carrying an insert at site B and prevalent at excitatory synapses). The structure of neurexin 1{beta}+SS{number_sign}4 reveals dramatic rearrangements to the 'hypervariable surface', the binding site for neuroligins. The splice insert protrudes as a long helix into space, triggers conversion of loop {beta}10-{beta}11 into a helix rearranging the binding site for neuroligins, and rearranges the Ca{sup 2+}-binding site required for ligand binding, increasing its affinity. Our structures reveal the mechanism by which neurexin 1{beta} isoforms acquire neuroligin splice isoform selectivity.

  2. The role of inherited rifted lithospheric structure on middle Cretaceous orogeny and Tertiary-present extension, North American Cordillera

    Science.gov (United States)

    Tikoff, Basil; Kelso, Paul; Fayon, Annia; Gaschnig, Richard; Vervoort, Jeff; Stetson-Lee, Tor; Byerly, Ad

    2017-04-01

    While the Eastern North American margin exhibits evidence of the rifted margin on subsequent deformation, this record is more obscure along the western Cordilleran margin. We recently conducted paleomagnetic and geochronologic analyses along the abrupt, boundary between cratonic North American and accreted terranes in Idaho. In this location, the abrupt boundary is designated by geochemical gradients (Sr, Nd, O) that are spatially coincident with major, regional-scale (western Idaho, Ahsahka) shear zones. The boundary is oriented NS in central-southern Idaho, and then abruptly changes 90° near Orofino, ID, to become EW oriented. Recent paleomagnetic data indicates that 30° clockwise rotation of the entire margin occurred post 85 Ma. Reconstruction of this rotation orients the margins at 060 (transform) and 330 (extensional), parallel to the inferred orientation of the Precambrian rifted margin elsewhere in the US Cordillera. The geometry would cause a structural syntaxis during northward (right-lateral) translation of accreted terranes. Northward terrane motion at 100 Ma result in dextral transpressional kinematics along the 330-oriented western Idaho shear zone and contractional deformation in the EW-oriented Ahsahka shear zone (Cretaceous orientations) in this syntaxis. This middle Cretaceous orogeny occurs at the other major structural syntaxis, south of the Sierra Nevada batholith in southeastern California, as a result of a 100 Ma worldwide plate re-organization. The Idaho syntaxis also acts as a fulcrum for Tertiary-present rotation, explaining the current displacement field in the northern US Cordillera. Overall, the study indicates that the inherited Precambrian rifted margin of the North American Cordillera exhibited a significant influence on subsequent deformation, despite overprinting of abundant magmatism, margin parallel terrane translation, and subsequent rotation.

  3. General overview on structure prediction of twilight-zone proteins.

    Science.gov (United States)

    Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

    2015-09-04

    Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

  4. Assessing the accuracy of template-based structure prediction metaservers by comparison with structural genomics structures.

    Science.gov (United States)

    Gront, Dominik; Grabowski, Marek; Zimmerman, Matthew D; Raynor, John; Tkaczuk, Karolina L; Minor, Wladek

    2012-12-01

    The explosion of the size of the universe of known protein sequences has stimulated two complementary approaches to structural mapping of these sequences: theoretical structure prediction and experimental determination by structural genomics (SG). In this work, we assess the accuracy of structure prediction by two automated template-based structure prediction metaservers (genesilico.pl and bioinfo.pl) by measuring the structural similarity of the predicted models to corresponding experimental models determined a posteriori. Of 199 targets chosen from SG programs, the metaservers predicted the structures of about a fourth of them "correctly." (In this case, "correct" was defined as placing more than 70 % of the alpha carbon atoms in the model within 2 Å of the experimentally determined positions.) Almost all of the targets that could be modeled to this accuracy were those with an available template in the Protein Data Bank (PDB) with more than 25 % sequence identity. The majority of those SG targets with lower sequence identity to structures in the PDB were not predicted by the metaservers with this accuracy. We also compared metaserver results to CASP8 results, finding that the models obtained by participants in the CASP competition were significantly better than those produced by the metaservers.

  5. APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction.

    Science.gov (United States)

    Borguesan, Bruno; Barbachan e Silva, Mariel; Grisci, Bruno; Inostroza-Ponta, Mario; Dorn, Márcio

    2015-12-01

    Tertiary protein structure prediction is one of the most challenging problems in structural bioinformatics. Despite the advances in algorithm development and computational strategies, predicting the folded structure of a protein only from its amino acid sequence remains as an unsolved problem. We present a new computational approach to predict the native-like three-dimensional structure of proteins. Conformational preferences of amino acid residues and secondary structure information were obtained from protein templates stored in the Protein Data Bank and represented as an Angle Probability List. Two knowledge-based prediction methods based on Genetic Algorithms and Particle Swarm Optimization were developed using this information. The proposed method has been tested with twenty-six case studies selected to validate our approach with different classes of proteins and folding patterns. Stereochemical and structural analysis were performed for each predicted three-dimensional structure. Results achieved suggest that the Angle Probability List can improve the effectiveness of metaheuristics used to predicted the three-dimensional structure of protein molecules by reducing its conformational search space. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Are specialized servers better at predicting protein structures than ...

    African Journals Online (AJOL)

    This research study answers the question that technology is the best for predicting protein structures. Stand-alone software only depend on protein structure prediction algorithms, while web servers consult a number of other sources such as meta servers and protein data banks to produce a protein structure achieved ...

  7. Computational Prediction of acyl-coA Binding Proteins Structure in Brassica napus.

    Science.gov (United States)

    Raboanatahiry, Nadia Haingotiana; Lu, Guangyuan; Li, Maoteng

    2015-01-01

    Acyl-coA binding proteins could transport acyl-coA esters from plastid to endoplasmic reticulum, prior to fatty acid biosynthesis, leading to the formation of triacylglycerol. The structure and the subcellular localization of acyl-coA binding proteins (ACBP) in Brassica napus were computationally predicted in this study. Earlier, the structure analysis of ACBPs was limited to the small ACBPs, the current study focused on all four classes of ACBPs. Physicochemical parameters including the size and the length, the intron-exon structure, the isoelectric point, the hydrophobicity, and the amino acid composition were studied. Furthermore, identification of conserved residues and conserved domains were carried out. Secondary structure and tertiary structure of ACBPs were also studied. Finally, subcellular localization of ACBPs was predicted. The findings indicated that the physicochemical parameters and subcellular localizations of ACBPs in Brassica napus were identical to Arabidopsis thaliana. Conserved domain analysis indicated that ACBPs contain two or three kelch domains that belong to different families. Identical residues in acyl-coA binding domains corresponded to eight amino acid residues in all ACBPs of B. napus. However, conserved residues of common ACBPs in all species of animal, plant, bacteria and fungi were only inclusive in small ACBPs. Alpha-helixes were displayed and conserved in all the acyl-coA binding domains, representing almost the half of the protein structure. The findings confirm high similarities in ACBPs between A. thaliana and B. napus, they might share the same functions but loss or gain might be possible.

  8. Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach

    Directory of Open Access Journals (Sweden)

    Taigang Liu

    2015-12-01

    Full Text Available The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE. These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.

  9. PSPP: a protein structure prediction pipeline for computing clusters.

    Directory of Open Access Journals (Sweden)

    Michael S Lee

    Full Text Available BACKGROUND: Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster. METHODOLOGY/PRINCIPAL FINDINGS: The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes. CONCLUSIONS: The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a

  10. Structure prediction of subtilisin BPN' mutants using molecular dynamics methods

    OpenAIRE

    Heiner, Andreas P.; Berendsen, Herman J.C.; van Gunsteren, Wilfred F.

    2017-01-01

    In this paper we describe the achievements and pitfalls encountered in doing structure predictions of protein mutants using molecular dynamics simulation techniques in which properties of atoms are slowly changed as a function of time. Basically the method consists of a thermodynamic integration (slow growth) calculation used for free energy determination, but aimed at structure prediction; this allows for a fast determination of the mutant structure. We compared the calculated structure of t...

  11. Genetic diversity, genetic structure, and mating system of brewer spruce (Pinaceae), a relict of the acto-tertiary forest

    Science.gov (United States)

    F. Thomas Ledig; Paul D. Hodgskiss; David R. Johnson

    2005-01-01

    Brewer spruce (Picea breweriana), a relict of the widespread Arcto-Tertiary forests, is now restricted to a highly fragmented range in the Klamath Region of California and Oregon. Expected heterozygosity for 26 isozyme loci, averaged over 10 populations, was 0.121. More notable than the relatively high level of diversity when compared to other woody...

  12. Critical Features of Fragment Libraries for Protein Structure Prediction

    Science.gov (United States)

    dos Santos, Karina Baptista

    2017-01-01

    The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction. PMID:28085928

  13. Critical Features of Fragment Libraries for Protein Structure Prediction.

    Science.gov (United States)

    Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

    2017-01-01

    The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

  14. Structure-activity relationships in defensin dimers: a novel link between beta-defensin tertiary structure and antimicrobial activity.

    Science.gov (United States)

    Campopiano, Dominic J; Clarke, David J; Polfer, Nick C; Barran, Perdita E; Langley, Ross J; Govan, John R W; Maxwell, Alison; Dorin, Julia R

    2004-11-19

    Defensins are cationic antimicrobial peptides that have a characteristic six-cysteine motif and are important components of the innate immune system. We recently described a beta-defensin-related peptide (Defr1) that had potent antimicrobial activity despite having only five cysteines. Here we report a relationship between the structure and activity of Defr1 through a comparative study with its six cysteine-containing analogue (Defr1 Y5C). Against a panel of pathogens, we found that oxidized Defr1 had significantly higher activity than its reduced form and the oxidized and reduced forms of Defr1 Y5C. Furthermore, Defr1 displayed activity against Pseudomonas aeruginosa in the presence of 150 mm NaCl, whereas Defr1 Y5C was inactive. By using nondenaturing gel electrophoresis and Fourier transform ion cyclotron resonance mass spectrometry, we observed Defr1 and Defr1 Y5C dimers. Two complementary fragmentation techniques (collision-induced dissociation and electron capture dissociation) revealed that Defr1 Y5C dimers form by noncovalent, weak association of monomers that contain three intramolecular disulfide bonds. In contrast, Defr1 dimers are resistant to collision-induced dissociation and are only dissociated into monomers by reduction using electron capture. This is indicative of Defr1 dimerization being mediated by an intermolecular disulfide bond. Proteolysis and peptide mass mapping revealed that Defr1 Y5C monomers have beta-defensin disulfide bond connectivity, whereas oxidized Defr1 is a complex mixture of dimeric isoforms with as yet unknown inter- and intramolecular connectivities. Each isoform contains one intermolecular and four intramolecular disulfide bonds, but because we were unable to resolve the isoforms by reverse phase chromatography, we could not assign each isoform with a specific antimicrobial activity. We conclude that the enhanced activity and stability of this mixture of Defr1 dimeric isoforms are due to the presence of an intermolecular

  15. Simultaneous prediction of protein secondary structure and transmembrane spans.

    Science.gov (United States)

    Leman, Julia Koehler; Mueller, Ralf; Karakas, Mert; Woetzel, Nils; Meiler, Jens

    2013-07-01

    Prediction of transmembrane spans and secondary structure from the protein sequence is generally the first step in the structural characterization of (membrane) proteins. Preference of a stretch of amino acids in a protein to form secondary structure and being placed in the membrane are correlated. Nevertheless, current methods predict either secondary structure or individual transmembrane states. We introduce a method that simultaneously predicts the secondary structure and transmembrane spans from the protein sequence. This approach not only eliminates the necessity to create a consensus prediction from possibly contradicting outputs of several predictors but bears the potential to predict conformational switches, i.e., sequence regions that have a high probability to change for example from a coil conformation in solution to an α-helical transmembrane state. An artificial neural network was trained on databases of 177 membrane proteins and 6048 soluble proteins. The output is a 3 × 3 dimensional probability matrix for each residue in the sequence that combines three secondary structure types (helix, strand, coil) and three environment types (membrane core, interface, solution). The prediction accuracies are 70.3% for nine possible states, 73.2% for three-state secondary structure prediction, and 94.8% for three-state transmembrane span prediction. These accuracies are comparable to state-of-the-art predictors of secondary structure (e.g., Psipred) or transmembrane placement (e.g., OCTOPUS). The method is available as web server and for download at www.meilerlab.org. Copyright © 2013 Wiley Periodicals, Inc.

  16. Viral IRES prediction system - a web server for prediction of the IRES secondary structure in silico.

    Directory of Open Access Journals (Sweden)

    Jun-Jie Hong

    Full Text Available The internal ribosomal entry site (IRES functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

  17. Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes

    Science.gov (United States)

    Weigt, Martin

    Over the last years, biological research has been revolutionized by experimental high-throughput techniques, in particular by next-generation sequencing technology. Unprecedented amounts of data are accumulating, and there is a growing request for computational methods unveiling the information hidden in raw data, thereby increasing our understanding of complex biological systems. Statistical-physics models based on the maximum-entropy principle have, in the last few years, played an important role in this context. To give a specific example, proteins and many non-coding RNA show a remarkable degree of structural and functional conservation in the course of evolution, despite a large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach - called Direct-Coupling Analysis - to link this sequence variability (easy to observe in sequence alignments, which are available in public sequence databases) to bio-molecular structure and function. In my presentation I will show, how this methodology can be used (i) to infer contacts between residues and thus to guide tertiary and quaternary protein structure prediction and RNA structure prediction, (ii) to discriminate interacting from non-interacting protein families, and thus to infer conserved protein-protein interaction networks, and (iii) to reconstruct mutational landscapes and thus to predict the phenotypic effect of mutations. References [1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt ''Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1'', Mol. Biol. Evol. (2015), doi: 10.1093/molbev/msv211 [2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt ''Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction'', Nucleic Acids Research (2015), doi: 10.1093/nar/gkv932 [3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C

  18. RNAstructure: software for RNA secondary structure prediction and analysis

    Directory of Open Access Journals (Sweden)

    Mathews David H

    2010-03-01

    Full Text Available Abstract Background To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. Results RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms, prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. Conclusion The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

  19. A crystal structure prediction enigma solved

    DEFF Research Database (Denmark)

    Hoser, Anna Agnieszka; Sovago, Ioana; Lanzac, A.

    2017-01-01

    The seemingly unpredictable structure of gallic acid monohydrate form IV has been investigated using accurate X-ray diffraction measurements at temperatures of 10 and 123 K. The measurements demonstrate that the structure is commensurately modulated at 10 K and disordered at higher temperatures. ...

  20. Referent Predictability is Affected by Syntactic Structure: Evidence from Chinese.

    Science.gov (United States)

    Cheng, Wei; Almor, Amit

    2017-02-01

    This paper examines the effect of syntactic structures on referent predictability. Focusing on stimulus-experiencer (SE) verbs, we conducted two sentence-completion experiments in Chinese by contrasting SE verbs in three structures (active canonical, active ba, and passive). The results showed that although verb semantics and discourse coherence relations produce a strong referential biases, the stimulus referent is overall less likely to be rementioned in the active canonical structure than in the other two structures. The findings thus indicate that referent predictability is determined by not only semantic but also syntactic factors. We discuss the theoretical implications for the nature of referent predictability and its relationship with referent accessibility.

  1. RBO Aleph: leveraging novel information sources for protein structure prediction.

    Science.gov (United States)

    Mabrouk, Mahmoud; Putz, Ines; Werner, Tim; Schneider, Michael; Neeb, Moritz; Bartels, Philipp; Brock, Oliver

    2015-07-01

    RBO Aleph is a novel protein structure prediction web server for template-based modeling, protein contact prediction and ab initio structure prediction. The server has a strong emphasis on modeling difficult protein targets for which templates cannot be detected. RBO Aleph's unique features are (i) the use of combined evolutionary and physicochemical information to perform residue-residue contact prediction and (ii) leveraging this contact information effectively in conformational space search. RBO Aleph emerged as one of the leading approaches to ab initio protein structure prediction and contact prediction during the most recent Critical Assessment of Protein Structure Prediction experiment (CASP11, 2014). In addition to RBO Aleph's main focus on ab initio modeling, the server also provides state-of-the-art template-based modeling services. Based on template availability, RBO Aleph switches automatically between template-based modeling and ab initio prediction based on the target protein sequence, facilitating use especially for non-expert users. The RBO Aleph web server offers a range of tools for visualization and data analysis, such as the visualization of predicted models, predicted contacts and the estimated prediction error along the model's backbone. The server is accessible at http://compbio.robotics.tu-berlin.de/rbo_aleph/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Neural network definitions of highly predictable protein secondary structure classes

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States); Steeg, E. [Toronto Univ., ON (Canada). Dept. of Computer Science; Farber, R. [Los Alamos National Lab., NM (United States)

    1994-02-01

    We use two co-evolving neural networks to determine new classes of protein secondary structure which are significantly more predictable from local amino sequence than the conventional secondary structure classification. Accurate prediction of the conventional secondary structure classes: alpha helix, beta strand, and coil, from primary sequence has long been an important problem in computational molecular biology. Neural networks have been a popular method to attempt to predict these conventional secondary structure classes. Accuracy has been disappointingly low. The algorithm presented here uses neural networks to similtaneously examine both sequence and structure data, and to evolve new classes of secondary structure that can be predicted from sequence with significantly higher accuracy than the conventional classes. These new classes have both similarities to, and differences with the conventional alpha helix, beta strand and coil.

  3. Protein structure prediction by all-atom free-energy refinement

    Science.gov (United States)

    Verma, Abhinav; Wenzel, Wolfgang

    2007-01-01

    Background The reliable prediction of protein tertiary structure from the amino acid sequence remains challenging even for small proteins. We have developed an all-atom free-energy protein forcefield (PFF01) that we could use to fold several small proteins from completely extended conformations. Because the computational cost of de-novo folding studies rises steeply with system size, this approach is unsuitable for structure prediction purposes. We therefore investigate here a low-cost free-energy relaxation protocol for protein structure prediction that combines heuristic methods for model generation with all-atom free-energy relaxation in PFF01. Results We use PFF01 to rank and cluster the conformations for 32 proteins generated by ROSETTA. For 22/10 high-quality/low quality decoy sets we select near-native conformations with an average Cα root mean square deviation of 3.03 Å/6.04 Å. The protocol incorporates an inherent reliability indicator that succeeds for 78% of the decoy sets. In over 90% of these cases near-native conformations are selected from the decoy set. This success rate is rationalized by the quality of the decoys and the selectivity of the PFF01 forcefield, which ranks near-native conformations an average 3.06 standard deviations below that of the relaxed decoys (Z-score). Conclusion All-atom free-energy relaxation with PFF01 emerges as a powerful low-cost approach toward generic de-novo protein structure prediction. The approach can be applied to large all-atom decoy sets of any origin and requires no preexisting structural information to identify the native conformation. The study provides evidence that a large class of proteins may be foldable by PFF01. PMID:17371594

  4. Factors predictive of abnormal semen parameters in male partners of couples attending the infertility clinic of a tertiary hospital in south-western Nigeria

    Directory of Open Access Journals (Sweden)

    Peter Olusola Aduloju

    2016-11-01

    Full Text Available Background: Infertility is a common gynaecological problem and male factor contributes significantly in the aetiology of infertility. Semen analysis has remained a useful investigation in the search for male factor infertility. Aim: This study assessed the pattern of semen parameters and predictive factors associated with abnormal parameters in male partners of infertile couples attending a Nigerian tertiary hospital. Methods: A descriptive study of infertile couples presenting at the clinic between January 2012and December 2015 was done at Ekiti State University Teaching Hospital, Ado-Ekiti. Seminal fluid from the male partners were analysed in the laboratory using the WHO 2010 criteria for human semen characteristics. Data was analysed using SPSS 17 and logistic regression analysis was used to determine the predictive factors associated with abnormal semen parameters. Results: A total of 443 men participated in the study and 38.2% had abnormal sperm parameters. Oligozoospermia (34.8% and asthenozoospermia (26.9% are leading single factor abnormality found, astheno-oligozoospermia occurred in 14.2% and oligo-astheno-teratozoospermia in 3.6% of cases. The prevalence of azoospermia was 3.4%. Smoking habit, past infection with mumps and previous groin surgery significantly predicted abnormal semen parameters with p values of 0.025, 0.040 and 0.017 respectively. Positive cultures were recorded in 36.2% of cases and staph aureus was the commonest organism. Conclusion: Male factor abnormalities remain significant contributors to infertility and men should be encouraged through advocacy to participate in investigation of infertility to reduce the level of stigmatization and ostracizing of women with infertility especially in sub-Saharan Africa.

  5. Evaluation of Candida Scoring Systems to Predict Early Candidemia: A Prospective and Observational Study at a Tertiary Care Hospital, Uttarakhand.

    Science.gov (United States)

    Gupta, Priyanka; Gupta, Pratima; Chatterjee, Biswaroop; Mittal, Garima; Prateek, Shashank; Mohanty, Aroop

    2017-12-01

    Candidemia in critically ill patients is usually a severe and life-threatening condition. Furthermore, due to its nonspecific presentation, it is difficult to diagnose leading to delayed treatment, prolonged hospitalization, and increased health-care costs with increase in morbidity and mortality. In view of lack of data on "Candida scoring systems," this study was designed to evaluate the effectiveness of these scoring systems in predicting the development of candidemia among the Intensive Care Unit patients. The "Candida score" was calculated at the onset of systemic inflammatory response syndrome, sepsis, or shock. Various scoring systems were compared using the area under the receiver operating characteristic curve. Among all three bedside risk scoring systems to predict candidemia both Leon score and Wenzel score offered significant discrimination between candidemic and noncandidemic patients with P = 0.000 and 0.001, respectively. The area under the curve for the scoring systems was 0.946 (95% confidence interval [CI] = 0.89-1) and 0.818 (95% CI = 0.687-0.949). Leon scoring system was found to have highest specificity, diagnostic accuracy, and positive likelihood ratio among all. Thus, we might conclude that a Leon score of ≥2.5 was most suitable for diagnosis of candidemia with significant accuracy and shortening of turnaround time when compared to the gold standard of blood culture. To the best of our knowledge, this is the first report on the subject.

  6. In silico Sequence Analysis, Structure Prediction and Function Annotation of Human Bcl-X Beta Protein

    Directory of Open Access Journals (Sweden)

    Anjali Singh

    2014-03-01

    Full Text Available Bcl-X proteins are the one of the best categorized member of the Bcl-2 protein families which acts as primary regulators of apoptosis in mammalian cells. The Bcl-X proteins are potential anti-cancer drug targets. In this study, the tertiary structure of the beta isoform of the apoptosis regulator Bcl-X in humans (h-Bcl-Xβ has been predicted by fold-recognition (threading approach. In silico assessment of the h-Bcl-Xβ protein revealed the characteristic structural features of anti-apoptotic Bcl-2 protein family in h-Bcl-Xβ protein. The predicted model was comprised of BH1-BH4 domains, seven alpha-helices and a C-terminal transmembrane domain for membrane localization and sub-cellular targeting. Quality assessment of the predict model confirmed its reliability as fairly good model. Active sites of h-Bcl-Xβ protein were identified using CASTp server. The future work can be directed towards drug designing for cancer treatment by regulating the activity of h-Bcl-Xβ proteins.

  7. Testing a maintenance model for eating disorders in a sample seeking treatment at a tertiary care center: a structural equation modeling approach.

    Science.gov (United States)

    Tasca, Giorgio A; Presniak, Michelle D; Demidenko, Natasha; Balfour, Louise; Krysanski, Valerie; Trinneer, Anne; Bissada, Hany

    2011-01-01

    Fairburn et al (Fairburn, CG, Cooper, Z, Shafran, R. Behav Res Ther 2003;41:509-528) proposed additional maintenance mechanisms (ie, interpersonal difficulties, mood intolerance, low self-esteem, and perfectionism) for some individuals with eating disorders in addition to core eating disorder psychopathology (ie, overevaluation of eating, weight, and shape and their control). This is the first study to both elaborate and test this maintenance model as a structural model. Adults seeking treatment of an eating disorder (N = 1451) at a specialized tertiary care center were included in this cross-sectional study. In the first part of the study, diagnostically heterogeneous participants (n = 406) were randomly selected to test a structural model based on the maintenance model. In the second part of the study, remaining participants (n = 1045) were grouped according to eating disorder diagnosis to test for invariance of the structural paths of the final model across diagnoses. Overall, the structural model with core and additional mechanisms fit the data well and, with 1 exception, represented maintenance processes for each of the diagnostic groups. Treatment models based on both core and additional maintenance factors for those seeking therapy at a specialized tertiary care center may result in improved treatment outcomes for these patients with eating disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Protein Structure and Function Prediction Using I-TASSER.

    Science.gov (United States)

    Yang, Jianyi; Zhang, Yang

    2015-12-17

    I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. Copyright © 2015 John Wiley & Sons, Inc.

  9. Prolonged Duration of Surgery Predicts Postoperative Hypoparathyroidism among Patients Undergoing Total Thyroidectomy in a Tertiary Referral Centre

    DEFF Research Database (Denmark)

    Sonne-Holm, Emilie; Holst Hahn, Christoffer

    2017-01-01

    constitutes an independent risk factor due to the risk of ischaemic damage. Regain of function of devascularized parathyroid glands must be expected to last at least 1 year postoperatively. Furthermore, the recovery of autotransplanted parathyroid glands should not be evaluated within 1-3 months after surgery......., to identify early predictive risk factors. METHODS: Based on a single-institution retrospective review, we identified 582 patients who underwent total thyroidectomy between January 2010 and March 2015. Information on age, gender, pathological diagnosis, duration of surgery, autotransplantation of parathyroid...... glands, neck dissection, and experience and position of the surgeon was retrieved from the medical records. Furthermore, serum levels of parathyroid hormone and calcium were registered pre- and postoperatively and after 3 and 12 months. RESULTS: The incidence of transient hypoparathyroidism during...

  10. Predictive and Prognostic Implications of Variant Philadelphia Translocations in CML: Experience From a Tertiary Oncology Center in Southern India.

    Science.gov (United States)

    Kanakasetty, Govind Babu; Kuntejowdahalli, Lakshmaiah; Thanky, Aditi Harsh; Dasappa, Lokanatha; Jacob, Linu Abraham; Mallekavu, Suresh Babu; Kumari, Prasanna

    2017-01-01

    Chronic myeloid leukemia (CML) is a myeloproliferative disorder characterized by Philadelphia (Ph) chromosome with classical t(9;22)(q34;q11) seen in up to 90% of cases. However 5% to 10% of patients who present with variant Ph translocations (vPh) have been an area of research for their significance in predicting response to various therapies including tyrosine kinase inhibitors as well as prognosticating survival outcomes for many years involving varied patient populations, with conflicting results. We retrospectively analyzed our data from January 2002 to December 2014. Patients with vPh in chronic phase of CML (CML-CP) were analyzed with respect to their demographic parameters, response to imatinib therapy, and survival and their data were compared with data of patients with classical Ph translocation (cPh). Of 615 patients diagnosed with CML-CP, 72 patients (11.7%) showed vPh. Most common chromosomes involved in these translocations were 14 (13.9%), 11 (12.5%), 19 (9.7%), and 7 (8.3%). Rates of complete hematological response, complete cytogenetic response, and major molecular response were not statistically different between the groups. At 5 years, event-free survival, failure-free survival, progression-free survival, and overall survival were 60% versus 67.9%, 62.7% versus 69.7%, 84.7% versus 92.1%, and 87.5% versus 92.4%, respectively, in vPh and cPh. The differences in survival were statistically not significant. To our knowledge, this is the largest series of variant translocations in CML-CP, pertaining to the Indian population. Our data suggest that the presence of vPh in CML has no significant effect in predicting response to imatinib as well as in prognosticating survival. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Prediction of the secondary structure of HIV-1 gp120

    DEFF Research Database (Denmark)

    Hansen, J E; Lund, O; Nielsen, Jens Ole

    1996-01-01

    The secondary structure of HIV-1 gp120 was predicted using multiple alignment and a combination of two independent methods based on neural network and nearest-neighbor algorithms. The methods agreed on the secondary structure for 80% of the residues in BH10 gp120. Six helices were predicted in HIV...... strain BH10 gp120, as well as in 27 other HIV-1 strains examined. Two helical segments were predicted in regions displaying profound sequence variation, one in a region suggested to be critical for CD4 binding. The predicted content of helix, beta-strand, and coil was consistent with estimates from...... of future HIV subunit vaccine candidates....

  12. Prediction of the Secondary Structure of HIV-1 gp120

    DEFF Research Database (Denmark)

    Hansen, Jan; Lund, Ole; Nielsen, Jens O.

    1996-01-01

    The secondary structure of HIV-1 gp120 was predicted using multiple alignment and a combination of two independent methods based on neural network and nearest-neighbor algorithms. The methods agreed on the secondary structure for 80% of the residues in BH10 gp120. Six helices were predicted in HIV...... strain BH10 gp120, as well as in 27 other HIV-1 strains examined. Two helical seqments were predicted in regions displaying profound sequence variation, one in a region suggested to be critical for CD4 biding. The predicted content of helix, beta-strand, and coil was consistent with estimates from...... of future HIV sub-unit vaccine candidates....

  13. Right hemisphere structures predict poststroke speech fluency.

    Science.gov (United States)

    Pani, Ethan; Zheng, Xin; Wang, Jasmine; Norton, Andrea; Schlaug, Gottfried

    2016-04-26

    We sought to determine via a cross-sectional study the contribution of (1) the right hemisphere's speech-relevant white matter regions and (2) interhemispheric connectivity to speech fluency in the chronic phase of left hemisphere stroke with aphasia. Fractional anisotropy (FA) of white matter regions underlying the right middle temporal gyrus (MTG), precentral gyrus (PreCG), pars opercularis (IFGop) and triangularis (IFGtri) of the inferior frontal gyrus, and the corpus callosum (CC) was correlated with speech fluency measures. A region within the superior parietal lobule (SPL) was examined as a control. FA values of regions that significantly predicted speech measures were compared with FA values from healthy age- and sex-matched controls. FA values for the right MTG, PreCG, and IFGop significantly predicted speech fluency, but FA values of the IFGtri and SPL did not. A multiple regression showed that combining FA of the significant right hemisphere regions with the lesion load of the left arcuate fasciculus-a previously identified biomarker of poststroke speech fluency-provided the best model for predicting speech fluency. FA of CC fibers connecting left and right supplementary motor areas (SMA) was also correlated with speech fluency. FA of the right IFGop and PreCG was significantly higher in patients than controls, while FA of a whole CC region of interest (ROI) and the CC-SMA ROI was significantly lower in patients. Right hemisphere white matter integrity is related to speech fluency measures in patients with chronic aphasia. This may indicate premorbid anatomical variability beneficial for recovery or be the result of poststroke remodeling. © 2016 American Academy of Neurology.

  14. Predicting and characterizing data sequences from structure-variable systems

    CERN Document Server

    Fangi, H P

    1995-01-01

    Abstract: In principle, all the natural systems such as biological, ecological and economical systems are structure-variable systems (in which some environment parameters are not fixed). In this Letter we show that data sequences from many structure-variable systems are short-term predictable. We also argue how to characterize the data sequences from structure-variable systems.

  15. Structure Prediction and Analysis of Neuraminidase Sequence Variants

    Science.gov (United States)

    Thayer, Kelly M.

    2016-01-01

    Analyzing protein structure has become an integral aspect of understanding systems of biochemical import. The laboratory experiment endeavors to introduce protein folding to ascertain structures of proteins for which the structure is unavailable, as well as to critically evaluate the quality of the prediction obtained. The model system used is the…

  16. Is protein structure prediction still an enigma?

    African Journals Online (AJOL)

    STORAGESEVER

    2008-12-29

    Dec 29, 2008 ... Proteins are large molecules indispensable for the existence and proper functioning of biological organisms. They perform a wide array of functions including catalysis, structure formation, transport, body defense, etc. Understanding the functions of proteins is a fundamental problem in the discovery of.

  17. Electrostatics, structure prediction, and the energy landscapes for protein folding and binding.

    Science.gov (United States)

    Tsai, Min-Yeh; Zheng, Weihua; Balamurugan, D; Schafer, Nicholas P; Kim, Bobby L; Cheung, Margaret S; Wolynes, Peter G

    2016-01-01

    While being long in range and therefore weakly specific, electrostatic interactions are able to modulate the stability and folding landscapes of some proteins. The relevance of electrostatic forces for steering the docking of proteins to each other is widely acknowledged, however, the role of electrostatics in establishing specifically funneled landscapes and their relevance for protein structure prediction are still not clear. By introducing Debye-Hückel potentials that mimic long-range electrostatic forces into the Associative memory, Water mediated, Structure, and Energy Model (AWSEM), a transferable protein model capable of predicting tertiary structures, we assess the effects of electrostatics on the landscapes of thirteen monomeric proteins and four dimers. For the monomers, we find that adding electrostatic interactions does not improve structure prediction. Simulations of ribosomal protein S6 show, however, that folding stability depends monotonically on electrostatic strength. The trend in predicted melting temperatures of the S6 variants agrees with experimental observations. Electrostatic effects can play a range of roles in binding. The binding of the protein complex KIX-pKID is largely assisted by electrostatic interactions, which provide direct charge-charge stabilization of the native state and contribute to the funneling of the binding landscape. In contrast, for several other proteins, including the DNA-binding protein FIS, electrostatics causes frustration in the DNA-binding region, which favors its binding with DNA but not with its protein partner. This study highlights the importance of long-range electrostatics in functional responses to problems where proteins interact with their charged partners, such as DNA, RNA, as well as membranes. © 2015 The Protein Society.

  18. Ensemble-based prediction of RNA secondary structures.

    Science.gov (United States)

    Aghaeepour, Nima; Hoos, Holger H

    2013-04-24

    Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

  19. Hepatitis C virus internal ribosome entry site RNA contains a tertiary structural element in a functional domain of stem–loop II

    Science.gov (United States)

    Lyons, Alita J.; Lytle, J. Robin; Gomez, Jordi; Robertson, Hugh D.

    2001-01-01

    The internal ribosome entry site (IRES) of hepatitis C virus (HCV) RNA contains >300 bases of highly conserved 5′-terminal sequence, most of it in the uncapped 5′-untranslated region (5′-UTR) upstream from the single AUG initiator triplet at which translation of the HCV polyprotein begins. Although progress has been made in defining singularities like the RNA pseudoknot near this AUG, the sequence and structural features of the HCV IRES which stimulate accurate and efficient initiation of protein synthesis are only partially defined. Here we report that a region further upstream from the AUG, stem–loop II of the HCV IRES, also contains an element of local tertiary structure which we have detected using RNase H cleavage and have mapped using the singular ability of two bases therein to undergo covalent intra-chain crosslinking stimulated by UV light. This pre-existing element maps to two non-contiguous stretches of the HCV IRES sequence, residues 53–68 and 103–117. Several earlier studies have shown that the correct sequence between bases 45 and 70 of the HCV IRES stem–loop II domain is required for initiation of protein synthesis. Because features of local tertiary structure like the one we report here are often associated with protein binding, we propose that the HCV stem–loop II element is directly involved in IRES action. PMID:11410661

  20. PREDICTING PROGNOSTIC VALUE OF OCULAR TRAUMA SCORE (OTS IN AN OPEN GLOBE INJURY IN TERTIARY EYE CARE HOSPITAL

    Directory of Open Access Journals (Sweden)

    Rahul

    2015-10-01

    Full Text Available AIM : To evaluate the prognostic value of OTS in open globe injuries. MATERIAL METHOD : Retrospective analysis of 77 eyes with open globe injuries was done from 01/07/2013 to 31/12/2014. Patients were assigned raw score sum based on initial V/A, and ocular findings then classified into 5 categories for predicting final visual outcome based on ocular Trauma score (OTS. RESULT : We estimated final V/A in 77 cases of open globe injuries (64.93% had raw sc ore between 65.91 (category 3, 4 Six months after the injury, 42.85% patients of categories 1 (raw score 0 - 44 achieved V/A of PL/HM as compared to 17% in OTS study. 16 patients with raw compared to OTS study. We reported comparable visual outcome with OT S study except in category 1 & 2. CONCLUSION: OTS score is valuable in triage, patient counseling and decision making for the management of ocular trauma. We recommend that OTS should be used routinely for open globe injuries as it is a simple guide

  1. Predicting the Structural Performance of Composite Structures Under Cyclic Loading

    NARCIS (Netherlands)

    Kassapoglou, C.

    2012-01-01

    The increased use of advanced composite materials on primary aircraft structure has brought back to the forefront the question of how such structures perform under repeated loading. In particular, when damage or other stress risers are present, tests have shown that the load to cause failure after a

  2. Whole-brain functional connectivity predicted by indirect structural connections

    DEFF Research Database (Denmark)

    Røge, Rasmus; Ambrosen, Karen Marie Sandø; Albers, Kristoffer Jon

    2017-01-01

    Modern functional and diffusion magnetic resonance imaging (fMRI and dMRI) provide data from which macro-scale networks of functional and structural whole brain connectivity can be estimated. Although networks derived from these two modalities describe different properties of the human brain......, they emerge from the same underlying brain organization, and functional communication is presumably mediated by structural connections. In this paper, we assess the structure-function relationship by evaluating how well functional connectivity can be predicted from structural graphs. Using high......-resolution whole brain networks generated with varying density, we contrast the performance of several non-parametric link predictors that measure structural communication flow. While functional connectivity is not well predicted directly by structural connections, we show that superior predictions can be achieved...

  3. Status of research aimed at predicting structural integrity

    Energy Technology Data Exchange (ETDEWEB)

    Reuter, W.G. [Lockheed Martin Idaho Technologies Co, Idaho Falls, ID (United States)

    1997-12-31

    Considerable research has been performed throughout the world on measuring the fracture toughness of metals. The existing capability fills the need encountered when selecting materials, thermal-mechanical treatments, welding procedures, etc., but cannot predict the fracture process of structural components containing cracks. The Idaho National Engineering and Environmental Laboratory and the Massachusetts Institute of Technology have been collaborating for a number of years on developing capabilities for using fracture toughness results to predict structural integrity. Because of the high cost of fabricating and testing structural components, these studies have been limited to predicting the fracture process in specimens containing surface cracks. This paper summarizes the present status of the experimental studies of using fracture toughness data to predict crack growth initiation in specimens (structural components) containing surface cracks. These results are limited to homogeneous base materials.

  4. Neural Network Algorithm for Prediction of Secondary Protein Structure

    National Research Council Canada - National Science Library

    Zikrija Avdagic; Elvir Purisevic; Emir Buza; Zlatan Coralic

    2009-01-01

    .... In this paper we describe the method and results of using CB513 as a dataset suitable for development of artificial neural network algorithms for prediction of secondary protein structure with MATLAB...

  5. Reengineering Aircraft Structural Life Prediction Using a Digital Twin

    Directory of Open Access Journals (Sweden)

    Eric J. Tuegel

    2011-01-01

    Full Text Available Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail.

  6. Predicting RNA secondary structures from sequence and probing data.

    Science.gov (United States)

    Lorenz, Ronny; Wolfinger, Michael T; Tanzer, Andrea; Hofacker, Ivo L

    2016-07-01

    RNA secondary structures have proven essential for understanding the regulatory functions performed by RNA such as microRNAs, bacterial small RNAs, or riboswitches. This success is in part due to the availability of efficient computational methods for predicting RNA secondary structures. Recent advances focus on dealing with the inherent uncertainty of prediction by considering the ensemble of possible structures rather than the single most stable one. Moreover, the advent of high-throughput structural probing has spurred the development of computational methods that incorporate such experimental data as auxiliary information. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Simplified Models for Accelerated Structural Prediction of Conjugated Semiconducting Polymers

    Energy Technology Data Exchange (ETDEWEB)

    Henry, Michael M. [Micron; Jones, Matthew L. [Micron; Oosterhout, Stefan D. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Braunecker, Wade A. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Kemper, Travis W. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Larsen, Ross E. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Kopidakis, Nikos [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Department; Toney, Michael F. [SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States; Olson, Dana C. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Jankowski, Eric [Micron; National Renewable Energy Laboratory, Golden, Colorado 80401, United States

    2017-11-20

    We perform molecular dynamics simulations of poly(benzodithiophene-thienopyrrolodione) (BDT-TPD) oligomers in order to evaluate the accuracy with which unoptimized molecular models can predict experimentally characterized morphologies. The predicted morphologies are characterized using simulated grazing-incidence X-ray scattering (GIXS) and compared to the experimental scattering patterns. We find that approximating the aromatic rings in BDT-TPD with rigid bodies, rather than combinations of bond, angle, and dihedral constraints, results in 14% lower computational cost and provides nearly equivalent structural predictions compared to the flexible model case. The predicted glass transition temperature of BDT-TPD (410 +/- 32 K) is found to be in agreement with experiments. Predicted morphologies demonstrate short-range structural order due to stacking of the chain backbones (p-p stacking around 3.9 A), and long-range spatial correlations due to the self-organization of backbone stacks into 'ribbons' (lamellar ordering around 20.9 A), representing the best-to-date computational predictions of structure of complex conjugated oligomers. We find that expensive simulated annealing schedules are not needed to predict experimental structures here, with instantaneous quenches providing nearly equivalent predictions at a fraction of the computational cost of annealing. We therefore suggest utilizing rigid bodies and fast cooling schedules for high-throughput screening studies of semiflexible polymers and oligomers to utilize their significant computational benefits where appropriate.

  8. Exploring the effects of sparse restraints on protein structure prediction.

    Science.gov (United States)

    Mandalaparthy, Varun; Sanaboyana, Venkata Ramana; Rafalia, Hitesh; Gosavi, Shachi

    2017-12-03

    One of the main barriers to accurate computational protein structure prediction is searching the vast space of protein conformations. Distance restraints or inter-residue contacts have been used to reduce this search space, easing the discovery of the correct folded state. It has been suggested that about 1 contact for every 12 residues may be sufficient to predict structure at fold level accuracy. Here, we use coarse-grained structure-based models in conjunction with molecular dynamics simulations to examine this empirical prediction. We generate sparse contact maps for 15 proteins of varying sequence lengths and topologies and find that given perfect secondary-structural information, a small fraction of the native contact map (5%-10%) suffices to fold proteins to their correct native states. We also find that different sparse maps are not equivalent and we make several observations about the type of maps that are successful at such structure prediction. Long range contacts are found to encode more information than shorter range ones, especially for α and αβ-proteins. However, this distinction reduces for β-proteins. Choosing contacts that are a consensus from successful maps gives predictive sparse maps as does choosing contacts that are well spread out over the protein structure. Additionally, the folding of proteins can also be used to choose predictive sparse maps. Overall, we conclude that structure-based models can be used to understand the efficacy of structure-prediction restraints and could, in future, be tuned to include specific force-field interactions, secondary structure errors and noise in the sparse maps. © 2017 Wiley Periodicals, Inc.

  9. Predicting nucleic acid binding interfaces from structural models of proteins

    Science.gov (United States)

    Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

    2011-01-01

    The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

  10. Predicting nucleic acid binding interfaces from structural models of proteins.

    Science.gov (United States)

    Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

    2012-02-01

    The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

  11. Structure prediction of loops with fixed and flexible stems.

    Science.gov (United States)

    Subramani, A; Floudas, C A

    2012-06-14

    The prediction of loop structures is considered one of the main challenges in the protein folding problem. Regardless of the dependence of the overall algorithm on the protein data bank, the flexibility of loop regions dictates the need for special attention to their structures. In this article, we present algorithms for loop structure prediction with fixed stem and flexible stem geometry. In the flexible stem geometry problem, only the secondary structure of three stem residues on either side of the loop is known. In the fixed stem geometry problem, the structure of the three stem residues on either side of the loop is also known. Initial loop structures are generated using a probability database for the flexible stem geometry problem, and using torsion angle dynamics for the fixed stem geometry problem. Three rotamer optimization algorithms are introduced to alleviate steric clashes between the generated backbone structures and the side chain rotamers. The structures are optimized by energy minimization using an all-atom force field. The optimized structures are clustered using a traveling salesman problem-based clustering algorithm. The structures in the densest clusters are then utilized to refine dihedral angle bounds on all amino acids in the loop. The entire procedure is carried out for a number of iterations, leading to improved structure prediction and refined dihedral angle bounds. The algorithms presented in this article have been tested on 3190 loops from the PDBSelect25 data set and on targets from the recently concluded CASP9 community-wide experiment.

  12. Referent Predictability Is Affected by Syntactic Structure: Evidence from Chinese

    Science.gov (United States)

    Cheng, Wei; Almor, Amit

    2017-01-01

    This paper examines the effect of syntactic structures on referent predictability. Focusing on stimulus-experiencer (SE) verbs, we conducted two sentence-completion experiments in Chinese by contrasting SE verbs in three structures (active canonical, active "ba," and passive). The results showed that although verb semantics and discourse…

  13. Evolving networks-Using past structure to predict the future

    Science.gov (United States)

    Shang, Ke-ke; Yan, Wei-sheng; Small, Michael

    2016-08-01

    Many previous studies on link prediction have focused on using common neighbors to predict the existence of links between pairs of nodes. More broadly, research into the structural properties of evolving temporal networks and temporal link prediction methods have recently attracted increasing attention. In this study, for the first time, we examine the use of links between a pair of nodes to predict their common neighbors and analyze the relationship between the weight and the structure in static networks, evolving networks, and in the corresponding randomized networks. We propose both new unweighted and weighted prediction methods and use six kinds of real networks to test our algorithms. In unweighted networks, we find that if a pair of nodes connect to each other in the current network, they will have a higher probability to connect common nodes both in the current and the future networks-and the probability will decrease with the increase of the number of neighbors. Furthermore, we find that the original networks have their particular structure and statistical characteristics which benefit link prediction. In weighted networks, the prediction algorithm performance of networks which are dominated by human factors decrease with the decrease of weight and are in general better in static networks. Furthermore, we find that geographical position and link weight both have significant influence on the transport network. Moreover, the evolving financial network has the lowest predictability. In addition, we find that the structure of non-social networks has more robustness than social networks. The structure of engineering networks has both best predictability and also robustness.

  14. Prevalence and predictive factors of birth traumas in neonates presenting to the children emergency center of a tertiary center in Southwest, Nigeria

    Directory of Open Access Journals (Sweden)

    Babayemi O Osinaike

    2017-01-01

    Full Text Available Background: Although the majority of birth injuries are minor and often unreported, occasionally birth injuries may be so severe as to be fatal or leave the child with a permanent disability or even death.Objective: This study aimed to document the patterns and predictive factors of birth injuries in neonates presenting at the emergency center of a tertiary hospital in South west, Nigeria. Patients And Methods: This was a cross-sectional study of neonates who presented at the Olikoye Ransome-Kuti Children Emergency Center of the Lagos University Teaching Hospital between October and December 2016. All neonates admitted for treatment at the center for any clinical condition were included in the study after initial review or resuscitation/treatment for their primary complaint, and consent was obtained from their caregivers. The babies were examined by at least a senior resident and any abnormality documented. Any underlining medical conditions such as asphyxia and neonatal sepsis were properly investigated and treated. Statistical analyses were performed by chi-square, student's t-test, using SPSS version 20.0. P ≤ 0.05 was considered statistically significant. Results: A total of 134 neonates were reviewed during the study period with majority, 84 (62.7%, being males. The mean age at presentation was 65.2 ± 89.2 h (median 24 h. Caput succedaneum (22.2% and subconjunctival hemorrhage (22.2% were the most frequent injuries observed, while cranial nerve injury the least. One patient had multiple injuries (cranial nerve injury with fractures humerus. Conclusions: Overall prevalence and pattern of birth injuries in neonates presenting at our emergency center was consistent with various studies from other centers. Parity of the mother, significant maternal medical history, duration of labor, mode of delivery, and skill of attending personnel at delivery were significant factors associated with birth injuries

  15. Prediction of structure and density for organic nitramines

    Science.gov (United States)

    Dzyabchenko, A. V.; Pivina, T. S.; Arnautova, E. A.

    1996-05-01

    An approach to ab initio crystal structure prediction by packing optimization is developed for organic nitramines, an important class of energetic materials. The principal features of the search method are: use of statistical data on the organic crystal structural classes to select typical space groups and site symmetries for further search; accounting for the energy-hypersurface symmetry to determine the unique search region; and use of an automated similarity-search procedure to recognize non-unique minima and determine the symmetry of optimized packings. The wide convergence properties of the local search procedure permit one to start optimization from an arbitrary point, so that no preliminary screening of the starting models is necessary. The numerical calculations were first carried out on the known crystal structures of three polymorphs of HMX (1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane). In this step, the force-field parameters for the nitramine fragment have been improved to obtain the best correspondence between the predicted and observed molecular geometries. The predicted packings were found to be in reasonably good agreement with the X-ray structural data, while the computed lattice energies were not accurate enough to predict the observed heats of sublimation and the trend of polymorph stabilities. Secondly, the method was employed to predict the possible crystal structures of eight isomeric azanitroadamantanes and wurtzitanes, whose molecular structures were proposed earlier on the basis of a computational study (T.S. Pivina et al., Propellants, Explosives, Pyrotechnics, 20 (1995) 91). As a result, the energy-minimized structures with densities up to 2.08 and 2.04 g cm -3 have been predicted for the adamantane and wurtzitane series, respectively, as the possible crystal polymorphs. Due to the interaction between the conformational and packing forces giving rise to some gain in the total energy at the expense of at least partial loss in molecular

  16. Bayesian model of protein primary sequence for secondary structure prediction.

    Directory of Open Access Journals (Sweden)

    Qiwei Li

    Full Text Available Determining the primary structure (i.e., amino acid sequence of a protein has become cheaper, faster, and more accurate. Higher order protein structure provides insight into a protein's function in the cell. Understanding a protein's secondary structure is a first step towards this goal. Therefore, a number of computational prediction methods have been developed to predict secondary structure from just the primary amino acid sequence. The most successful methods use machine learning approaches that are quite accurate, but do not directly incorporate structural information. As a step towards improving secondary structure reduction given the primary structure, we propose a Bayesian model based on the knob-socket model of protein packing in secondary structure. The method considers the packing influence of residues on the secondary structure determination, including those packed close in space but distant in sequence. By performing an assessment of our method on 2 test sets we show how incorporation of multiple sequence alignment data, similarly to PSIPRED, provides balance and improves the accuracy of the predictions. Software implementing the methods is provided as a web application and a stand-alone implementation.

  17. Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools

    Directory of Open Access Journals (Sweden)

    Deborah Antunes

    2018-01-01

    Full Text Available RNA molecules are essential players in many fundamental biological processes. Prokaryotes and eukaryotes have distinct RNA classes with specific structural features and functional roles. Computational prediction of protein structures is a research field in which high confidence three-dimensional protein models can be proposed based on the sequence alignment between target and templates. However, to date, only a few approaches have been developed for the computational prediction of RNA structures. Similar to proteins, RNA structures may be altered due to the interaction with various ligands, including proteins, other RNAs, and metabolites. A riboswitch is a molecular mechanism, found in the three kingdoms of life, in which the RNA structure is modified by the binding of a metabolite. It can regulate multiple gene expression mechanisms, such as transcription, translation initiation, and mRNA splicing and processing. Due to their nature, these entities also act on the regulation of gene expression and detection of small metabolites and have the potential to helping in the discovery of new classes of antimicrobial agents. In this review, we describe software and web servers currently available for riboswitch aptamer identification and secondary and tertiary structure prediction, including applications.

  18. Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach.

    Science.gov (United States)

    Desautels, Thomas; Das, Ritankar; Calvert, Jacob; Trivedi, Monica; Summers, Charlotte; Wales, David J; Ercole, Ari

    2017-09-15

    Unplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult and potentially increasing length of stay and mortality in some settings. Identifying patients who are likely to suffer unplanned ICU readmission could reduce the frequency of this adverse event. A single academic, tertiary care hospital in the UK. A set of 3326 ICU episodes collected between October 2014 and August 2016. All records were of patients who visited an ICU at some point during their stay. We excluded patients who were ≤16 years of age; visited ICUs other than the general and neurosciences ICU; were missing crucial electronic patient record measurements; or had indeterminate ICU discharge outcomes or very early or extremely late discharge times. After exclusion, 2018 outcome-labelled episodes remained. Area under the receiver operating characteristic curve (AUROC) for prediction of unplanned ICU readmission or in-hospital death within 48 hours of first ICU discharge. In 10-fold cross-validation, an ensemble predictor was trained on data from both the target hospital and the Medical Information Mart for Intensive Care (MIMIC-III) database and tested on the target hospital's data. This predictor discriminated between patients with the unplanned ICU readmission or death outcome and those without this outcome, attaining mean AUROC of 0.7095 (SE 0.0260), superior to the purpose-built Stability and Workload Index for Transfer (SWIFT) score (AUROC=0.6082, SE 0.0249; p=0.014, pairwise t-test). Despite the inherent difficulties, we demonstrate that a novel machine learning algorithm based on transfer learning could achieve good discrimination, over and above that of the treating clinicians or the value added by the SWIFT score. Accurate prediction of unplanned readmission could be used to target resources more efficiently. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article

  19. Can pre-operative axial CT imaging predict syndesmosis instability in patients sustaining ankle fractures? Seven years' experience in a tertiary trauma center

    Energy Technology Data Exchange (ETDEWEB)

    Yeung, Tsz Wai; Chan, Chung Yan Grace; Chan, Wun Cheung Samuel; Yuen, Ming Keung [Tuen Mun Hospital, Department of Radiology, Tuen Mun (China); Yeung, Yuk Nam [Tune Mun Hospital, Department of Orthopaedics and Traumatology, Tuen Mun (China)

    2015-06-01

    The purpose of this study is to explore the diagnostic accuracy of CT measurements in predicting syndesmosis instability of injured ankle, with correlation to operative findings. From July 2006 to June 2013, 123 patients presented to a single tertiary hospital who received pre-operative CT for ankle fractures were retrospectively reviewed. All patients underwent open reduction and internal fixation for fractures and intra-operative syndesmosis integrity tests. The morphology of incisura fibularis was categorized as deep or shallow. The tibiofibular distance (TFD) between the medial border of the fibula and the nearest point of the lateral border of tibia were measured at anterior (aTFD), middle (mTFD), posterior (pTFD), and maximal (maxTFD) portions across the syndesmosis on axial CT images at 10 mm proximal to the tibial plafond. Statistical analysis was performed with independent samples t test and ROC curve analysis. Intraobserver reproducibility and inter-observers agreement were also evaluated. Of the 123 patients, 39 (31.7 %) were operatively diagnosed with syndesmosis instability. No significant difference of incisura fibularis morphology (deep or shallow) and TFDs was demonstrated respective to genders. The axial CT measurements were significantly higher in ankles diagnosed with syndesmosis instability than the group without (maxTFD means 7.2 ± 2.96 mm vs. 4.6 ± 1.4 mm, aTFD mean 4.9 ± 3.7 mm vs. 1.8 ± 1.4 mm, mTFD mean 5.3 ± 2.4 mm vs. 3.2 ± 1.6 mm, pTFD mean 5.3 ± 1.8 mm vs. 4.1 ± 1.3 mm, p < 0.05). Their respective cutoff values with best sensitivity and specificity were calculated; the aTFD (AUC 0.798) and maxTFD (AUC 0.794) achieved the highest diagnostic accuracy. The optimal cutoff levels were aTFD = 4 mm (sensitivity, 56.4 %; specificity, 91.7 %) and maxTFD = 5.65 mm (sensitivity, 74.4 %; specificity, 79.8 %). The inter-observer agreement was good for all aTFD, mTFD, pTFD, and maxTFD measurements (ICC 0.959, 0.799, 0.783, and 0.865). The ICC

  20. Blind Test of Physics-Based Prediction of Protein Structures

    Science.gov (United States)

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  1. Blind test of physics-based prediction of protein structures.

    Science.gov (United States)

    Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

    2009-02-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

  2. A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach.

    Science.gov (United States)

    Hua, S; Sun, Z

    2001-04-27

    We have introduced a new method of protein secondary structure prediction which is based on the theory of support vector machine (SVM). SVM represents a new approach to supervised pattern classification which has been successfully applied to a wide range of pattern recognition problems, including object recognition, speaker identification, gene function prediction with microarray expression profile, etc. In these cases, the performance of SVM either matches or is significantly better than that of traditional machine learning approaches, including neural networks.The first use of the SVM approach to predict protein secondary structure is described here. Unlike the previous studies, we first constructed several binary classifiers, then assembled a tertiary classifier for three secondary structure states (helix, sheet and coil) based on these binary classifiers. The SVM method achieved a good performance of segment overlap accuracy SOV=76.2 % through sevenfold cross validation on a database of 513 non-homologous protein chains with multiple sequence alignments, which out-performs existing methods. Meanwhile three-state overall per-residue accuracy Q(3) achieved 73.5 %, which is at least comparable to existing single prediction methods. Furthermore a useful "reliability index" for the predictions was developed. In addition, SVM has many attractive features, including effective avoidance of overfitting, the ability to handle large feature spaces, information condensing of the given data set, etc. The SVM method is conveniently applied to many other pattern classification tasks in biology. Copyright 2001 Academic Press.

  3. RNA secondary structure prediction using highly parallel computers.

    Science.gov (United States)

    Nakaya, A; Yamamoto, K; Yonezawa, A

    1995-12-01

    An RNA secondary structure prediction method using a highly parallel computer is reported. We focus on finding thermodynamically stable structures of a single-stranded RNA molecule. Our approach is based on a parallel combinatorial method which calculates the free energy of a molecule as the sum of the free energies of all the physically possible hydrogen bonds. Our parallel algorithm finds many highly stable structures all at once, while most of the conventional prediction methods find only the most stable structure. The important idea in our algorithm is search tree pruning, with dynamic load balancing across the processor elements in a parallel computer. Software tools for visualization and classification of secondary structures are also presented using the sequence of cadang-cadang coconut viroid as an example. Our software system runs on CM-5.

  4. RNA folding: structure prediction, folding kinetics and ion electrostatics.

    Science.gov (United States)

    Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

    2015-01-01

    Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

  5. Evolutionary rate variation and RNA secondary structure prediction

    DEFF Research Database (Denmark)

    Knudsen, B; Andersen, E S; Damgaard, Christian Kroun

    2004-01-01

    of approach. Determining these rates can be hard to do reliably without a large and accurate initial alignment, which ideally also has structural annotation. Hence, one must often apply rates extracted from other RNA families with trusted alignments and structures. Here, we investigate this problem......Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type....... In addition we obtained an alignment of the 5' HIV-1 region that is more consistent with the structure than that currently in the database. We added randomized noise to the original values of the rates to investigate the stability of predictions to rate matrix deviations. We find that changes within a fairly...

  6. Improving the accuracy of protein secondary structure prediction using structural alignment

    Directory of Open Access Journals (Sweden)

    Gallin Warren J

    2006-06-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

  7. Denaturation of RNA secondary and tertiary structure by urea: simple unfolded state models and free energy parameters account for measured m-values

    Science.gov (United States)

    Lambert, Dominic; Draper, David E.

    2012-01-01

    To investigate the mechanism by which urea destabilizes RNA structure, urea-induced unfolding of four different RNA secondary and tertiary structures was quantified in terms of an m-value, the rate at which the free energy of unfolding changes with urea molality. From literature data and our osmometric study of a backbone analog, we derived average interaction potentials (per Å2 of solvent accessible surface) between urea and three kinds of RNA surfaces: phosphate, ribose, and base. Estimates of the increases in solvent accessible surface areas upon RNA denaturation were based on a simple model of unfolded RNA as a combination of helical and single strand segments. These estimates, combined with the three interaction potentials and a term to account for urea interactions with released ions, yield calculated m-values in good agreement with experimental values (200 mm monovalent salt). Agreement was obtained only if single-stranded RNAs were modeled in a highly stacked, A form conformation. The primary driving force for urea induced denaturation is the strong interaction of urea with the large surface areas of bases that become exposed upon denaturation of either RNA secondary or tertiary structure, though urea interactions with backbone and released ions may account for up to a third of the m-value. Urea m-values for all four RNA are salt-dependent, which we attribute to an increased extension (or decreased charge density) of unfolded RNAs with increased urea concentration. The sensitivity of the urea m-value to base surface exposure makes it a potentially useful probe of the conformations of RNA unfolded states. PMID:23088364

  8. A new protein structure representation for efficient protein function prediction.

    Science.gov (United States)

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

  9. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

  10. Prediction of protein folding rates from simplified secondary structure alphabet.

    Science.gov (United States)

    Huang, Jitao T; Wang, Titi; Huang, Shanran R; Li, Xin

    2015-10-21

    Protein folding is a very complicated and highly cooperative dynamic process. However, the folding kinetics is likely to depend more on a few key structural features. Here we find that secondary structures can determine folding rates of only large, multi-state folding proteins and fails to predict those for small, two-state proteins. The importance of secondary structures for protein folding is ordered as: extended β strand > α helix > bend > turn > undefined secondary structure>310 helix > isolated β strand > π helix. Only the first three secondary structures, extended β strand, α helix and bend, can achieve a good correlation with folding rates. This suggests that the rate-limiting step of protein folding would depend upon the formation of regular secondary structures and the buckling of chain. The reduced secondary structure alphabet provides a simplified description for the machine learning applications in protein design. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

    Directory of Open Access Journals (Sweden)

    Kurgan Lukasz

    2009-12-01

    Full Text Available Abstract Background Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. Results The proposed MODular Approach to Structural class prediction (MODAS method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets, depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. Conclusions The improved

  12. Distance matrix-based approach to protein structure prediction.

    Science.gov (United States)

    Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

    2009-03-01

    Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

  13. Apolipoprotein E: isoform specific differences in tertiary structure and interaction with amyloid-β in human Alzheimer brain.

    Directory of Open Access Journals (Sweden)

    Phillip B Jones

    2011-01-01

    Full Text Available We applied a novel application of FLIM-FRET to in situ measurement and quantification of protein interactions to explore isoform specific differences in Aβ-ApoE interaction and ApoE tertiary conformation in senile plaques in human Alzheimer brain. ApoE3 interacts more closely with Aβ than ApoE4, but a greater proportion of Aβ molecules within plaques are decorated with ApoE4 than ApoE3, lending strong support to the hypothesis that isoform specific differences in ApoE are linked with Aβ deposition. We found an increased number of ApoE N-terminal fragments in ApoE4 plaques, consistent with the observation that ApoE4 is more easily cleaved than ApoE3. In addition, we measured a small but significant isoform specific difference in ApoE domain interaction. Based on our in situ data, supported by traditional biochemical data, we propose a pathway by which isoform specific conformational differences increase the level of cleavage at the hinge region of ApoE4, leading to a loss of ApoE function to mediate clearance of Aβ and thereby increase the risk of AD for carriers of the APOEε4 allele.

  14. Social media use profile, social skills, and nurse-patient interaction among Registered Nurses in tertiary hospitals: A structural equation model analysis.

    Science.gov (United States)

    Mariano, Micah Celine O; Maniego, John Christian M; Manila, Hariette Lou Marie D; Mapanoo, Ram Cedrick C; Maquiran, Kerwin Miguel A; Macindo, John Rey B; Tejero, Lourdes Marie S; Torres, Gian Carlo S

    2017-12-29

    Social media has become increasingly important over the past decades and has been integrated in various environments, including the healthcare setting. Yet, the influence of social media use on the social skills and nurse-patient interaction of nurses is an area in nursing that requires further studies. This study determined the interrelationships among social media use profile, social skills, and nurse-patient interaction of Registered Nurses in tertiary hospitals. Employing structural equation modeling, a descriptive-correlational study was conducted among 212 consecutively-selected nurses from two tertiary hospitals. Consenting respondents completed a two-part survey composed of the respondent profile sheet and the Social Skills Inventory. The respondent profile sheet assessed demographic profile and social media use profile in terms of the mode, frequency, and duration of utilization. Three trained team members observed each nurse-patient dyad and completed the Nurse-Patient Bonding Instrument. A good fit model illustrated the negative effects of frequent social media use to patient openness (β = -0.18, p media on a daily basis, however, positively affected both dimensions of social skills. Accessing social media platforms using non-handheld devices showed the most influential positive effects to social skills and nurse-patient interaction. Additionally, although verbal social skills positively affected most dimensions of nurse-patient interaction, non-verbal social skills negatively influenced patient engagement (β = -0.19, p = 0.019) and nurse openness (β = -0.38, p ≤ 0.05). The structural model illustrates the effects of using social media on the social skills and nurse-patient interaction of nurses and emphasizes the need for implementing institutional policies on the judicious use and application of social media in the workplace. Further, social skills development programs geared toward having a balanced social skill must be

  15. Predictive factors for obtaining a correct therapeutic range using antivitamin K anticoagulants: a tertiary center experience of patient adherence to anticoagulant therapy

    Directory of Open Access Journals (Sweden)

    Jurcuţ R

    2015-09-01

    Full Text Available Ruxandra Jurcuţ,1 Sebastian Militaru,1 Oliviana Geavlete,1 Nic Drăgotoiu,1 Sergiu Sipoş,1 Răzvan Roşulescu,2 Carmen Ginghină,1 Ciprian Jurcuţ2 1Prof Dr CC Iliescu Emergency Institute for Cardiovascular Diseases, University of Medicine and Pharmacy, 2Dr Carol Davila Central University Emergency Military Hospital, Bucharest, Romania Background: Patient adherence is an essential factor in obtaining efficient oral anticoagulation using vitamin K antagonists (VKAs, a situation with a narrow therapeutic window. Therefore, patient education and awareness are crucial for good management. Auditing the current situation would help to identify the magnitude of the problem and to build tailored education programs for these patients. Methods: This study included 68 hospitalized chronically anticoagulated patients (mean age 62.6±13.1 years; males, 46% who responded to a 26-item questionnaire to assess their knowledge on VKA therapy management. Laboratory and clinical data were used to determine the international normalized ratio (INR at admission, as well as to calculate CHA2DS2-VASC and HAS-BLED scores for patients with atrial fibrillation. Results: The majority of patients (62% were receiving VKA for atrial fibrillation, the others for a mechanical prosthesis and previous thromboembolic disease or stroke. In the atrial fibrillation group, the mean CHA2DS2-VASC score was 3.1±1.5, while the average HAS-BLED score was 1.8±1.2. More than half of the patients (53% had an INR outside of the therapeutic range at admission, with the majority (43% having a low INR. A correct INR value was predicted by education level (higher education and the diagnostic indication (patients with mechanical prosthesis being best managed. Patients presenting with a therapeutic INR had a trend toward longer treatment duration than those outside the therapeutic range (62±72 months versus 36±35 months, respectively, P=0.06. There was no correlation between INR at admission

  16. UTILITY OF THE DECAF SCORE IN PREDICTING IN HOSPITAL OUTCOME IN PATIENTS WITH ACUTE EXACERBATION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE IN A TERTIARY CARE HOSPITAL OF SOUTHERN INDIA

    Directory of Open Access Journals (Sweden)

    Ravi Chethan Kumar A. N

    2017-09-01

    Full Text Available BACKGROUND Acute exacerbation of chronic obstructive pulmonary disease being an all too common cause for hospital admissions Worldwide poses a logistical stress for the treating physicians and hospital administration with regards to morbidity and mortality rates. Identifying upon admission those at higher risk of dying in-hospital could be useful for triaging patients to the appropriate level of care, determining the aggressiveness of therapies and timing safe discharges. The aim of this study was to evaluate the utilisation of the DECAF score in predicting in hospital outcome in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD in a Tertiary Care Hospital of Southern India. MATERIALS AND METHODS Patients admitted with COPD exacerbations in K.R. Hospital, Mysore Medical College And Research Institute, Mysuru in between the May 2017 and July 2017 were taken has study subjects. A total of 80 patients were taken into the study. The duration of hospital stay, ICU admission and deaths were noted. DECAF score is applied to all study subjects and the severity of AECOPD is graded at the time of admission. The data collected and complied were then analysed for the correlation between score and subsequent management and overall outcome. RESULTS Total of 80 patients were recruited in the study. Mean age for male was 66.47, female was 70.86. Length of hospital stay was more in patients with decaf score more than 3 (average hospital stay 10 days. Patients with DECAF score of 2, 70.4% required inhalations oxygen, remaining 29.6% were managed with only bronchodilators whereas patients with DECAF score of 5 (max score in our study group there was a 100% initiation of assisted ventilation 33.3% received NIV ventilation while 66.6% required endotracheal intubation with ventilator support. In present study, 85 percent patients were survived. Total 6 patients (7.5% had died, belonging to high risk DECAF group (score 3 to 6

  17. Tertiary lymphoid tissue

    Science.gov (United States)

    Di Caro, Giuseppe; Marchesi, Federica

    2014-01-01

    Tumor-infiltrating lymphocytes influence colorectal cancer progression. We have recently documented that tertiary lymphoid tissue in the colorectal cancer microenvironment orchestrates lymphocyte infiltration and that tertiary lymphoid tissue and lymphocytes cooperate in a coordinated antitumor immune response to improve patient outcome. Thus, tertiary lymphoid tissue represents a potential target in the design of tailored immune-based therapeutic approaches. PMID:25083321

  18. Cloud prediction of protein structure and function with PredictProtein for Debian.

    Science.gov (United States)

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

  19. Aspects of Prediction Accuracy in Human-structure Interaction

    DEFF Research Database (Denmark)

    Pedersen, Lars

    2009-01-01

    Structures such as grandstands in stadia and office floors in buildings are typically occupied by seated persons, and it is a challenge to predict the dynamic characteristics of these structures. This is because the structures and the seated persons interact when the structures undergo vibrations......, basically with the effect that the seated persons influence the dynamic system. The mechanism of the interaction is not well understood, and there are a number of factors that might influence the mechanism of the interaction. Through experiments with a vibrating floor carrying seated humans, the paper looks...... into the mechanism of the interaction focusing on its effect on dynamic structural properties. It is investigated to which extent factors such as posture of the seated persons and the construction type of the seat on which the persons are sitting have a bearing on the structural frequency and damping. This provides...

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

    Directory of Open Access Journals (Sweden)

    Murga Leonel F

    2007-04-01

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

  1. Are specialized web servers better at predicting protein structures ...

    African Journals Online (AJOL)

    RABAIL HAFEEZ (0973106)

    2012-07-03

    Jul 3, 2012 ... process of protein structure prediction. We gave the insulin sequence as input in all the stand alone software and saved the models produced as PDB files on my computer. Our next step was to use the insulin protein sequence as an input for all the web servers chosen for this research. All the web servers ...

  2. Molecular cloning, sequence analysis and structure prediction of the ...

    African Journals Online (AJOL)

    Molecular cloning, sequence analysis and structure prediction of the related to b 0,+ amino acid transporter (rBAT) in Cyprinus carpio L. ... The amplified product was 2370 bp, including a 42 bp 5'-untranslated region, a 288 bp 3'-untranslated region, and a 2040 bp open reading frame (ORF), which encoded 679 amino acids ...

  3. Cross-Disciplinary Perceptions of Structured Interprofessional Rounds in Promoting Teamwork Within an Academic Tertiary Care Obstetric Unit.

    Science.gov (United States)

    Chau, Anthony; Vijjeswarapu, Mary A; Hickey, Margaret; Acker, David; Huang, Chuan-Chin; Tsen, Lawrence C

    2017-06-01

    In 2005, physician and nursing leaders at Brigham and Women's Hospital initiated structured interprofessional rounds (SIPRs) on the labor and delivery (L&D) suite to improve team communication. We performed a cross-sectional analysis of providers' perceptions of SIPRs and their effectiveness in improving teamwork. We hypothesized that on average, providers would perceive SIPRs as being effective in promoting teamwork, but ratings would differ among professional groups. After a factor analysis and internal consistency assessment, a 19-item paper-based questionnaire was used to evaluate providers' perceptions using a 5-point Likert scale. Respondents included L&D nurses, midwives, obstetricians, and anesthesiologists who participate in SIPRs. The primary aim was to evaluate the providers' perceptions of SIPRs and their association with professional roles. The outcome was total response score for each provider, ranging from 19 to 95; perception of SIPRs as being effective in promoting teamwork was defined as having a total response score of >66.5 (mean score, >3.5 per question). A univariable linear regression model was performed, followed by a multivariable analysis adjusting for predictors that modified the outcome; predictors included years of professional practice, years of experience on the L&D suite, number of clinical work hours worked weekly, and principal shift assignment among nurses. The associations between these predictors and providers' perceptions were assessed as a secondary aim. A total of 234 practitioners responded (100% response rate). The mean total response score (SD) for all providers was 73.3 (9.5). After multivariable adjustment, the mean total response scores were significantly higher for obstetric providers than for anesthesia (Δ mean, 6.5, 95% CI, 0.3, 12.7 P = .036) and midwifery (Δ mean, 12.5, 95% CI, 2.0, 23.0, P = .009) providers. Providers scored significantly lower if they worked >60 clinical hours per week compared with ≤20 (

  4. Towards a unified fatigue life prediction method for marine structures

    CERN Document Server

    Cui, Weicheng; Wang, Fang

    2014-01-01

    In order to apply the damage tolerance design philosophy to design marine structures, accurate prediction of fatigue crack growth under service conditions is required. Now, more and more people have realized that only a fatigue life prediction method based on fatigue crack propagation (FCP) theory has the potential to explain various fatigue phenomena observed. In this book, the issues leading towards the development of a unified fatigue life prediction (UFLP) method based on FCP theory are addressed. Based on the philosophy of the UFLP method, the current inconsistency between fatigue design and inspection of marine structures could be resolved. This book presents the state-of-the-art and recent advances, including those by the authors, in fatigue studies. It is designed to lead the future directions and to provide a useful tool in many practical applications. It is intended to address to engineers, naval architects, research staff, professionals and graduates engaged in fatigue prevention design and survey ...

  5. Amphibian and reptile road-kills on tertiary roads in relation to landscape structure: using a citizen science approach with open-access land cover data.

    Science.gov (United States)

    Heigl, Florian; Horvath, Kathrin; Laaha, Gregor; Zaller, Johann G

    2017-06-26

    Amphibians and reptiles are among the most endangered vertebrate species worldwide. However, little is known how they are affected by road-kills on tertiary roads and whether the surrounding landscape structure can explain road-kill patterns. The aim of our study was to examine the applicability of open-access remote sensing data for a large-scale citizen science approach to describe spatial patterns of road-killed amphibians and reptiles on tertiary roads. Using a citizen science app we monitored road-kills of amphibians and reptiles along 97.5 km of tertiary roads covering agricultural, municipal and interurban roads as well as cycling paths in eastern Austria over two seasons. Surrounding landscape was assessed using open access land cover classes for the region (Coordination of Information on the Environment, CORINE). Hotspot analysis was performed using kernel density estimation (KDE+). Relations between land cover classes and amphibian and reptile road-kills were analysed with conditional probabilities and general linear models (GLM). We also estimated the potential cost-efficiency of a large scale citizen science monitoring project. We recorded 180 amphibian and 72 reptile road-kills comprising eight species mainly occurring on agricultural roads. KDE+ analyses revealed a significant clustering of road-killed amphibians and reptiles, which is an important information for authorities aiming to mitigate road-kills. Overall, hotspots of amphibian and reptile road-kills were next to the land cover classes arable land, suburban areas and vineyards. Conditional probabilities and GLMs identified road-kills especially next to preferred habitats of green toad, common toad and grass snake, the most often found road-killed species. A citizen science approach appeared to be more cost-efficient than monitoring by professional researchers only when more than 400 km of road are monitored. Our findings showed that freely available remote sensing data in combination with a

  6. Automatic prediction of facial trait judgments: appearance vs. structural models.

    Directory of Open Access Journals (Sweden)

    Mario Rojas

    Full Text Available Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a derive a facial trait judgment model from training data and b predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations and classification rules (4 rules suggest that a prediction of perception of facial traits is learnable by both holistic and structural approaches; b the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

  7. Ab initio prediction of transcription factor targets using structural knowledge.

    Directory of Open Access Journals (Sweden)

    2005-06-01

    Full Text Available Current approaches for identification and detection of transcription factor binding sites rely on an extensive set of known target genes. Here we describe a novel structure-based approach applicable to transcription factors with no prior binding data. Our approach combines sequence data and structural information to infer context-specific amino acid-nucleotide recognition preferences. These are used to predict binding sites for novel transcription factors from the same structural family. We demonstrate our approach on the Cys(2His(2 Zinc Finger protein family, and show that the learned DNA-recognition preferences are compatible with experimental results. We use these preferences to perform a genome-wide scan for direct targets of Drosophila melanogaster Cys(2His(2 transcription factors. By analyzing the predicted targets along with gene annotation and expression data we infer the function and activity of these proteins.

  8. Application of Functional Use Predictions to Aid in Structure ...

    Science.gov (United States)

    Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

  9. PASSML: combining evolutionary inference and protein secondary structure prediction.

    Science.gov (United States)

    Liò, P; Goldman, N; Thorne, J L; Jones3, D T

    1998-01-01

    Evolutionary models of amino acid sequences can be adapted to incorporate structure information; protein structure biologists can use phylogenetic relationships among species to improve prediction accuracy. Results : A computer program called PASSML ('Phylogeny and Secondary Structure using Maximum Likelihood') has been developed to implement an evolutionary model that combines protein secondary structure and amino acid replacement. The model is related to that of Dayhoff and co-workers, but we distinguish eight categories of structural environment: alpha helix, beta sheet, turn and coil, each further classified according to solvent accessibility, i.e. buried or exposed. The model of sequence evolution for each of the eight categories is a Markov process with discrete states in continuous time, and the organization of structure along protein sequences is described by a hidden Markov model. This paper describes the PASSML software and illustrates how it allows both the reconstruction of phylogenies and prediction of secondary structure from aligned amino acid sequences. PASSML 'ANSI C' source code and the example data sets described here are available at http://ng-dec1.gen.cam.ac.uk/hmm/Passml.html and 'downstream' Web pages. P.Lio@gen.cam.ac.uk

  10. Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction.

    Science.gov (United States)

    Saraswathi, S; Fernández-Martínez, J L; Kolinski, A; Jernigan, R L; Kloczkowski, A

    2012-09-01

    Computational methods are rapidly gaining importance in the field of structural biology, mostly due to the explosive progress in genome sequencing projects and the large disparity between the number of sequences and the number of structures. There has been an exponential growth in the number of available protein sequences and a slower growth in the number of structures. There is therefore an urgent need to develop computational methods to predict structures and identify their functions from the sequence. Developing methods that will satisfy these needs both efficiently and accurately is of paramount importance for advances in many biomedical fields, including drug development and discovery of biomarkers. A novel method called fast learning optimized prediction methodology (FLOPRED) is proposed for predicting protein secondary structure, using knowledge-based potentials combined with structure information from the CATH database. A neural network-based extreme learning machine (ELM) and advanced particle swarm optimization (PSO) are used with this data that yield better and faster convergence to produce more accurate results. Protein secondary structures are predicted reliably, more efficiently and more accurately using FLOPRED. These techniques yield superior classification of secondary structure elements, with a training accuracy ranging between 83 % and 87 % over a widerange of hidden neurons and a cross-validated testing accuracy ranging between 81 % and 84 % and a segment overlap (SOV) score of 78 % that are obtained with different sets of proteins. These results are comparable to other recently published studies, but are obtained with greater efficiencies, in terms of time and cost.

  11. Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins.

    Science.gov (United States)

    Yang, Jing; He, Bao-Ji; Jang, Richard; Zhang, Yang; Shen, Hong-Bin

    2015-12-01

    Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g., >3 bonds, is too low to effectively assist structure assembly simulations. We propose a new hierarchical order reduction protocol called Cyscon for disulfide-bonding prediction. The most confident disulfide bonds are first identified and bonding prediction is then focused on the remaining cysteine residues based on SVR training. Compared with purely machine learning-based approaches, Cyscon improved the average accuracy of connectivity pattern prediction by 21.9%. For proteins with more than 5 disulfide bonds, Cyscon improved the accuracy by 585% on the benchmark set of PDBCYS. When applied to 158 non-redundant cysteine-rich proteins, Cyscon predictions helped increase (or decrease) the TM-score (or RMSD) of the ab initio QUARK modeling by 12.1% (or 14.4%). This result demonstrates a new avenue to improve the ab initio structure modeling for cysteine-rich proteins. http://www.csbio.sjtu.edu.cn/bioinf/Cyscon/ zhng@umich.edu or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Prediction of Elastic-Plastic Behaviour of Structures at Notches

    Directory of Open Access Journals (Sweden)

    Tanweer Hussain

    2012-07-01

    Full Text Available Under the condition of elastic-plastic deformation, aero engine casings experience local stress and strain concentrations along with associated variations in load paths and stiffness. The accurate prediction of such behaviour is clearly necessary for design optimisation, potentially leading to beneficial weight savings. The present research seeks to tackle the objective of accurate characterisation of elasticplastic casing behaviour. The objective is to develop approximate techniques for predicting the elasticplastic behaviour, for both generalised load-displacement responses (i.e. for global response and notch stress-strain responses. Accurate prediction of the stress-strain distribution at a notch is difficult and existing notch prediction techniques can only be used for small strains. This paper seeks to develop novel techniques for predicting large elastic-plastic notch strain and associated stresses, with application to aero engine casing notches. The repeated local joints at the spoke-shell casing are of particular interest as they are the most likely sites for plastic deformation and possibly crack initiation. These local joints incorporate realistic notch-type features and the load cases cover a range of loading combinations, to develop insight and understanding of the elastic-plastic behaviour. This work analyse a double edgenotched flat bar with semicircular notches and a representative case of actual aero engine casing-type structures in a more simplified form. The investigation was carried out for structures for which stress and total strain are related by a power law. The equivalent stress at a notch can be estimated, given the value of n, by a linear interpolation between the stresses for a cases n=1 and n=0. The application of the notch stress-strain prediction method is illustrated through use of examples of notch components. The predictions are compared with results obtained using finite element analyses and approximate methods

  13. Mesoscopic structure prediction of nanoparticle assembly and coassembly: Theoretical foundation

    KAUST Repository

    Hur, Kahyun

    2010-01-01

    In this work, we present a theoretical framework that unifies polymer field theory and density functional theory in order to efficiently predict ordered nanostructure formation of systems having considerable complexity in terms of molecular structures and interactions. We validate our approach by comparing its predictions with previous simulation results for model systems. We illustrate the flexibility of our approach by applying it to hybrid systems composed of block copolymers and ligand coated nanoparticles. We expect that our approach will enable the treatment of multicomponent self-assembly with a level of molecular complexity that approaches experimental systems. © 2010 American Institute of Physics.

  14. JEWEL predictions for Jet structure modifications at RHIC

    Science.gov (United States)

    Verma, Aditya; Kunnawalkam Elayavalli, Raghav; Salur, Sevil

    2017-09-01

    RHIC is ideally suited to investigate transport and tomographic properties of the quark gluon plasma in heavy ion collisions using fully reconstructed jets as hard probes. In this poster, we present predictions for inclusive di-jet and jet structure observables sensitive to jet-medium interactions. This is accomplished by harnessing JEWEL, a Monte Carlo event generator for heavy ion collisions with its updated medium recoil information. With JEWEL's successful record of predictions at the LHC, studying its performance at RHIC energies can precipitate an improved understanding of the jet quenching phenomena.

  15. PDBalert: automatic, recurrent remote homology tracking and protein structure prediction

    Directory of Open Access Journals (Sweden)

    Söding Johannes

    2008-11-01

    Full Text Available Abstract Background During the last years, methods for remote homology detection have grown more and more sensitive and reliable. Automatic structure prediction servers relying on these methods can generate useful 3D models even below 20% sequence identity between the protein of interest and the known structure (template. When no homologs can be found in the protein structure database (PDB, the user would need to rerun the same search at regular intervals in order to make timely use of a template once it becomes available. Results PDBalert is a web-based automatic system that sends an email alert as soon as a structure with homology to a protein in the user's watch list is released to the PDB database or appears among the sequences on hold. The mail contains links to the search results and to an automatically generated 3D homology model. The sequence search is performed with the same software as used by the very sensitive and reliable remote homology detection server HHpred, which is based on pairwise comparison of Hidden Markov models. Conclusion PDBalert will accelerate the information flow from the PDB database to all those who can profit from the newly released protein structures for predicting the 3D structure or function of their proteins of interest.

  16. Predicting protein structures with a multiplayer online game.

    Science.gov (United States)

    Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

    2010-08-05

    People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

  17. Comparing Coronal Structure Predictions to CATE Eclipse Observations

    Science.gov (United States)

    Kovac, Sarah A.; Citizen CATE Experiment 2017 Team

    2018-01-01

    The total solar eclipse of the sun on 21 August 2017 crossed the entire continental United States, giving the opportunity for millions of people to see this spectacular celestial event. The Citizen Continental America Telescopic Eclipse Experiment, or Citizen CATE, captured roughly 90 minutes of totality data from 62 identical setups along the path. Prior to the eclipse, the appearance of the corona was predicted using images from ground and satellite telescopes. The size of the coronal holes on the surface of the sun and the polar plumes extending out into the corona have been examined to predict the features in the corona during totality. By looking at trends in large-scale features, such as streamers, and long-lasting features, such as coronal holes, the atmosphere of the sun can be predicted with reasonable accuracy. This prediction is then compared to other forecast models and what was captured on eclipse day. This experiment imaged the total solar eclipse in 2016 and developed a prediction method extrapolating from the data gathered in Indonesia. The same prediction method was used to forecast the structures expected in the corona on 21 August 2017.

  18. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

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

  19. Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Cobaugh Christian W

    2004-08-01

    Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

  20. Constraint Logic Programming approach to protein structure prediction

    Directory of Open Access Journals (Sweden)

    Fogolari Federico

    2004-11-01

    Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

  1. Virality prediction and community structure in social networks.

    Science.gov (United States)

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  2. Virality Prediction and Community Structure in Social Networks

    Science.gov (United States)

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-08-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  3. Predictive simulation of guide-wave structural health monitoring

    Science.gov (United States)

    Giurgiutiu, Victor

    2017-04-01

    This paper presents an overview of recent developments on predictive simulation of guided wave structural health monitoring (SHM) with piezoelectric wafer active sensor (PWAS) transducers. The predictive simulation methodology is based on the hybrid global local (HGL) concept which allows fast analytical simulation in the undamaged global field and finite element method (FEM) simulation in the local field around and including the damage. The paper reviews the main results obtained in this area by researchers of the Laboratory for Active Materials and Smart Structures (LAMSS) at the University of South Carolina, USA. After thematic introduction and research motivation, the paper covers four main topics: (i) presentation of the HGL analysis; (ii) analytical simulation in 1D and 2D; (iii) scatter field generation; (iv) HGL examples. The paper ends with summary, discussion, and suggestions for future work.

  4. A Memetic Algorithm for 3-D Protein Structure Prediction Problem.

    Science.gov (United States)

    Correa, Leonardo; Borguesan, Bruno; Farfan, Camilo; Inostroza-Ponta, Mario; Dorn, Marcio

    2016-12-02

    Memetic Algorithms are population-based metaheuristics intrinsically concerned with exploiting all available knowledge about the problem under study. The incorporation of problem domain knowledge is not an optional mechanism, but a fundamental feature of the Memetic Algorithms. In this paper, we present a Memetic Algorithm to tackle the three-dimensional protein structure prediction problem. The method uses a structured population and incorporates a Simulated Annealing algorithm as a local search strategy, as well as ad-hoc crossover and mutation operators to deal with the problem. It takes advantage of structural knowledge stored in the Protein Data Bank, by using an Angle Probability List that helps to reduce the search space and to guide the search strategy. The proposed algorithm was tested on nineteen protein sequences of amino acid residues, and the results show the ability of the algorithm to find native-like protein structures. Experimental results have revealed that the proposed algorithm can find good solutions regarding root-mean-square deviation and global distance total score test in comparison with the experimental protein structures. We also show that our results are comparable in terms of folding organization with state-of-the-art prediction methods, corroborating the effectiveness of our proposal.

  5. Protein structure prediction of CASP5 comparative modeling and fold recognition targets using consensus alignment approach and 3D assessment.

    Science.gov (United States)

    Ginalski, Krzysztof; Rychlewski, Leszek

    2003-01-01

    For the fifth round of Critical Assessment of Techniques for Protein Structure Prediction (CASP5) all comparative modeling (CM) and fold recognition (FR) target proteins were modeled using a combination of consensus alignment strategy and 3D assessment. A large number and broad variety of prediction targets, with sequence identity between each modeled domain and the related known structure, ranging from 6 to 49%, represented all difficulty levels in comparative modeling and fold recognition. The critical steps in modeling, selection of template(s) and generation of sequence-to-structure alignment, were based on the results of secondary structure prediction and tertiary fold recognition carried out using the Meta Server coupled with the 3D-Jury system. The main idea behind the modeling procedure was to select the most common alignment variants provided by individual servers, as well as to generate several alternatives for questionable regions and to evaluate them in 3D by building corresponding molecular models. Analysis of fold-specific features and sequence conservation patterns for the target family was also widely used at this stage. For both CM and FR targets remote homologs of known structure were clearly recognized by the 3D-Jury system. In the analogous fold recognition subcategory, the correct fold was identified for five out of eight domains. The average alignment accuracy for FR models (48%) was far less than for CM predictions (80%). These finding, coupled with the observation that in the majority of cases the submitted models were not closer to the experimental structure than their best templates, indicate that, especially for difficult targets, there is still ample room for improvement. Copyright 2003 Wiley-Liss, Inc.

  6. Controlled crystal dehydration triggers a space-group switch and shapes the tertiary structure of cytomegalovirus immediate-early 1 (IE1) protein.

    Science.gov (United States)

    Klingl, Stefan; Scherer, Myriam; Stamminger, Thomas; Muller, Yves A

    2015-07-01

    Cytomegalovirus immediate-early 1 (IE1) protein is a key viral effector protein that reprograms host cells. Controlled dehydration experiments with IE1 crystals not only extended their diffraction limit from 2.85 to 2.3 Å resolution but also triggered a monoclinic to tetragonal space-group transition with only minor alterations in the unit-cell parameters. An analysis of the pre-dehydration and post-dehydration crystal structures shows how dehydration rearranges the packing of IE1 molecules to meet the unit-cell constraints of the higher lattice symmetry. The transition from P21 to P43 reduces the number of copies in the asymmetric unit from four to two, and molecules previously related by noncrystallographic symmetry merge into identical crystallographic copies in the tetragonal space group. At the same time, dehydration considerably alters the tertiary structure of one of the two remaining IE1 chains in the asymmetric unit. It appears that this conformational switch is required to compensate for a transition that is assumed to be unfavourable, namely from a highly preferred to a rarely observed space group. At the same time, the dehydration-triggered molecular reshaping could reveal an inherent molecular flexibility that possibly informs on the biological function of IE1, namely on its binding to target proteins from the host cell.

  7. Quantifying Confidence in Model Predictions for Hypersonic Aircraft Structures

    Science.gov (United States)

    2015-03-01

    and Driscoll, J.F. (2011). “Uncertainty propagation in integrated airframe- propulsion system analysis for hypersonic vehicles.” Proc., 17th AIAA Intl...AFRL-RQ-WP-TR-2015-0069 QUANTIFYING CONFIDENCE IN MODEL PREDICTIONS FOR HYPERSONIC AIRCRAFT STRUCTURES Benjamin P. Smarslok Hypersonic ...Signature// BENJAMIN P. SMARSLOK MEI-LING LIBER, Branch Chief Program Manager Hypersonic Sciences Branch Hypersonic Sciences Branch

  8. A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences

    Directory of Open Access Journals (Sweden)

    Jyh-Jong Tsay

    2015-07-01

    Full Text Available Protein structure prediction (PSP is concerned with the prediction of protein tertiary structure from primary structure and is a challenging calculation problem. After decades of research effort, numerous solutions have been proposed for optimisation methods based on energy models. However, further investigation and improvement is still needed to increase the accuracy and similarity of structures. This study presents a novel backbone angle preference factor, which is one of the factors inducing protein folding. The proposed multiobjective optimisation approach simultaneously considers energy models and backbone angle preferences to solve the ab initio PSP. To prove the effectiveness of the multiobjective optimisation approach based on the energy models and backbone angle preferences, 75 amino acid sequences with lengths ranging from 22 to 88 amino acids were selected from the CB513 data set to be the benchmarks. The data sets were highly dissimilar, therefore indicating that they are meaningful. The experimental results showed that the root-mean-square deviation (RMSD of the multiobjective optimization approach based on energy model and backbone angle preferences was superior to those of typical energy models, indicating that the proposed approach can facilitate the ab initio PSP.

  9. Functional structure of biological communities predicts ecosystem multifunctionality.

    Directory of Open Access Journals (Sweden)

    David Mouillot

    Full Text Available The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF. Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.

  10. Ranking beta sheet topologies with applications to protein structure prediction

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2011-01-01

    One reason why ab initio protein structure predictors do not perform very well is their inability to reliably identify long-range interactions between amino acids. To achieve reliable long-range interactions, all potential pairings of ß-strands (ß-topologies) of a given protein are enumerated...... of this paper is a method to deal with the inaccuracies of secondary structure predictors when enumerating potential ß-topologies. The results reported in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. They indicate that decoy generation can......, consistently top-ranks native ß-topologies. Since the number of potential ß-topologies grows exponentially with the number of ß-strands, it is unrealistic to expect that all potential ß-topologies can be enumerated for large proteins. The second result of this paper is an enumeration scheme of a subset of ß...

  11. Structure prediction and validation of the ERK8 kinase domain.

    Directory of Open Access Journals (Sweden)

    Angela Strambi

    Full Text Available Extracellular signal-regulated kinase 8 (ERK8 has been already implicated in cell transformation and in the protection of genomic integrity and, therefore, proposed as a novel potential therapeutic target for cancer. In the absence of a crystal structure, we developed a three-dimensional model for its kinase domain. To validate our model we applied a structure-based virtual screening protocol consisting of pharmacophore screening and molecular docking. Experimental characterization of the hit compounds confirmed that a high percentage of the identified scaffolds was able to inhibit ERK8. We also confirmed an ATP competitive mechanism of action for the two best-performing molecules. Ultimately, we identified an ERK8 drug-resistant "gatekeeper" mutant that corroborated the predicted molecular binding mode, confirming the reliability of the generated structure. We expect that our model will be a valuable tool for the development of specific ERK8 kinase inhibitors.

  12. Prediction of Cracking Induced by Indirect Actions in RC Structures

    Science.gov (United States)

    Anerdi, Costanza; Bertagnoli, Gabriele; Gino, Diego; Malavisi, Marzia; Mancini, Giuseppe

    2017-10-01

    Cracking of concrete plays a key role in reinforced concrete (RC) structures design, especially in serviceability conditions. A variety of reasons contribute to develop cracking and its presence in concrete structures is to be considered as almost unavoidable. Therefore, a good control of the phenomenon in order to provide durability is required. Cracking development is due to tensile stresses that arise in concrete structures as a result of the action of direct external loads or restrained endogenous deformations. This paper focuses on cracking induced by indirect actions. In fact, there is very limited literature regarding this particular phenomenon if compared to its high incidence in the construction practice. As a consequence, the correct prediction of the crack opening, width and position when structures are subjected to imposed deformations, such as massive castings or other highly restrained structures, becomes a compelling task, not so much for the structural capacity, as for their durability. However, this is only partially addressed by commonly used design methods, which are usually intended for direct actions. A set of non-linear analysis on simple tie models is performed using the Finite Element Method in order to study the cracking process under imposed deformations. Different concrete grades have been considered and analysed. The results of this study have been compared with the provisions of the most common codes.

  13. De novo backbone and sequence design of an idealized alpha/beta-barrel protein: evidence of stable tertiary structure.

    Science.gov (United States)

    Offredi, F; Dubail, F; Kischel, P; Sarinski, K; Stern, A S; Van de Weerdt, C; Hoch, J C; Prosperi, C; François, J M; Mayo, S L; Martial, J A

    2003-01-03

    We have designed, synthesized, and characterized a 216 amino acid residue sequence encoding a putative idealized alpha/beta-barrel protein. The design was elaborated in two steps. First, the idealized backbone was defined with geometric parameters representing our target fold: a central eight parallel-stranded beta-sheet surrounded by eight parallel alpha-helices, connected together with short structural turns on both sides of the barrel. An automated sequence selection algorithm, based on the dead-end elimination theorem, was used to find the optimal amino acid sequence fitting the target structure. A synthetic gene coding for the designed sequence was constructed and the recombinant artificial protein was expressed in bacteria, purified and characterized. Far-UV CD spectra with prominent bands at 222nm and 208nm revealed the presence of alpha-helix secondary structures (50%) in fairly good agreement with the model. A pronounced absorption band in the near-UV CD region, arising from immobilized aromatic side-chains, showed that the artificial protein is folded in solution. Chemical unfolding monitored by tryptophan fluorescence revealed a conformational stability (DeltaG(H2O)) of 35kJ/mol. Thermal unfolding monitored by near-UV CD revealed a cooperative transition with an apparent T(m) of 65 degrees C. Moreover, the artificial protein did not exhibit any affinity for the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulfonic acid (ANS), providing additional evidence that the artificial barrel is not in the molten globule state, contrary to previously designed artificial alpha/beta-barrels. Finally, 1H NMR spectra of the folded and unfolded proteins provided evidence for specific interactions in the folded protein. Taken together, the results indicate that the de novo designed alpha/beta-barrel protein adopts a stable three-dimensional structure in solution. These encouraging results show that de novo design of an idealized protein structure of more than 200

  14. Strain Concentration at Structural Discontinuities and Its Prediction Based on Characteristics of Compliance Change in Structures

    Science.gov (United States)

    Kasahara, Naoto

    Elevated temperature structural design codes pay attention to strain concentration at structural discontinuities due to creep and plasticity, since it causes an increase in creep-fatigue damage of materials. One of the difficulties in predicting strain concentration is its dependence on the magnitude of loading, the constitutive equations, and the duration of loading. In this study, the author investigated the fundamental mechanism of strain concentration and its main factors. The results revealed that strain concentration is caused by strain redistribution between elastic and inelastic regions, which can be quantified by the characteristics of structural compliance. The characteristics of structural compliance are controlled by elastic region in structures and are insensitive to constitutive equations. It means that inelastic analysis can be easily applied to obtain compliance characteristics. By utilizing this fact, a simplified inelastic analysis method was proposed based on the characteristics of compliance change for the prediction of strain concentration.

  15. Role of Tertiary Lymphoid Structures (TLS) in Anti-Tumor Immunity: Potential Tumor-Induced Cytokines/Chemokines that Regulate TLS Formation in Epithelial-Derived Cancers

    Energy Technology Data Exchange (ETDEWEB)

    Pimenta, Erica M. [Rutgers Biomedical and Health Sciences, New Jersey Medical School-Cancer Center, Newark, NJ 07103 (United States); Barnes, Betsy J., E-mail: barnesbe@njms.rutgers.edu [Department of Biochemistry and Molecular Biology, Rutgers Biomedical and Health Sciences, New Jersey Medical School-Cancer Center, Newark, NJ 07103 (United States)

    2014-04-23

    Following the successes of monoclonal antibody immunotherapies (trastuzumab (Herceptin{sup ®}) and rituximab (Rituxan{sup ®})) and the first approved cancer vaccine, Provenge{sup ®} (sipuleucel-T), investigations into the immune system and how it can be modified by a tumor has become an exciting and promising new field of cancer research. Dozens of clinical trials for new antibodies, cancer and adjuvant vaccines, and autologous T and dendritic cell transfers are ongoing in hopes of identifying ways to re-awaken the immune system and force an anti-tumor response. To date, however, few consistent, reproducible, or clinically-relevant effects have been shown using vaccine or autologous cell transfers due in part to the fact that the immunosuppressive mechanisms of the tumor have not been overcome. Much of the research focus has been on re-activating or priming cytotoxic T cells to recognize tumor, in some cases completely disregarding the potential roles that B cells play in immune surveillance or how a solid tumor should be treated to maximize immunogenicity. Here, we will summarize what is currently known about the induction or evasion of humoral immunity via tumor-induced cytokine/chemokine expression and how formation of tertiary lymphoid structures (TLS) within the tumor microenvironment may be used to enhance immunotherapy response.

  16. Role of Tertiary Lymphoid Structures (TLS in Anti-Tumor Immunity: Potential Tumor-Induced Cytokines/Chemokines that Regulate TLS Formation in Epithelial-Derived Cancers

    Directory of Open Access Journals (Sweden)

    Erica M. Pimenta

    2014-04-01

    Full Text Available Following the successes of monoclonal antibody immunotherapies (trastuzumab (Herceptin® and rituximab (Rituxan® and the first approved cancer vaccine, Provenge® (sipuleucel-T, investigations into the immune system and how it can be modified by a tumor has become an exciting and promising new field of cancer research. Dozens of clinical trials for new antibodies, cancer and adjuvant vaccines, and autologous T and dendritic cell transfers are ongoing in hopes of identifying ways to re-awaken the immune system and force an anti-tumor response. To date, however, few consistent, reproducible, or clinically-relevant effects have been shown using vaccine or autologous cell transfers due in part to the fact that the immunosuppressive mechanisms of the tumor have not been overcome. Much of the research focus has been on re-activating or priming cytotoxic T cells to recognize tumor, in some cases completely disregarding the potential roles that B cells play in immune surveillance or how a solid tumor should be treated to maximize immunogenicity. Here, we will summarize what is currently known about the induction or evasion of humoral immunity via tumor-induced cytokine/chemokine expression and how formation of tertiary lymphoid structures (TLS within the tumor microenvironment may be used to enhance immunotherapy response.

  17. Isotopic and anatomical evidence of an herbivorous diet in the Early Tertiary giant bird Gastornis. Implications for the structure of Paleocene terrestrial ecosystems

    Science.gov (United States)

    Angst, D.; Lécuyer, C.; Amiot, R.; Buffetaut, E.; Fourel, F.; Martineau, F.; Legendre, S.; Abourachid, A.; Herrel, A.

    2014-04-01

    The mode of life of the early Tertiary giant bird Gastornis has long been a matter of controversy. Although it has often been reconstructed as an apex predator feeding on small mammals, according to other interpretations, it was in fact a large herbivore. To determine the diet of this bird, we analyze here the carbon isotope composition of the bone apatite from Gastornis and contemporaneous herbivorous mammals. Based on 13C-enrichment measured between carbonate and diet of carnivorous and herbivorous modern birds, the carbonate δ13C values of Gastornis bone remains, recovered from four Paleocene and Eocene French localities, indicate that this bird fed on plants. This is confirmed by a morphofunctional study showing that the reconstructed jaw musculature of Gastornis was similar to that of living herbivorous birds and unlike that of carnivorous forms. The herbivorous Gastornis was the largest terrestrial tetrapod in the Paleocene biota of Europe, unlike the situation in North America and Asia, where Gastornis is first recorded in the early Eocene, and the largest Paleocene animals were herbivorous mammals. The structure of the Paleocene terrestrial ecosystems of Europe may have been similar to that of some large islands, notably Madagascar, prior to the arrival of humans.

  18. Structural basis of light chain amyloidogenicity: comparison of the thermodynamic properties, fibrillogenic potential and tertiary structural features of four vλ6 proteins

    Energy Technology Data Exchange (ETDEWEB)

    Wall, J.S.; Gupta, V.; Wilkerson, M.; Schell, M.; Loris, R.; Adams, P.; Solomon, A.; Stevens, F.; Dealwis, C.

    2004-04-01

    Primary (AL) amyloidosis results from the pathologic deposition of monoclonal light chains as amyloid fibrils. Studies of recombinant-derived variable region (V{sub L}) fragments of these proteins have shown an inverse relationship between thermodynamic stability and fibrillogenic potential. Further, ionic interactions within the V{sub L} domain were predicted to influence the kinetics of light chain fibrillogenicity, as evidenced from our analyses of a relatively stable V{sub {lambda}}6 protein (Jto) with a long range electrostatic interaction between Asp and Arg side chains at position 29 and 68, respectively, and an unstable, highly fibrillogenic V{sub {lambda}}6 protein (Wil) that had neutral amino acids at these locations. To test this hypothesis, we have generated two Jto-related mutants designed to disrupt the interaction between Asp 29 and Arg 68 (JtoD29A and JtoR68S). Although the thermodynamic stabilities of unfolding for these two molecules were identical, they exhibited very different kinetics of fibril formation: the rate of JtoD29A fibrillogenesis was slow and comparable to the parent molecule, whereas that of JtoR68S was significantly faster. High-resolution X-ray diffraction analyses of crystals prepared from the two mutants having the same space group and unit cell dimensions revealed no significant main-chain conformational changes. However, several notable side-chain alterations were observed in JtoR68S, as compared with JtoD29A, that resulted in the solvent exposure of a greater hydrophobic surface and modifications in the electrostatic potential surface. We posit that these differences contributed to the enhanced fibrillogenic potential of the Arg 68 mutant, since both Jto mutants lacked the intrachain ionic interaction and were equivalently unstable. The information gleaned from our studies has provided insight into structural parameters that in addition to overall thermodynamic stability, contribute to the fibril forming propensity of

  19. Prediction of Noise Transmission in Lightweight Building Structures

    DEFF Research Database (Denmark)

    Dickow, Kristoffer Ahrens

    groups, where one group shows pass band/stop band behavior, while the other has a nearly uniform distribution of modes. The suggested approach for SEA adaptation is to consider a ribbed plate as two SEA subsystems: One that contains modes related to waves traveling in the direction orthogonal to the ribs...... degree of off-site assembly allows for a high quality production and helps minimize both production costs and the risk of unforeseen events that could otherwise lead to costly delays. The standard EN 12354, describing a simplified statistical energy analysis (SEA) subsystem approach, provides a valuable...... result in imprecise predictions. Furthermore, lightweight buildings have low-frequency problems due to the low mass of the structure and often unpredictability (variation) between the building acoustic performance of supposedly identical dwellings can be observed. Therefore, better prediction methods...

  20. Structural syntactic prediction measured with ELAN: evidence from ERPs.

    Science.gov (United States)

    Fonteneau, Elisabeth

    2013-02-08

    The current study used event-related potentials (ERPs) to investigate how and when argument structure information is used during the processing of sentences with a filler-gap dependency. We hypothesize that one specific property - animacy (living vs. non-living) - is used by the parser during the building of the syntactic structure. Participants heard sentences that were rated off-line as having an expected noun (Who did the Lion King chase the caravan with?) or an unexpected noun (Who did Lion King chase the animal with?). This prediction is based on the animacy properties relation between the wh-word and the noun in the object position. ERPs from the noun in the unexpected condition (animal) elicited a typical Early Left Anterior Negativity (ELAN)/P600 complex compared to the noun in the expected condition (caravan). Firstly, these results demonstrate that the ELAN reflects not only grammatical category violation but also animacy property expectations in filler-gap dependency. Secondly, our data suggests that the language comprehension system is able to make detailed predictions about aspects of the upcoming words to build up the syntactic structure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  1. Offspring social network structure predicts fitness in families.

    Science.gov (United States)

    Royle, Nick J; Pike, Thomas W; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

    2012-12-22

    Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

  2. Intermolecular force field development and crystal structure prediction

    Science.gov (United States)

    Gao, Daquan

    1998-11-01

    Chapter 1 is a general introduction for the following chapters that include three journal articles. Chapter 2 deals with force field development about a particular compound, Cl2. The crystal structure of Cl2 has been simulated by an isotropic force field that includes polar flattening of the Cl atom and a 5-center distributed monopole model. Polar flattening is achieved by moving the repulsion center toward the molecular center, which induces the short contact. The 5- center distributed monopole represents the molecular electrical potential that dictates the molecular orientation in the cell. This intermolecular force field can approximate the correct space group symmetry of solid state chlorine. Chapter 3 reports the implementation of a systematic way of developing intermolecular force field parameters. Intermolecular atom-atom force field parameters of the (exp-6-1) type for boron and hydrogen atoms in boron hydrides were determined. Using the resulting force field, minimum energy crystal structures were found with structural parameter values close to those of the observed structures. Chapter 4 discusses the new finding on space groups. Relationships between space groups, molecular symmetry and site symmetry, and molecular packing groups are treated. The number of molecules in the cell, Z, is the same as the order of the molecular packing group. The order of the space group is equal to or greater than Z depending upon the site symmetry of the molecular position. Several examples of application of this packing group treatment to ab initio crystal structure predictions are given.

  3. A probabilistic fragment-based protein structure prediction algorithm.

    Science.gov (United States)

    Simoncini, David; Berenger, Francois; Shrestha, Rojan; Zhang, Kam Y J

    2012-01-01

    Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

  4. Leveraging structure for enzyme function prediction: methods, opportunities, and challenges.

    Science.gov (United States)

    Jacobson, Matthew P; Kalyanaraman, Chakrapani; Zhao, Suwen; Tian, Boxue

    2014-08-01

    The rapid growth of the number of protein sequences that can be inferred from sequenced genomes presents challenges for function assignment, because only a small fraction (currently predict functions of uncharacterized proteins. Recently, there has been significant progress in using protein structures as an additional source of information to infer aspects of enzyme function, which is the focus of this review. Successful application of these approaches has led to the identification of novel metabolites, enzyme activities, and biochemical pathways. We discuss opportunities to elucidate systematically protein domains of unknown function, orphan enzyme activities, dead-end metabolites, and pathways in secondary metabolism. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. The systematic structure and predictability of urban business diversity

    CERN Document Server

    Youn, Hyejin; Lobo, José; Strumsky, Deborah; Samaniego, Horacio; West, Geoffrey B

    2014-01-01

    Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large datasets. Here, we study abundances of business categories across U.S. metropolitan statistical areas to investigate how diversity of economic activities depends on city size. A universal structure common to all cities is revealed, manifesting self-similarity in internal economic structure as well as aggregated metrics (GDP, patents, crime). A derivation is presented that explains universality and the observed empirical distribution. The model incorporates a generalized preferential attachment process with ceaseless introduction of new business types. Combined with scaling analyses for individual categories, the theory quantitatively predicts how individual business types systematically change rank ...

  6. Predicting fracture in micron-scale polycrystalline silicon MEMS structures.

    Energy Technology Data Exchange (ETDEWEB)

    Hazra, Siddharth S. (Carnegie Mellon University, Pittsburgh, PA); de Boer, Maarten Pieter (Carnegie Mellon University, Pittsburgh, PA); Boyce, Brad Lee; Ohlhausen, James Anthony; Foulk, James W., III; Reedy, Earl David, Jr.

    2010-09-01

    Designing reliable MEMS structures presents numerous challenges. Polycrystalline silicon fractures in a brittle manner with considerable variability in measured strength. Furthermore, it is not clear how to use a measured tensile strength distribution to predict the strength of a complex MEMS structure. To address such issues, two recently developed high throughput MEMS tensile test techniques have been used to measure strength distribution tails. The measured tensile strength distributions enable the definition of a threshold strength as well as an inferred maximum flaw size. The nature of strength-controlling flaws has been identified and sources of the observed variation in strength investigated. A double edge-notched specimen geometry was also tested to study the effect of a severe, micron-scale stress concentration on the measured strength distribution. Strength-based, Weibull-based, and fracture mechanics-based failure analyses were performed and compared with the experimental results.

  7. Prediction of Halocarbon Toxicity from Structure: A Hierarchical QSAR Approach

    Energy Technology Data Exchange (ETDEWEB)

    Gute, B D; Balasubramanian, K; Geiss, K; Basak, S C

    2003-04-11

    Mathematical structural invariants and quantum theoretical descriptors have been used extensively in quantitative structure-activity relationships (QSARs) for the estimation of pharmaceutical activities, biological properties, physicochemical properties, and the toxicities of chemicals. Recently our research team has explored the relative importance of various levels of chemodescriptors, i.e., topostructural, topochemical, geometrical, and quantum theoretical descriptors, in property estimation. This study examines the contribution of chemodescriptors ranging from topostructural to quantum theoretic calculations up to the Gaussian STO-3G level in the prediction of the toxicity of a set of twenty halocarbons. We also report the results of experimental cell-level toxicity studies on these twenty halocarbons to validate our models.

  8. PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics

    Directory of Open Access Journals (Sweden)

    Rychlewski Leszek

    2006-02-01

    Full Text Available Abstract Background The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB. Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. Results Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0, for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. Conclusion We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. Availability http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF

  9. Alpha-amylase from mung beans (Vigna radiata)--correlation of biochemical properties and tertiary structure by homology modelling.

    Science.gov (United States)

    Tripathi, Pallavi; Lo Leggio, Leila; Mansfeld, Johanna; Ulbrich-Hofmann, Renate; Kayastha, Arvind M

    2007-06-01

    Alpha-amylase from germinated mung beans (Vigna radiata) has been purified 600-fold to electrophoretic homogeneity and a final specific activity of 437 U/mg. SDS-PAGE of the final preparation revealed a single protein band of 46 kDa. The optimum pH was 5.6. The energy of activation was determined to be 7.03 kcal/mol in the temperature range 15-55 degrees C. Km for starch was 1.6 mg/mL in 50 mM sodium acetate buffer, pH 5.5. Thermal inactivation studies at 70 degrees C showed first-order kinetics with rate constant (k) equal to 0.005 min(-1). Mung bean alpha-amylase showed high specificity for its primary substrate starch. Addition of EDTA (10 mM) caused irreversible loss of activity. Mung bean alpha-amylase is inhibited in a non-competitive manner by heavy metal ions, for example, mercury with a Ki of 110 microM. Homology modelling studies with mung bean alpha-amylase using barley alpha-amylases Amy 1 and Amy 2 as templates showed a very similar structure as expected from the high sequence identity. The model showed that alpha-amylase from mung beans has no sugar-binding site, instead it has a methionine. Furthermore, instead of two tryptophans, it has Val(277) and Lys(278), which are the conserved residues, important for proper folding and conformational stability.

  10. Development of advanced structural analysis methodologies for predicting widespread fatigue damage in aircraft structures

    Science.gov (United States)

    Harris, Charles E.; Starnes, James H., Jr.; Newman, James C., Jr.

    1995-01-01

    NASA is developing a 'tool box' that includes a number of advanced structural analysis computer codes which, taken together, represent the comprehensive fracture mechanics capability required to predict the onset of widespread fatigue damage. These structural analysis tools have complementary and specialized capabilities ranging from a finite-element-based stress-analysis code for two- and three-dimensional built-up structures with cracks to a fatigue and fracture analysis code that uses stress-intensity factors and material-property data found in 'look-up' tables or from equations. NASA is conducting critical experiments necessary to verify the predictive capabilities of the codes, and these tests represent a first step in the technology-validation and industry-acceptance processes. NASA has established cooperative programs with aircraft manufacturers to facilitate the comprehensive transfer of this technology by making these advanced structural analysis codes available to industry.

  11. RNAalifold: improved consensus structure prediction for RNA alignments

    Directory of Open Access Journals (Sweden)

    Stadler Peter F

    2008-11-01

    Full Text Available Abstract Background The prediction of a consensus structure for a set of related RNAs is an important first step for subsequent analyses. RNAalifold, which computes the minimum energy structure that is simultaneously formed by a set of aligned sequences, is one of the oldest and most widely used tools for this task. In recent years, several alternative approaches have been advocated, pointing to several shortcomings of the original RNAalifold approach. Results We show that the accuracy of RNAalifold predictions can be improved substantially by introducing a different, more rational handling of alignment gaps, and by replacing the rather simplistic model of covariance scoring with more sophisticated RIBOSUM-like scoring matrices. These improvements are achieved without compromising the computational efficiency of the algorithm. We show here that the new version of RNAalifold not only outperforms the old one, but also several other tools recently developed, on different datasets. Conclusion The new version of RNAalifold not only can replace the old one for almost any application but it is also competitive with other approaches including those based on SCFGs, maximum expected accuracy, or hierarchical nearest neighbor classifiers.

  12. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

    The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

  13. Prediction of Alzheimer's disease using individual structural connectivity networks

    Science.gov (United States)

    Shao, Junming; Myers, Nicholas; Yang, Qinli; Feng, Jing; Plant, Claudia; Böhm, Christian; Förstl, Hans; Kurz, Alexander; Zimmer, Claus; Meng, Chun; Riedl, Valentin; Wohlschläger, Afra; Sorg, Christian

    2012-01-01

    Alzheimer's disease (AD) progressively degrades the brain's gray and white matter. Changes in white matter reflect changes in the brain's structural connectivity pattern. Here, we established individual structural connectivity networks (ISCNs) to distinguish predementia and dementia AD from healthy aging in individual scans. Diffusion tractography was used to construct ISCNs with a fully automated procedure for 21 healthy control subjects (HC), 23 patients with mild cognitive impairment and conversion to AD dementia within 3 years (AD-MCI), and 17 patients with mild AD dementia. Three typical pattern classifiers were used for AD prediction. Patients with AD and AD-MCI were separated from HC with accuracies greater than 95% and 90%, respectively, irrespective of prediction approach and specific fiber properties. Most informative connections involved medial prefrontal, posterior parietal, and insular cortex. Patients with mild AD were separated from those with AD-MCI with an accuracy of approximately 85%. Our finding provides evidence that ISCNs are sensitive to the impact of earliest stages of AD. ISCNs may be useful as a white matter-based imaging biomarker to distinguish healthy aging from AD. PMID:22405045

  14. The ability of synovitis to predict structural damage in rheumatoid arthritis

    DEFF Research Database (Denmark)

    Dougados, Maxime; Devauchelle-Pensec, Valérie; Ferlet, Jean François

    2013-01-01

    To evaluate synovitis (clinical vs ultrasound (US)) to predict structural progression in rheumatoid arthritis (RA).......To evaluate synovitis (clinical vs ultrasound (US)) to predict structural progression in rheumatoid arthritis (RA)....

  15. A high density of tertiary lymphoid structure B cells in lung tumors is associated with increased CD4+ T cell receptor repertoire clonality.

    Science.gov (United States)

    Zhu, Wei; Germain, Claire; Liu, Zheng; Sebastian, Yinong; Devi, Priyanka; Knockaert, Samantha; Brohawn, Philip; Lehmann, Kim; Damotte, Diane; Validire, Pierre; Yao, Yihong; Valge-Archer, Viia; Hammond, Scott A; Dieu-Nosjean, Marie-Caroline; Higgs, Brandon W

    2015-12-01

    T and B cell receptor (TCR and BCR, respectively) Vβ or immunoglobulin heavy chain complementarity-determining region 3 sequencing allows monitoring of repertoire changes through recognition, clonal expansion, affinity maturation, and T or B cell activation in response to antigen. TCR and BCR repertoire analysis can advance understanding of antitumor immune responses in the tumor microenvironment. TCR and BCR repertoires of sorted CD4+, CD8+ or CD19+ cells in tumor, non-tumoral distant tissue (NT), and peripheral compartments (blood/draining lymph node [P]) from 47 non-small cell lung cancer (NSCLC) patients (agemedian = 68 y) were sequenced. The clonotype spectra were assessed among different tissues and correlated with clinical and immunological parameters. In all tissues, CD4+ and CD8+ TCR repertoires had greater clonality relative to CD19+ BCR. CD4+ T cells exhibited greater clonality in NT compared to tumor (p = 0.002) and P (p 68). Younger patients exhibited greater CD4+ T cell diversity in P compared to older patients (p = 0.05), and greater CD4+ T cell clonality in tumor relative to P (p cell clonality in tumor and P, respectively (both p = 0.05), correlated with high density of tumor-associated tertiary lymphoid structure (TLS) B cells, a biomarker of higher overall survival in NSCLC. Results indicate distinct adaptive immune responses in NSCLC, where peripheral T cell diversity is modulated by age, and tumor T cell clonal expansion is favored by the presence of TLSs in the tumor microenvironment.

  16. Prediction of Chloride Diffusion in Concrete Structure Using Meshless Methods

    Directory of Open Access Journals (Sweden)

    Ling Yao

    2016-01-01

    Full Text Available Degradation of RC structures due to chloride penetration followed by reinforcement corrosion is a serious problem in civil engineering. The numerical simulation methods at present mainly involve finite element methods (FEM, which are based on mesh generation. In this study, element-free Galerkin (EFG and meshless weighted least squares (MWLS methods are used to solve the problem of simulation of chloride diffusion in concrete. The range of a scaling parameter is presented using numerical examples based on meshless methods. One- and two-dimensional numerical examples validated the effectiveness and accuracy of the two meshless methods by comparing results obtained by MWLS with results computed by EFG and FEM and results calculated by an analytical method. A good agreement is obtained among MWLS and EFG numerical simulations and the experimental data obtained from an existing marine concrete structure. These results indicate that MWLS and EFG are reliable meshless methods that can be used for the prediction of chloride ingress in concrete structures.

  17. The extended evolutionary synthesis: its structure, assumptions and predictions.

    Science.gov (United States)

    Laland, Kevin N; Uller, Tobias; Feldman, Marcus W; Sterelny, Kim; Müller, Gerd B; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

    2015-08-22

    Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the 'extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism-environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. © 2015 The Author(s).

  18. The extended evolutionary synthesis: its structure, assumptions and predictions

    Science.gov (United States)

    Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

    2015-01-01

    Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559

  19. Synoptic Factors Affecting Structure Predictability of Hurricane Alex (2016)

    Science.gov (United States)

    Gonzalez-Aleman, J. J.; Evans, J. L.; Kowaleski, A. M.

    2016-12-01

    On January 7, 2016, a disturbance formed over the western North Atlantic basin. After undergoing tropical transition, the system became the first hurricane of 2016 - and the first North Atlantic hurricane to form in January since 1938. Already an extremely rare hurricane event, Alex then underwent extratropical transition [ET] just north of the Azores Islands. We examine the factors affecting Alex's structural evolution through a new technique called path-clustering. In this way, 51 ensembles from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF-EPS) are grouped based on similarities in the storm's path through the Cyclone Phase Space (CPS). The differing clusters group various possible scenarios of structural development represented in the ensemble forecasts. As a result, it is possible to shed light on the role of the synoptic scale in changing the structure of this hurricane in the midlatitudes through intercomparison of the most "realistic" forecast of the evolution of Alex and the other physically plausible modes of its development.

  20. SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

    Directory of Open Access Journals (Sweden)

    Chen Ke

    2008-05-01

    Full Text Available Abstract Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is

  1. Tertiary oil recovery: potential application and constraints

    Energy Technology Data Exchange (ETDEWEB)

    Geffen, C. A.

    1978-06-01

    The technology of tertiary oil recovery methods is described and potential economic and environmental constraints to future commercial application are identified. Oil recoverable by tertiary techniques represents a domestic resource of between 11- and 42-billion barrels. Estimates of additional oil supplies from tertiary methods by the year 2000 range from 1 to 8 million barrels per day, depending on the price of oil and the rate of technological development. The principal constraints to large-scale application of tertiary methods at the present time include environmental, economic and technological concerns. Regulatory action associated with the Clean Air Act Amendments of 1977 currently delay the expansion of thermal recovery operations in California and may discourage future projects. The high production costs of tertiary projects also hamper process implementation. Further testing and research is necessary to develop the technology of tertiary recovery methods and prove these techniques successful on a field-wide scale. To enable tertiary oil recovery to play a significant role in augmenting domestic energy supplies, further research and development is necessary. More accurate methods of determining reservoir structure and residual oil saturations are required, as well as means for assuring the technical feasibility and success of a tertiary method in different reservoir types. Technical process limitations must also be resolved. The severity of potential environmental impacts and constraints identified in this report should be determined. These concerns include the air pollutant emissions from steam generation in thermal processes; acceptable methods of brine disposal; damage due to runoff or accidental discharge of oil-rich chemicals into surface waters; the impacts of fluid injection on deep aquifers and the prevailing geological structure; and an adequate supply of high quality fresh water.

  2. Secondary and tertiary hyperparathyroidism.

    Science.gov (United States)

    Jamal, Sophie A; Miller, Paul D

    2013-01-01

    We reviewed the etiology and management of secondary and tertiary hyperparathyroidism. Secondary hyperparathyroidism is characterized by an increase in parathyroid hormone (PTH) that is appropriate and in response to a stimulus, most commonly low serum calcium. In secondary hyperparathyroidism, the serum calcium is normal and the PTH level is elevated. Tertiary hyperparathyroidism is characterized by excessive secretion of PTH after longstanding secondary hyperparathyroidism, in which hypercalcemia has ensued. Tertiary hyperparathyroidism typically occurs in men and women with chronic kidney disease usually after kidney transplant. The etiology and treatment of secondary hyperparathyroidism is relatively straightforward whereas data on the management of tertiary hyperparathyroidism is limited to a few small trials with short follow-up. Copyright © 2013 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

  3. PREDICTED STRUCTURE AND BINDING MOTIFS OF COLLAGEN α1(XI).

    Science.gov (United States)

    McDougal, Owen M; Warner, Lisa R; Mallory, Chris; Oxford, Julia Thom

    2011-12-01

    The amino propeptide of collagen α1(XI) (NPP) has been shown to bind glycosaminoglycans and to form a dimer. While these are independent biochemical events, it is likely that dimerization facilitates the interaction with glycosaminoglycans or alternatively, that glycosaminoglycan interaction facilitates the formation of an NPP:NPP dimer. The computer program MODELLER was used to generate a homology model of the collagen α1(XI) NPP monomer using the crystal structure of the closely related noncollagenous-4 (NC4) domain of collagen α1(IX) (PDB:2UUR) as the template. Additionally, a dimer model of collagen α1(XI) NPP domain was created based upon the thrombospondin dimer template (PDB:1Z78). The structure of the dimer created in MODELLER was validated by comparison to a dimer model generated by docking two monomers of PDB:2UUR using ClusPro. Calculations of relative binding energy for the interaction between each collagen α1(XI) NPP model and glycosaminoglycans as ligands was performed using AutoDock4. Computational results support a higher affinity between heparan sulfate and a dimer compared to a monomer. These findings are supported by affinity chromatography experiments in which distinct monomer and dimer peaks were observed. Sequential point mutation studies of the putative binding site (147-KKKITK-152) indicated the importance of the basic lysine residue for binding to heparan sulfate. Two orders of magnitude change in binding affinity was predicted when comparing wild type to the mutation K152A. Experimental data supports the predicted change in affinity.

  4. Evaluation of the Special Tertiary Admissions Test (STAT)

    Science.gov (United States)

    Coates, Hamish; Friedman, Tim

    2010-01-01

    This paper reports findings from the first national Australian study of the predictive validity of the Special Tertiary Admissions Test (STAT). Background on tertiary admissions procedures in Australia is presented, followed by information on STAT and the research methods. The results affirm that STAT, through the provision of baseline and…

  5. Occupational Structure in European Countries: What do Forecasts Predict?

    Directory of Open Access Journals (Sweden)

    Nina Vishnevskaya

    2017-12-01

    Full Text Available This paper analyzes the future occupational structure of the labour force in European members of the Organisation for Co-operation and Development (OECD. Occupational structure forecasts allow researchers to evaluate the quality of job openings and, consequently, overall future labour market performance. Identification of demand for certain occupations in Europe can facilitate assessment of whether processes occurring in the Russian labour market are consistent with global trends. The paper discusses the methodology of labour force forecasting and basic research approaches to the prediction of occupational structure changes. It emphasizes the dynamics of demand for representatives of certain occupations in Europe by identifying the fastest growing and declining occupations and suggests possible reasons for changing demand. The paper demonstrates that the main occupational trend over the next decade will consist in the increasing importance of professionals, as well as technicians and associate professionals. The increase in demand for health professionals and representatives of occupations providing scientific and technological innovation will be most significant. At the same time, it is expected that demand for elementary occupations will also rise. This process will evolve simultaneously with the decrease in the total number of skilled and semi-skilled blue-collar occupations due to globalization and the reduction of industrial production in developed economies. The ongoing “mechanization” of many job functions will not eliminate the need for occupations such as cleaners, labourers, domestic servants or personal workers. The need for these jobs allow employees with low levels of education to enter the labour market rather than depending on the social benefit system. Another tendency for all countries with developed economies will be reduced demand for many whitecollar occupations as modern computer technologies and the automation of many

  6. EFSA CEF Panel (EFSA Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids) , 2016. Scientific Opinion on Flavouring Group Evaluation 90, Revision 1 (FGE.90Rev1): consideration of six substances evaluated by JECFA (68th meeting) structurally related to aliphatic, alicyclic and aromatic saturated and unsaturated tertiary alcohols, aromatic tertiary alcohols and their esters evaluated by EFSA in FGE.18Rev1 and FGE.75Rev1

    DEFF Research Database (Denmark)

    Beltoft, Vibe Meister; Nørby, Karin Kristiane

    , as laid down in Commission Regulation (EC) No 1565/2000. The present consideration concerns a group of six aliphatic, acyclic and alicyclic terpenoid tertiary alcohols and structurally related substances evaluated by JECFA at the 68th meeting in 2007. This revision of FGE.90 is made because additional...

  7. An evolutionary method for learning HMM structure: prediction of protein secondary structure

    DEFF Research Database (Denmark)

    Won, Kyoung-Jae; Hamelryck, Thomas; Prügel-Bennett, Adam

    2007-01-01

    of such Block-HMMs. After each step of the GA, the standard HMM estimation algorithm (the Baum-Welch algorithm) was used to update model parameters. The final HMM captures several features of protein sequence and structure, with its own HMM grammar. In contrast to neural network based predictors, the evolved...... HMM also calculates the probabilities associated with the predictions. We carefully examined the performance of the HMM based predictor, both under the multiple- and single-sequence...

  8. Sequence and structure prediction of RNA-dependent RNA polymerase of lily symptomless virus isolated from L. × 'Casablanca'.

    Science.gov (United States)

    Xu, Pinsan; Li, Huangai; Liu, Jiwen; Luan, Yushi; Yin, Yalei; Bai, Jianfang

    2011-06-01

    The DNA sequence of the RNA-dependent RNA polymerase (RdRp) gene of lily symptomless virus (LSV), a lily-infecting member of the genus Carlavirus, was determined from nine overlapping cDNA fragments of different sizes. The complete sequence of this RdRp gene (HM070294) consisted of 5,847 nucleotides coding for a protein of 220 kDa. It had 97-98% sequence identity with RdRps of other known isolates at both the DNA and the amino acid level. Phylogenetic analysis indicated that this RdRp (designated as RdRp-DL) was closely related to the RdRp of the Korean isolate (AM516059), as well as to the RdRps from Passiflora latent virus (PLV) and Kalanchoe latent virus (KLV) of the genus Carlavirus. Hydrophobic analysis of RdRp-DL revealed a hydrophobic N-terminus and a hydrophilic C-terminus. Helices and Loops were the major secondary structures of RdRp-DL. In addition, RdRp-DL also had three coil structures. Four conserved domains were identified: typoviral methyltransferase, RNA-dependent RNA polymerase, P-loop-containing nucleoside triphosphate hydrolases and carlavirus endopeptidase. A model of the tertiary structure predicted by I-TASSER was obtained for each of these conserved domains. This is the first report of a detailed phylogenetic analysis of LSV RdRp with those of other members of the genus Carlavirus, and the first to predict the domain structures of LSV RdRp.

  9. Towards Fully Automated Structure-Based Function Prediction In Structural Genomics: A Case Study

    Science.gov (United States)

    Watson, James D.; Sanderson, Steve; Ezersky, Alexandra; Savchenko, Alexei; Edwards, Aled; Orengo, Christine; Joachimiak, Andrzej; Laskowski, Roman A.; Thornton, Janet M.

    2007-01-01

    Summary As the global Structural Genomics projects have picked up pace the number of structures annotated in the Protein Data Bank as “hypothetical protein” or “unknown function” has grown significantly. A major challenge now involves the development of computational methods to accurately and automatically assign functions to these proteins. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI) we review the success of the pipeline and the importance of structure-based function prediction. As a dataset we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity difficult to identify using current sequence methods. No one method is successful in all cases so through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chance that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment. PMID:17316683

  10. A cost driven predictive maintenance policy for structural airframe maintenance

    Directory of Open Access Journals (Sweden)

    Yiwei WANG

    2017-06-01

    Full Text Available Airframe maintenance is traditionally performed at scheduled maintenance stops. The decision to repair a fuselage panel is based on a fixed crack size threshold, which allows to ensure the aircraft safety until the next scheduled maintenance stop. With progress in sensor technology and data processing techniques, structural health monitoring (SHM systems are increasingly being considered in the aviation industry. SHM systems track the aircraft health state continuously, leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule. This paper builds upon a model-based prognostics framework that the authors developed in their previous work, which couples the Extended Kalman filter (EKF with a first-order perturbation (FOP method. By using the information given by this prognostics method, a novel cost driven predictive maintenance (CDPM policy is proposed, which ensures the aircraft safety while minimizing the maintenance cost. The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance. A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented. Under the condition of assuring the same safety level, the CDPM is compared in terms of cost with two other maintenance policies: scheduled maintenance and threshold based SHM maintenance. The comparison results show CDPM could lead to significant cost savings.

  11. STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION

    Energy Technology Data Exchange (ETDEWEB)

    CHRISTOPHER M. HADAD; JOSEPH M. CALO; ROBERT H. ESSENHIGH; ROBERT H. HURT

    1998-06-04

    During the past quarter of this project, significant progress continued was made on both major technical tasks. Progress was made at OSU on advancing the application of computational chemistry to oxidative attack on model polyaromatic hydrocarbons (PAHs) and graphitic structures. This work is directed at the application of quantitative ab initio molecular orbital theory to address the decomposition products and mechanisms of coal char reactivity. Previously, it was shown that the �hybrid� B3LYP method can be used to provide quantitative information concerning the stability of the corresponding radicals that arise by hydrogen atom abstraction from monocyclic aromatic rings. In the most recent quarter, these approaches have been extended to larger carbocyclic ring systems, such as coronene, in order to compare the properties of a large carbonaceous PAH to that of the smaller, monocyclic aromatic systems. It was concluded that, at least for bond dissociation energy considerations, the properties of the large PAHs can be modeled reasonably well by smaller systems. In addition to the preceding work, investigations were initiated on the interaction of selected radicals in the �radical pool� with the different types of aromatic structures. In particular, the different pathways for addition vs. abstraction to benzene and furan by H and OH radicals were examined. Thus far, the addition channel appears to be significantly favored over abstraction on both kinetic and thermochemical grounds. Experimental work at Brown University in support of the development of predictive structural models of coal char combustion was focused on elucidating the role of coal mineral matter impurities on reactivity. An �inverse� approach was used where a carbon material was doped with coal mineral matter. The carbon material was derived from a high carbon content fly ash (Fly Ash 23 from the Salem Basin Power Plant. The ash was obtained from Pittsburgh #8 coal (PSOC 1451). Doped

  12. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

    Directory of Open Access Journals (Sweden)

    Kurgan Lukasz

    2008-10-01

    Full Text Available Abstract Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM values serve as an input to the support vector machine (SVM predictor. Results We show that (1 all four predicted secondary structures are useful; (2 the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3 the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an

  13. Design and synthesis of potent HIV-1 protease inhibitors with (S)-tetrahydrofuran-tertiary amine-acetamide as P2-ligand: Structure-activity studies and biological evaluation.

    Science.gov (United States)

    Bai, Xiaoguang; Yang, Zhiheng; Zhu, Mei; Dong, Biao; Zhou, Lei; Zhang, Guoning; Wang, Juxian; Wang, Yucheng

    2017-09-08

    The design, synthesis, and SAR study of a new series of HIV-1 protease inhibitors incorporating stereochemically defined tetrahydrofuran-tertiary amine-acetamide P2-ligand are described. Various substituent effects on the tertiary amine P2-ligand and phenylsulfonamide P2'-ligand were investigated to maximize the ligand-binding site interactions in the protease active site. Most of inhibitors displayed low nanomolar to subnanomolar inhibitory potency. Inhibitor 20e containing N-(S-tetrahydrofuran)-N-(2-methoxyethyl)acetamide as P2-ligand along with 4-methoxylphenylsulfonamide as P2'-ligand displayed the most potent enzyme inhibitory activity (IC50 = 0.35 nM) and remarkably low cytotoxicity (CC50 = 305 μM). Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  14. First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Ceder, Gerbrand [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials and Engineering

    2018-01-28

    Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

  15. Update on protein structure prediction: results of the 1995 IRBM workshop

    DEFF Research Database (Denmark)

    Hubbard, Tim; Tramontano, Anna; Hansen, Jan

    1996-01-01

    Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a numbe...

  16. RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

    Science.gov (United States)

    Ellington, Roni; Wachira, James; Nkwanta, Asamoah

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

  17. Improving search for low energy protein structures with an iterative niche genetic algorithm

    DEFF Research Database (Denmark)

    Helles, Glennie

    2010-01-01

    In attempts to predict the tertiary structure of proteins we use almost exclusively metaheuristics. However, despite known differences in performance of metaheuristics for different problems, the effect of the choice of metaheuristic has received precious little attention in this field...

  18. Predicting Successful Memes using Network and Community Structure

    OpenAIRE

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2014-01-01

    We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of...

  19. Individual brain structure and modelling predict seizure propagation.

    Science.gov (United States)

    Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

    2017-03-01

    See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

  20. Predicting aphasia type from brain damage measured with structural MRI.

    Science.gov (United States)

    Yourganov, Grigori; Smith, Kimberly G; Fridriksson, Julius; Rorden, Chris

    2015-12-01

    Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca's, Wernicke's, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery (WAB). Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients' aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine - SVM) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. PREDICTING APHASIA TYPE FROM BRAIN DAMAGE MEASURED WITH STRUCTURAL MRI

    Science.gov (United States)

    Yourganov, Grigori; Smith, Kimberly G.; Fridriksson, Julius; Rorden, Chris

    2015-01-01

    Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca’s, Wernicke’s, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery. Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients’ aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. PMID:26465238

  2. 2. Tertiary Foraminifera

    NARCIS (Netherlands)

    Umbgrove, J.H.F.

    1931-01-01

    In his review of the palaeozoology of Java, K. Martin could in 1919, record 49 foraminifera from tertiary strata of Java, on the strength of a critical study of the existant literature, and especially on the strength of his own studies and knowledge of the above mentioned fossils (Bibl. 49). In

  3. Structural synthetic biotechnology: from molecular structure to predictable design for industrial strain development.

    Science.gov (United States)

    Chen, Zhen; Wilmanns, Matthias; Zeng, An-Ping

    2010-10-01

    The future of industrial biotechnology requires efficient development of highly productive and robust strains of microorganisms. Present praxis of strain development cannot adequately fulfill this requirement, primarily owing to the inability to control reactions precisely at a molecular level, or to predict reliably the behavior of cells upon perturbation. Recent developments in two areas of biology are changing the situation rapidly: structural biology has revealed details about enzymes and associated bioreactions at an atomic level; and synthetic biology has provided tools to design and assemble precisely controllable modules for re-programming cellular metabolic circuitry. However, because of different emphases, to date, these two areas have developed separately. A linkage between them is desirable to harness their concerted potential. We therefore propose structural synthetic biotechnology as a new field in biotechnology, specifically for application to the development of industrial microbial strains. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. The Ability of the Acute Physiology and Chronic Health Evaluation (APACHE IV Score to Predict Mortality in a Single Tertiary Hospital

    Directory of Open Access Journals (Sweden)

    Jae Woo Choi

    2017-08-01

    Full Text Available Background The Acute Physiology and Chronic Health Evaluation (APACHE II model has been widely used in Korea. However, there have been few studies on the APACHE IV model in Korean intensive care units (ICUs. The aim of this study was to compare the ability of APACHE IV and APACHE II in predicting hospital mortality, and to investigate the ability of APACHE IV as a critical care triage criterion. Methods The study was designed as a prospective cohort study. Measurements of discrimination and calibration were performed using the area under the receiver operating characteristic curve (AUROC and the Hosmer-Lemeshow goodness-of-fit test respectively. We also calculated the standardized mortality ratio (SMR. Results The APACHE IV score, the Charlson Comorbidity index (CCI score, acute respiratory distress syndrome, and unplanned ICU admissions were independently associated with hospital mortality. The calibration, discrimination, and SMR of APACHE IV were good (H = 7.67, P = 0.465; C = 3.42, P = 0.905; AUROC = 0.759; SMR = 1.00. However, the explanatory power of an APACHE IV score >93 alone on hospital mortality was low at 44.1%. The explanatory power was increased to 53.8% when the hospital mortality was predicted using a model that considers APACHE IV >93 scores, medical admission, and risk factors for CCI >3 coincidentally. However, the discriminative ability of the prediction model was unsatisfactory (C index <0.70. Conclusions The APACHE IV presented good discrimination, calibration, and SMR for hospital mortality.

  5. Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

    Directory of Open Access Journals (Sweden)

    Vullo Alessandro

    2007-06-01

    Full Text Available Abstract Background Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and solvent accessibilities are extracted directly from the templates. We show that structural information from templates greatly improves secondary structure and solvent accessibility prediction quality, and that, on average, the systems significantly enrich the information contained in the templates. For sequence similarity exceeding 30%, secondary structure prediction quality is approximately 90%, close to its theoretical maximum, and 2-class solvent accessibility roughly 85%. Gains are robust with respect to template selection noise, and significant for marginal sequence similarity and for short alignments, supporting the claim that these improved predictions may prove beneficial beyond the case in which clear homology is available. Conclusion The predictive system are publicly available at the address http://distill.ucd.ie.

  6. Smart Utilization of Tertiary Instructional Modes

    Science.gov (United States)

    Hamilton, John; Tee, Singwhat

    2010-01-01

    This empirical research surveys first year tertiary business students across different campuses regarding their perceived views concerning traditional, blended and flexible instructional approaches. A structural equation modeling approach shows traditional instructional modes deliver lower levels of student-perceived learning quality, learning…

  7. Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

    Science.gov (United States)

    Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

    2017-10-12

    Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

  8. Prediction of difficult intubations using conventional indicators; Does rapid sequence intubation ease difficult intubations? A prospective randomised study in a tertiary care teaching hospital

    Directory of Open Access Journals (Sweden)

    Gangadharan Lakshmi

    2011-01-01

    Full Text Available Background : Endotracheal intubations performed in the Emergency Department. Aims : To assess whether conventional indicators of difficult airway can predict a difficult intubation in the Emergency Setting and to investigate the effect of rapid sequence intubation (RSI on ease of intubation. Settings and Design : A prospective randomized study was designed involving 60 patients requiring intubation, over a period of 4 months. Materials and Methods : Demographic profile, details of methods used, airway assessment, ease of intubation, and Cormack and Lehane score were recorded. Airway assessment score and ease of intubation criteria were devised and assessed. Statistical Analysis : Descriptive statistical analysis was carried out. Chi-square/2 × 2, 2 × 3, 3 × 3, Fisher Exact test have been used to find the significance of study parameters on categorical scale between two or more groups. Results : Patients with a Mallampatti score of three or four were found to have worse laryngoscopic views (Cormack-Lehane score, 3 or 4. Of all airway indicators assessed, an increased Mallampatti score was found to have significant correlation with increased difficulty in intubation. The use of RSI was associated with better laryngoscopic views, and easier intubations. Conclusions : An airway assessment using the Mallampatti score is invaluable as a tool to predict a difficult airway and should be performed routinely if possible. RSI aids intubation ease. If not otherwise contraindicated, it should be performed routinely for all intubations in the ED.

  9. Structure-based de novo prediction of zinc-binding sites in proteins of unknown function.

    Science.gov (United States)

    Zhao, Wei; Xu, Meng; Liang, Zhi; Ding, Bo; Niu, Liwen; Liu, Haiyan; Teng, Maikun

    2011-05-01

    Zinc-binding proteins are the most abundant metallo-proteins in Protein Data Bank (PDB). Accurate prediction of zinc-binding sites in proteins of unknown function may provide important clues for the inference of protein function. As zinc binding is often associated with characteristic 3D arrangements of zinc ligand residues, its prediction may benefit from using not only the sequence information but also the structure information of proteins. In this work, we present a structure-based method, TEMSP (3D TEmplate-based Metal Site Prediction), to predict zinc-binding sites. TEMSP significantly improves over previously reported best methods in predicting as many as possible true ligand residues for zinc with minimum overpredictions: if only those results in which all zinc ligand residues have been correctly predicted are defined as true positives, our method improves sensitivity from less than 30% to above 60%, and selectivity from around 25% to 80%. These results are for predictions based on apo state structures. In addition, the method can predict the zinc-bound local structures reliably, generating predictions useful for function inference. We applied TEMSP to 1888 protein structures of the 'Unknown Function' class in the PDB database. A number of zinc-binding sites have been discovered de novo, i.e. based solely on the protein structures. Using the predicted local structures of these sites, possible functional roles were analyzed. TEMSP is freely available from http://netalign.ustc.edu.cn/temsp/.

  10. Improving 3D structure prediction from chemical shift data

    NARCIS (Netherlands)

    van der Schot, G.; Zhang, Z.; Vernon, R.; Shen, Y.; Vranken, W.F.; Baker, D.; Bonvin, A.M.J.J.|info:eu-repo/dai/nl/113691238; Lange, O.F.

    2013-01-01

    We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CSRosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts

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

    DEFF Research Database (Denmark)

    Blom, Nikolaj; Gammeltoft, Steen; Brunak, Søren

    1999-01-01

    Protein phosphorylation at serine, threonine or tyrosine residues affects a multitude of cellular signaling processes. Howis specificity in substrate recognition and phosphorylation by protein kinases achieved? Here, we present an artificialneural network method that predicts phosphorylation site...

  12. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  13. Visibility of natural tertiary rainbows.

    Science.gov (United States)

    Lee, Raymond L; Laven, Philip

    2011-10-01

    Naturally occurring tertiary rainbows are extraordinarily rare and only a handful of reliable sightings and photographs have been published. Indeed, tertiaries are sometimes assumed to be inherently invisible because of sun glare and strong forward scattering by raindrops. To analyze the natural tertiary's visibility, we use Lorenz-Mie theory, the Debye series, and a modified geometrical optics model (including both interference and nonspherical drops) to calculate the tertiary's (1) chromaticity gamuts, (2) luminance contrasts, and (3) color contrasts as seen against dark cloud backgrounds. Results from each model show that natural tertiaries are just visible for some unusual combinations of lighting conditions and raindrop size distributions.

  14. A scoring function based on solvation thermodynamics for protein structure prediction.

    Science.gov (United States)

    Du, Shiqiao; Harano, Yuichi; Kinoshita, Masahiro; Sakurai, Minoru

    2012-01-01

    We predict protein structure using our recently developed free energy function for describing protein stability, which is focused on solvation thermodynamics. The function is combined with the current most reliable sampling methods, i.e., fragment assembly (FA) and comparative modeling (CM). The prediction is tested using 11 small proteins for which high-resolution crystal structures are available. For 8 of these proteins, sequence similarities are found in the database, and the prediction is performed with CM. Fairly accurate models with average Cα root mean square deviation (RMSD) ∼ 2.0 Å are successfully obtained for all cases. For the rest of the target proteins, we perform the prediction following FA protocols. For 2 cases, we obtain predicted models with an RMSD ∼ 3.0 Å as the best-scored structures. For the other case, the RMSD remains larger than 7 Å. For all the 11 target proteins, our scoring function identifies the experimentally determined native structure as the best structure. Starting from the predicted structure, replica exchange molecular dynamics is performed to further refine the structures. However, we are unable to improve its RMSD toward the experimental structure. The exhaustive sampling by coarse-grained normal mode analysis around the native structures reveals that our function has a linear correlation with RMSDs function is quite reliable for the protein structure prediction while the sampling method remains one of the major limiting factors in it. The aspects through which the methodology could further be improved are discussed.

  15. Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets.

    Science.gov (United States)

    Zhao, Huiying; Yang, Yuedong; Zhou, Yaoqi

    2011-04-01

    Mechanistic understanding of many key cellular processes often involves identification of RNA binding proteins (RBPs) and RNA binding sites in two separate steps. Here, they are predicted simultaneously by structural alignment to known protein-RNA complex structures followed by binding assessment with a DFIRE-based statistical energy function. This method achieves 98% accuracy and 91% precision for predicting RBPs and 93% accuracy and 78% precision for predicting RNA-binding amino-acid residues for a large benchmark of 212 RNA binding and 6761 non-RNA binding domains (leave-one-out cross-validation). Additional tests revealed that the method makes no false positive prediction from 311 DNA binding domains but correctly detects six domains binding with both DNA and RNA. In addition, it correctly identified 31 of 75 unbound RNA-binding domains with 92% accuracy and 65% precision for predicted binding residues and achieved 86% success rate in its application to SCOP RNA binding domain superfamily (Structural Classification Of Proteins). It further predicts 25 targets as RBPs in 2076 structural genomics targets: 20 of 25 predicted ones (80%) are putatively RNA binding. The superior performance over existing methods indicates the importance of dividing structures into domains, using a Z-score to measure relative structural similarity, and a statistical energy function to measure protein-RNA binding affinity.

  16. Structural health monitoring for fatigue life prediction of orthotropic brdige decks

    NARCIS (Netherlands)

    Pijpers, R.J.M.; Pahlavan, P.L.; Paulissen, J.H.; Hakkesteegt, H.C.; Jansen, T.H.

    2013-01-01

    Infrastructure asset owners are more and more confronted with structures reaching the end of their structural life. Structural Health Monitoring (SHM) systems should provide up-to-date information about the actual condition, as well predict the structural life and required maintenance of the assets

  17. Perspective: Role of structure prediction in materials discovery and design

    Directory of Open Access Journals (Sweden)

    Richard J. Needs

    2016-05-01

    Full Text Available Materials informatics owes much to bioinformatics and the Materials Genome Initiative has been inspired by the Human Genome Project. But there is more to bioinformatics than genomes, and the same is true for materials informatics. Here we describe the rapidly expanding role of searching for structures of materials using first-principles electronic-structure methods. Structure searching has played an important part in unraveling structures of dense hydrogen and in identifying the record-high-temperature superconducting component in hydrogen sulfide at high pressures. We suggest that first-principles structure searching has already demonstrated its ability to determine structures of a wide range of materials and that it will play a central and increasing part in materials discovery and design.

  18. Perspective: Role of structure prediction in materials discovery and design

    Science.gov (United States)

    Needs, Richard J.; Pickard, Chris J.

    2016-05-01

    Materials informatics owes much to bioinformatics and the Materials Genome Initiative has been inspired by the Human Genome Project. But there is more to bioinformatics than genomes, and the same is true for materials informatics. Here we describe the rapidly expanding role of searching for structures of materials using first-principles electronic-structure methods. Structure searching has played an important part in unraveling structures of dense hydrogen and in identifying the record-high-temperature superconducting component in hydrogen sulfide at high pressures. We suggest that first-principles structure searching has already demonstrated its ability to determine structures of a wide range of materials and that it will play a central and increasing part in materials discovery and design.

  19. [Mortality in patients with potentially severe trauma in a tertiary care hospital emergency department and evaluation of risk prediction with the GAP prognostic scale].

    Science.gov (United States)

    Martín Quirós, Alejandro; Borobia Pérez, Alberto; Pertejo Fernández, Ana; Pérez Perilla, Patricia; Rivera Núñez, Angélica; Martínez Virto, Ana María; Quintana Díaz, Manuel

    2015-01-01

    To assess mortality in patients with potentially severe injuries and explore the correlation between mortality and the score on the GAP scale (Glasgow Coma Scale, age, and systolic blood pressure). Retrospective observational study of all patients with potentially severe injuries treated in an emergency department (ED) over a period of 15 months. We recorded epidemiologic variables, cause of injury, type of transport, need for prehospital orotracheal intubation, substance abuse, Charlson Comorbidity Index (CCI), variables for the GAP prognostic score, destination on discharge from the ED and at the end of the episode, and mortality. Data for 864 patients entered the final analysis. Mortality was higher in older patients (mean [SD] age, 57.9 [26.6] vs 41.1 [17.4], P<.05) and those with a higher mean CCI (3.3 [2.9] vs 0.9 [1.7]). Accident type was a precipitating factor associated with mortality (P<.001), but substance abuse was unrelated. Patients who died had lower mean Glasgow scores (9.1 [5.3] vs 14.8 [1.2], P<.001) and lower mean systolic and diastolic pressures (respectively, 113.8 [19.8] vs 131.3 [20.7] mm Hg, P=.012, and 60.1 [16.8] vs 77.7 [11.7] mm Hg, P=.002). Patients who died also had lower mean GAP scores than survivors (15.1 [4.8] vs 22.6 [1.7], P<.001). Risk factors that remained significant in the multivariate analysis were CCI (odds ratio [OR], 0.704; 95% CI, 0.52-0.96) and GAP score (OR, 1.8; 95% CI, 1.45-2.20). Mortality in our patient series was lower than rates in previously published reports. The GAP score was a useful tool for predicting mortality in the series we studied.

  20. Predictive Modeling of Complex Contoured Composite Structures Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The existing HDWLT (pictured) contoured composite structure design, its analyses and manufacturing tools, will be used to validate key analyses inputs through...

  1. Improved fuzzy PID controller design using predictive functional control structure.

    Science.gov (United States)

    Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

    2017-11-01

    In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Automated 3D RNA structure prediction using the RNAComposer method for riboswitches.

    Science.gov (United States)

    Purzycka, K J; Popenda, M; Szachniuk, M; Antczak, M; Lukasiak, P; Blazewicz, J; Adamiak, R W

    2015-01-01

    Understanding the numerous functions of RNAs depends critically on the knowledge of their three-dimensional (3D) structure. In contrast to the protein field, a much smaller number of RNA 3D structures have been assessed using X-ray crystallography, NMR spectroscopy, and cryomicroscopy. This has led to a great demand to obtain the RNA 3D structures using prediction methods. The 3D structure prediction, especially of large RNAs, still remains a significant challenge and there is still a great demand for high-resolution structure prediction methods. In this chapter, we describe RNAComposer, a method and server for the automated prediction of RNA 3D structures based on the knowledge of secondary structure. Its applications are supported by other automated servers: RNA FRABASE and RNApdbee, developed to search and analyze secondary and 3D structures. Another method, RNAlyzer, offers new way to analyze and visualize quality of RNA 3D models. Scope and limitations of RNAComposer in application for an automated prediction of riboswitches' 3D structure will be presented and discussed. Analysis of the cyclic di-GMP-II riboswitch from Clostridium acetobutylicum (PDB ID 3Q3Z) as an example allows for 3D structure prediction of related riboswitches from Clostridium difficile 4, Bacillus halodurans 1, and Thermus aquaticus Y5.1 of yet unknown structures. © 2015 Elsevier Inc. All rights reserved.

  3. Vfold: a web server for RNA structure and folding thermodynamics prediction.

    Science.gov (United States)

    Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

    2014-01-01

    The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

  4. Predicting emotional exhaustion among haemodialysis nurses: a structural equation model using Kanter's structural empowerment theory.

    Science.gov (United States)

    Hayes, Bronwyn; Douglas, Clint; Bonner, Ann

    2014-12-01

    To test an explanatory model of the relationships between the nursing work environment, job satisfaction, job stress and emotional exhaustion for haemodialysis nurses, drawing on Kanter's theory of organizational empowerment. Understanding the organizational predictors of burnout (emotional exhaustion) in haemodialysis nurses is critical for staff retention and improving nurse and patient outcomes. Previous research has demonstrated high levels of emotional exhaustion among haemodialysis nurses, yet the relationships between nurses' work environment, job satisfaction, stress and emotional exhaustion in this population are poorly understood. A cross-sectional online survey. 417 nurses working in haemodialysis units completed an online survey between October 2011-April 2012 using validated measures of the work environment, job satisfaction, job stress and emotional exhaustion. Overall, the structural equation model demonstrated adequate fit and we found partial support for the hypothesized relationships. Nurses' work environment had a direct positive effect on job satisfaction, explaining 88% of the variance. Greater job satisfaction, in turn, predicted lower job stress, explaining 82% of the variance. Job satisfaction also had an indirect effect on emotional exhaustion by mitigating job stress. However, job satisfaction did not have a direct effect on emotional exhaustion. The work environment of haemodialysis nurses is pivotal to the development of job satisfaction. Nurses' job satisfaction also predicts their level of job stress and emotional exhaustion. Our findings suggest staff retention can be improved by creating empowering work environments that promote job satisfaction among haemodialysis nurses. © 2014 John Wiley & Sons Ltd.

  5. Using Structural Equation Modelling (SEM) to predict use of ...

    African Journals Online (AJOL)

    subsequently the use of VCT services are generally lacking. We employed Structural Equation Modelling (SEM) ... Voluntary counselling and testing (VCT), Structural equation modelling (SEM), AMOS program Introduction ..... similar to those reported in hospital or satellite. (stand-alone) VCT centres, we feel that our findings.

  6. Protein structure prediction using bee colony optimization metaheuristic

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel

    2010-01-01

    of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy. Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested...

  7. Finite Element Based HWB Centerbody Structural Optimization and Weight Prediction

    Science.gov (United States)

    Gern, Frank H.

    2012-01-01

    This paper describes a scalable structural model suitable for Hybrid Wing Body (HWB) centerbody analysis and optimization. The geometry of the centerbody and primary wing structure is based on a Vehicle Sketch Pad (VSP) surface model of the aircraft and a FLOPS compatible parameterization of the centerbody. Structural analysis, optimization, and weight calculation are based on a Nastran finite element model of the primary HWB structural components, featuring centerbody, mid section, and outboard wing. Different centerbody designs like single bay or multi-bay options are analyzed and weight calculations are compared to current FLOPS results. For proper structural sizing and weight estimation, internal pressure and maneuver flight loads are applied. Results are presented for aerodynamic loads, deformations, and centerbody weight.

  8. RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

    Science.gov (United States)

    Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

    2015-01-01

    This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

  9. RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.

    Science.gov (United States)

    Miao, Zhichao; Adamiak, Ryszard W; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

    2015-06-01

    This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. © 2015 Miao et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  10. Crystal structure prediction and its application in Earth and materials sciences.

    Science.gov (United States)

    Zhu, Qiang; Oganov, Artem R; Zhou, Xiang-Feng

    2014-01-01

    Evolutionary algorithms, based on physically motivated forms of variation operators and local optimization, proved to be a powerful approach in determining the crystal structure of materials. This review summarized the recent progress of the USPEX method as a tool for crystal structure prediction. In particular, we highlight the methodology in (1) prediction of molecular crystal structures and (2) variable-composition structure predictions, and their applications to a series of systems, including Mg(BH4)2, Xe-O, Mg-O compounds, etc. We demonstrate that this method has a wide field of applications in both computational materials design and studies of matter at extreme conditions.

  11. Language and Literature in Tertiary Education: The Case for Stylistics.

    Science.gov (United States)

    Buckledee, Steve

    2002-01-01

    Advocates the use of stylistics for teaching English-as-a-Foreign-Language at the tertiary level. Describes stylistics, discusses discourse conventions and grammatical structure, and examines stylistic analysis of a Shakespearian sonnet and a poem. (Author/VWL)

  12. Primary Index Term Secondary Index Term Tertiary Index term ...

    Indian Academy of Sciences (India)

    chaubey

    Tertiary Index term. Geosciences. Solid earth. Tectonics. Structural Geology. Geodynamics. Seismology. Exploration geophysics. Seismic hazards. Geomagnetism. Mineralogy. Petrology. Metamorphic. Igneous. Sedimentary. Fossil fuels. Petroleum and coal. Isotope geology. Geochronology. Isotope geology. Landform and.

  13. Principles for Predicting RNA Secondary Structure Design Difficulty.

    Science.gov (United States)

    Anderson-Lee, Jeff; Fisker, Eli; Kosaraju, Vineet; Wu, Michelle; Kong, Justin; Lee, Jeehyung; Lee, Minjae; Zada, Mathew; Treuille, Adrien; Das, Rhiju

    2016-02-27

    Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Pathways to Structure-Property Relationships of Peptide-Materials Interfaces: Challenges in Predicting Molecular Structures.

    Science.gov (United States)

    Walsh, Tiffany R

    2017-07-18

    challenges in their successful application to model the biotic-abiotic interface, related to several factors. For instance, simulations require a plausible description of the chemistry and the physics of the interface, which comprises two very different states of matter, in the presence of liquid water. Also, it is essential that the conformational ensemble be comprehensively characterized under these conditions; this is especially challenging because intrinsically disordered peptides do not typically admit one single structure or set of structures. Moreover, a plausible structural model of the substrate is required, which may require a high level of detail, even for single-element materials such as Au surfaces or graphene. Developing and applying strategies to make credible predictions of the conformational ensemble of adsorbed peptides and using these to construct structure-property relationships of these interfaces have been the goals of our efforts. We have made substantial progress in developing interatomic potentials for these interfaces and adapting advanced conformational sampling approaches for these purposes. This Account summarizes our progress in the development and deployment of interfacial force fields and molecular simulation techniques for the purpose of elucidating these insights at biomolecule-materials interfaces, using examples from our laboratories ranging from noble-metal interfaces to graphitic substrates (including carbon nanotubes and graphene) and oxide materials (such as titania). In addition to the well-established application areas of plasmonic materials, biosensing, and the production of medical implant materials, we outline new directions for this field that have the potential to bring new advances in areas such as energy materials and regenerative medicine.

  15. Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

    National Research Council Canada - National Science Library

    Anum Munir; Azhar Mehmood; Shumaila Azam

    2016-01-01

    ... built up. Illustrating the structural and functional privileged insights of these HPs might likewise prompt a superior comprehension of the protein-protein associations or networks in diverse types of life. Bananas (Musa acuminata spp...

  16. Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music.

    Science.gov (United States)

    Agres, Kat; Herremans, Dorien; Bigo, Louis; Conklin, Darrell

    2016-01-01

    An empirical investigation of how local harmonic structures (e.g., chord progressions) contribute to the experience and enjoyment of uplifting trance (UT) music is presented. The connection between rhythmic and percussive elements and resulting trance-like states has been highlighted by musicologists, but no research, to our knowledge, has explored whether repeated harmonic elements influence affective responses in listeners of trance music. Two alternative hypotheses are discussed, the first highlighting the direct relationship between repetition/complexity and enjoyment, and the second based on the theoretical inverted-U relationship described by the Wundt curve. We investigate the connection between harmonic structure and subjective enjoyment through interdisciplinary behavioral and computational methods: First we discuss an experiment in which listeners provided enjoyment ratings for computer-generated UT anthems with varying levels of harmonic repetition and complexity. The anthems were generated using a statistical model trained on a corpus of 100 uplifting trance anthems created for this purpose, and harmonic structure was constrained by imposing particular repetition structures (semiotic patterns defining the order of chords in the sequence) on a professional UT music production template. Second, the relationship between harmonic structure and enjoyment is further explored using two computational approaches, one based on average Information Content, and another that measures average tonal tension between chords. The results of the listening experiment indicate that harmonic repetition does in fact contribute to the enjoyment of uplifting trance music. More compelling evidence was found for the second hypothesis discussed above, however some maximally repetitive structures were also preferred. Both computational models provide evidence for a Wundt-type relationship between complexity and enjoyment. By systematically manipulating the structure of chord

  17. Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music

    Science.gov (United States)

    Agres, Kat; Herremans, Dorien; Bigo, Louis; Conklin, Darrell

    2017-01-01

    An empirical investigation of how local harmonic structures (e.g., chord progressions) contribute to the experience and enjoyment of uplifting trance (UT) music is presented. The connection between rhythmic and percussive elements and resulting trance-like states has been highlighted by musicologists, but no research, to our knowledge, has explored whether repeated harmonic elements influence affective responses in listeners of trance music. Two alternative hypotheses are discussed, the first highlighting the direct relationship between repetition/complexity and enjoyment, and the second based on the theoretical inverted-U relationship described by the Wundt curve. We investigate the connection between harmonic structure and subjective enjoyment through interdisciplinary behavioral and computational methods: First we discuss an experiment in which listeners provided enjoyment ratings for computer-generated UT anthems with varying levels of harmonic repetition and complexity. The anthems were generated using a statistical model trained on a corpus of 100 uplifting trance anthems created for this purpose, and harmonic structure was constrained by imposing particular repetition structures (semiotic patterns defining the order of chords in the sequence) on a professional UT music production template. Second, the relationship between harmonic structure and enjoyment is further explored using two computational approaches, one based on average Information Content, and another that measures average tonal tension between chords. The results of the listening experiment indicate that harmonic repetition does in fact contribute to the enjoyment of uplifting trance music. More compelling evidence was found for the second hypothesis discussed above, however some maximally repetitive structures were also preferred. Both computational models provide evidence for a Wundt-type relationship between complexity and enjoyment. By systematically manipulating the structure of chord

  18. PREDICTING APHASIA TYPE FROM BRAIN DAMAGE MEASURED WITH STRUCTURAL MRI

    OpenAIRE

    Yourganov, Grigori; Smith, Kimberly G.; Fridriksson, Julius; Rorden, Chris

    2015-01-01

    Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca’s, Wernicke’s,...

  19. Structural Properties of MHC Class II Ligands, Implications for the Prediction of MHC Class II Epitopes

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Buus, Søren; Nielsen, Morten

    2010-01-01

    class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC...... class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and......, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100–200 peptides per allele) to derive accurate description of their binding motif. Little work has been performed characterizing structural...

  20. Building a better fragment library for de novo protein structure prediction.

    Directory of Open Access Journals (Sweden)

    Saulo H P de Oliveira

    Full Text Available Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10. We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".

  1. GTfold: Enabling parallel RNA secondary structure prediction on multi-core desktops

    DEFF Research Database (Denmark)

    Swenson, M Shel; Anderson, Joshua; Ash, Andrew

    2012-01-01

    Accurate and efficient RNA secondary structure prediction remains an important open problem in computational molecular biology. Historically, advances in computing technology have enabled faster and more accurate RNA secondary structure predictions. Previous parallelized prediction programs...... achieved significant improvements in runtime, but their implementations were not portable from niche high-performance computers or easily accessible to most RNA researchers. With the increasing prevalence of multi-core desktop machines, a new parallel prediction program is needed to take full advantage......, on machines with four or more cores. Conclusions GTfold supports advances in RNA structural biology by reducing the timescales for secondary structure prediction. The difference will be particularly valuable to researchers working with lengthy RNA sequences, such as RNA viral genomes....

  2. Evolving stochastic context-free grammars for RNA secondary structure prediction

    DEFF Research Database (Denmark)

    Anderson, James WJ; Tataru, Paula Cristina; Stains, Joe

    2012-01-01

    with quite different structure could have very similar predictive ability. Many ambiguous grammars were found which were at least as effective as the best current unambiguous grammars. Conclusions Overall the method of evolving SCFGs for RNA secondary structure prediction proved effective in finding many...... grammars that had strong predictive accuracy, as good or slightly better than those designed manually. Furthermore, several of the best grammars found were ambiguous, demonstrating that such grammars should not be disregarded.......Background Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few...

  3. Knowledge-based prediction of protein backbone conformation using a structural alphabet.

    Science.gov (United States)

    Vetrivel, Iyanar; Mahajan, Swapnil; Tyagi, Manoj; Hoffmann, Lionel; Sanejouand, Yves-Henri; Srinivasan, Narayanaswamy; de Brevern, Alexandre G; Cadet, Frédéric; Offmann, Bernard

    2017-01-01

    Libraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks, is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of Protein Blocks. Predicting the local structure of a protein in terms of protein blocks is the general objective of this work. A new approach, PB-kPRED is proposed towards this aim. It involves (i) organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii) applying a knowledge-based algorithm that does not rely on any secondary structure predictions and/or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures. Though PB-kPRED uses the structural information from homologues in preference, if available. The predictions were evaluated rigorously on 15,544 query proteins representing a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. We have shown that the kPRED method was able to achieve mean accuracies ranging from 40.8% to 66.3% depending on the availability of homologues. The impact of the different strategies for scanning the database on the prediction was evaluated and is discussed. Our results highlight the usefulness of the method in the context of proteins without any known structural homologues. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82). An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.

  4. Knowledge-based prediction of protein backbone conformation using a structural alphabet.

    Directory of Open Access Journals (Sweden)

    Iyanar Vetrivel

    Full Text Available Libraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks, is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of Protein Blocks. Predicting the local structure of a protein in terms of protein blocks is the general objective of this work. A new approach, PB-kPRED is proposed towards this aim. It involves (i organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii applying a knowledge-based algorithm that does not rely on any secondary structure predictions and/or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures. Though PB-kPRED uses the structural information from homologues in preference, if available. The predictions were evaluated rigorously on 15,544 query proteins representing a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. We have shown that the kPRED method was able to achieve mean accuracies ranging from 40.8% to 66.3% depending on the availability of homologues. The impact of the different strategies for scanning the database on the prediction was evaluated and is discussed. Our results highlight the usefulness of the method in the context of proteins without any known structural homologues. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82. An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.

  5. Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

    CERN Document Server

    Takács, Gergely

    2012-01-01

    Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

  6. LOCUSTRA: accurate prediction of local protein structure using a two-layer support vector machine approach.

    Science.gov (United States)

    Zimmermann, Olav; Hansmann, Ulrich H E

    2008-09-01

    Constraint generation for 3d structure prediction and structure-based database searches benefit from fine-grained prediction of local structure. In this work, we present LOCUSTRA, a novel scheme for the multiclass prediction of local structure that uses two layers of support vector machines (SVM). Using a 16-letter structural alphabet from de Brevern et al. (Proteins: Struct., Funct., Bioinf. 2000, 41, 271-287), we assess its prediction ability for an independent test set of 222 proteins and compare our method to three-class secondary structure prediction and direct prediction of dihedral angles. The prediction accuracy is Q16=61.0% for the 16 classes of the structural alphabet and Q3=79.2% for a simple mapping to the three secondary classes helix, sheet, and coil. We achieve a mean phi(psi) error of 24.74 degrees (38.35 degrees) and a median RMSDA (root-mean-square deviation of the (dihedral) angles) per protein chain of 52.1 degrees. These results compare favorably with related approaches. The LOCUSTRA web server is freely available to researchers at http://www.fz-juelich.de/nic/cbb/service/service.php.

  7. Carte géologique et Structurale des bassins tertiaires du domaine méditerranéen : commentaires Geological and Structural Map of Tertiary Basins in the Mediterranean Domain : Comments

    Directory of Open Access Journals (Sweden)

    Biju-Duval B.

    2006-11-01

    Full Text Available Cette note est destinée à commenter la représentation adoptée sur la « Carte géologique et structurale des bassins tertiaires du domaine méditerranéen » publiée par l'IFP, le CNEXO et l'INAG. On y précise les principes de réalisation, le but principal étant de situer les informations marines disponibles dans leur cadre géologique s les données en mer sont principalement relatives aux séries quaternaires et tertiaires récentes : seules celles-ci ont été détaillées sur la carte et inscrites dans le cadre structural des bassins. Dans une première partie, des commentaires techniques précisent les différentes représentations utilisées à terre et en mer, situent les simplifications effectuées et donnent un aperçu sur la bibliographie et l'évolution des connaissances. La seconde partie permet de survoler rapidement les problèmes des bassins tertiaires méditerranéens par quelques commentaires géologiques qui donnent une esquisse de l'histoire de ces bassins. En conclusion, on essaie de faire ressortir les points importants qui se dégagent après lecture attentive de la carte. The aim of this article is ta comment on the representation adopted for the « Geological and Structural Map of Tertiary Basins in the Mediterranean Domain » published by IFP, CNEXO and INAG. The main goals are shaded, with the principal one being to situate available marine data in their geological setting. Offshore data mainly have ta do with recent Quartenary and Tertiary series which are the only cries itemized on the map and included within the structural setting of the basins. The first part contains technical comments on the different representations used, both onshore and offshore, to situate the simplifications used and to give some insight into the bibliography and how our understanding has evolved. The second part makes a brief review of problems relating to Mediterranean Tertiary basins with the help of various geological comments

  8. Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

    Science.gov (United States)

    Yehdego, Daniel T; Zhang, Boyu; Kodimala, Vikram K R; Johnson, Kyle L; Taufer, Michela; Leung, Ming-Ying

    2013-05-01

    Secondary structures of ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Experimental observations and computing limitations suggest that we can approach the secondary structure prediction problem for long RNA sequences by segmenting them into shorter chunks, predicting the secondary structures of each chunk individually using existing prediction programs, and then assembling the results to give the structure of the original sequence. The selection of cutting points is a crucial component of the segmenting step. Noting that stem-loops and pseudoknots always contain an inversion, i.e., a stretch of nucleotides followed closely by its inverse complementary sequence, we developed two cutting methods for segmenting long RNA sequences based on inversion excursions: the centered and optimized method. Each step of searching for inversions, chunking, and predictions can be performed in parallel. In this paper we use a MapReduce framework, i.e., Hadoop, to extensively explore meaningful inversion stem lengths and gap sizes for the segmentation and identify correlations between chunking methods and prediction accuracy. We show that for a set of long RNA sequences in the RFAM database, whose secondary structures are known to contain pseudoknots, our approach predicts secondary structures more accurately than methods that do not segment the sequence, when the latter predictions are possible computationally. We also show that, as sequences exceed certain lengths, some programs cannot computationally predict pseudoknots while our chunking methods can. Overall, our predicted structures still retain the accuracy level of the original prediction programs when compared with known experimental secondary structure.

  9. An adaptive genetic algorithm for crystal structure prediction

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Shunqing [Xiamen Univ., (People' s Republic of China); Ames Lab., Ames, IA (United States); Ji, Min [Ames Lab., Ames, IA (United States); Wang, Cai-Zhuang [Ames Lab., Ames, IA (United States); Nguyen, Manh Cuong [Ames Lab., Ames, IA (United States); Zhao, Xin [Ames Lab., Ames, IA (United States); Umemoto, K. [Ames Lab., Ames, IA (United States); Univ. of Minnesota, Minneapolis, MN (United States); Wentzcovitch, R. M. [Univ. of Minnesota, Minneapolis, MN (United States); Ho, Kai-Ming [Ames Lab., Ames, IA (United States)

    2013-12-18

    We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This strategy increases the efficiency of the DFT-based GA by several orders of magnitude. This gain allows a considerable increase in the size and complexity of systems that can be studied by first principles. The performance of the method is illustrated by successful structure identifications of complex binary and ternary intermetallic compounds with 36 and 54 atoms per cell, respectively. The discovery of a multi-TPa Mg-silicate phase with unit cell containing up to 56 atoms is also reported. Such a phase is likely to be an essential component of terrestrial exoplanetary mantles.

  10. 3D protein structure prediction of influenza A virus based on optimization genetic algorithm.

    Science.gov (United States)

    Gao, Jie; Jin, Pei-Xuan; Xu, Hong-xing

    2014-05-01

    The 3D structure of close polymer is constituted by the interaction of close contact couples among amino acid residues. In this paper, 3D protein structure of influenza A virus was predicted. Twenty kinds of amino acid residues were divided into four categories according to the number of close contact couples. The stable structure with minimum energy was obtained by using optimization genetic algorithm. The HNXP 3D lattice model was established to predict the 3D protein structure. It can be concluded that the two kinds of structures are significantly similar by computing the similarity.

  11. Multiple classifier integration for the prediction of protein structural classes.

    Science.gov (United States)

    Chen, Lei; Lu, Lin; Feng, Kairui; Li, Wenjin; Song, Jie; Zheng, Lulu; Yuan, Youlang; Zeng, Zhenbin; Feng, Kaiyan; Lu, Wencong; Cai, Yudong

    2009-11-15

    Supervised classifiers, such as artificial neural network, partition trees, and support vector machines, are often used for the prediction and analysis of biological data. However, choosing an appropriate classifier is not straightforward because each classifier has its own strengths and weaknesses, and each biological dataset has its own characteristics. By integrating many classifiers together, people can avoid the dilemma of choosing an individual classifier out of many to achieve an optimized classification results (Rahman et al., Multiple Classifier Combination for Character Recognition: Revisiting the Majority Voting System and Its Variation, Springer, Berlin, 2002, 167-178). The classification algorithms come from Weka (Witten and Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, San Francisco, 2005) (a collection of software tools for machine learning algorithms). By integrating many predictors (classifiers) together through simple voting, the correct prediction (classification) rates are 65.21% and 65.63% for a basic training dataset and an independent test set, respectively. These results are better than any single machine learning algorithm collected in Weka when exactly the same data are used. Furthermore, we introduce an integration strategy which takes care of both classifier weightings and classifier redundancy. A feature selection strategy, called minimum redundancy maximum relevance (mRMR), is transferred into algorithm selection to deal with classifier redundancy in this research, and the weightings are based on the performance of each classifier. The best classification results are obtained when 11 algorithms are selected by mRMR method, and integrated together through majority votes with weightings. As a result, the prediction correct rates are 68.56% and 69.29% for the basic training dataset and the independent test dataset, respectively. The web-server is available at http

  12. Observation selection bias in contact prediction and its implications for structural bioinformatics.

    Science.gov (United States)

    Orlando, G; Raimondi, D; Vranken, W F

    2016-11-18

    Next Generation Sequencing is dramatically increasing the number of known protein sequences, with related experimentally determined protein structures lagging behind. Structural bioinformatics is attempting to close this gap by developing approaches that predict structure-level characteristics for uncharacterized protein sequences, with most of the developed methods relying heavily on evolutionary information collected from homologous sequences. Here we show that there is a substantial observational selection bias in this approach: the predictions are validated on proteins with known structures from the PDB, but exactly for those proteins significantly more homologs are available compared to less studied sequences randomly extracted from Uniprot. Structural bioinformatics methods that were developed this way are thus likely to have over-estimated performances; we demonstrate this for two contact prediction methods, where performances drop up to 60% when taking into account a more realistic amount of evolutionary information. We provide a bias-free dataset for the validation for contact prediction methods called NOUMENON.

  13. Novel stable structure of Li3PS4 predicted by evolutionary algorithm under high-pressure

    Directory of Open Access Journals (Sweden)

    S. Iikubo

    2018-01-01

    Full Text Available By combining theoretical predictions and in-situ X-ray diffraction under high pressure, we found a novel stable crystal structure of Li3PS4 under high pressures. At ambient pressure, Li3PS4 shows successive structural transitions from γ-type to β-type and from β-type to α type with increasing temperature, as is well established. In this study, an evolutionary algorithm successfully predicted the γ-type crystal structure at ambient pressure and further predicted a possible stable δ-type crystal structures under high pressure. The stability of the obtained structures is examined in terms of both static and dynamic stability by first-principles calculations. In situ X-ray diffraction using a synchrotron radiation revealed that the high-pressure phase is the predicted δ-Li3PS4 phase.

  14. Predicting 3D Structure, Flexibility, and Stability of RNA Hairpins in Monovalent and Divalent Ion Solutions

    Science.gov (United States)

    Shi, Ya-Zhou; Jin, Lei; Wang, Feng-Hua; Zhu, Xiao-Long; Tan, Zhi-Jie

    2015-01-01

    A full understanding of RNA-mediated biology would require the knowledge of three-dimensional (3D) structures, structural flexibility, and stability of RNAs. To predict RNA 3D structures and stability, we have previously proposed a three-bead coarse-grained predictive model with implicit salt/solvent potentials. In this study, we further develop the model by improving the implicit-salt electrostatic potential and including a sequence-dependent coaxial stacking potential to enable the model to simulate RNA 3D structure folding in divalent/monovalent ion solutions. The model presented here can predict 3D structures of RNA hairpins with bulges/internal loops (RNA hairpins with bulge loops of different lengths at several divalent/monovalent ion conditions. In addition, the model successfully predicts the stability of RNA hairpins with various loops/stems in divalent/monovalent ion solutions. PMID:26682822

  15. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

    DEFF Research Database (Denmark)

    Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.

    2012-01-01

    Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing...... methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used nc...

  16. Water balance and topography predict fire and forest structure patterns

    Science.gov (United States)

    Van R. Kane; James A. Lutz; C. Alina Cansler; Nicholas A. Povak; Derek J. Churchill; Douglas F. Smith; Jonathan T. Kane; Malcolm P. North

    2015-01-01

    Mountainous topography creates fine-scale environmental mosaics that vary in precipitation, temperature, insolation, and slope position. This mosaic in turn influences fuel accumulation and moisture and forest structure. We studied these the effects of varying environmental conditions across a 27,104 ha landscape within Yosemite National Park, California, USA, on the...

  17. Is protein structure prediction still an enigma? | Sobha | African ...

    African Journals Online (AJOL)

    Proteins are large molecules indispensable for the existence and proper functioning of biological organisms. They perform a wide array of functions including catalysis, structure formation, transport, body defense, etc. Understanding the functions of proteins is a fundamental problem in the discovery of drugs to treat various ...

  18. Prediction of Vibration Transmission within Periodic Bar Structures

    DEFF Research Database (Denmark)

    Domadiya, Parthkumar Gandalal; Andersen, Lars Vabbersgaard; Sorokin, Sergey

    2012-01-01

    The present analysis focuses on vibration transmission within semi-infinite bar structure. The bar is consisting of two different materials in a periodic manner. A periodic bar model is generated using two various methods: The Finite Element method (FEM) and a Floquet theory approach. A parameter...

  19. Models for Prediction of Structural Properties of Palmnut Fibre ...

    African Journals Online (AJOL)

    An analytical study was carried out to investigate the structural properties of palmnut fibre reinforced cement-based composites. Explicit expressions were derived for the flexural, compressive and elongation behavior of composites using a two-phase constitutive model and verified using results obtained from literature.

  20. Structure Building Predicts Grades in College Psychology and Biology

    Science.gov (United States)

    Arnold, Kathleen M.; Daniel, David B.; Jensen, Jamie L.; McDaniel, Mark A.; Marsh, Elizabeth J.

    2016-01-01

    Knowing what skills underlie college success can allow students, teachers, and universities to identify and to help at-risk students. One skill that may underlie success across a variety of subject areas is structure building, the ability to create mental representations of narratives (Gernsbacher, Varner, & Faust, 1990). We tested if…

  1. Memoir: template-based structure prediction for membrane proteins.

    Science.gov (United States)

    Ebejer, Jean-Paul; Hill, Jamie R; Kelm, Sebastian; Shi, Jiye; Deane, Charlotte M

    2013-07-01

    Membrane proteins are estimated to be the targets of 50% of drugs that are currently in development, yet we have few membrane protein crystal structures. As a result, for a membrane protein of interest, the much-needed structural information usually comes from a homology model. Current homology modelling software is optimized for globular proteins, and ignores the constraints that the membrane is known to place on protein structure. Our Memoir server produces homology models using alignment and coordinate generation software that has been designed specifically for transmembrane proteins. Memoir is easy to use, with the only inputs being a structural template and the sequence that is to be modelled. We provide a video tutorial and a guide to assessing model quality. Supporting data aid manual refinement of the models. These data include a set of alternative conformations for each modelled loop, and a multiple sequence alignment that incorporates the query and template. Memoir works with both α-helical and β-barrel types of membrane proteins and is freely available at http://opig.stats.ox.ac.uk/webapps/memoir.

  2. Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction

    Directory of Open Access Journals (Sweden)

    Chira Camelia

    2011-07-01

    Full Text Available Abstract Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods.

  3. Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction

    Science.gov (United States)

    2011-01-01

    Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP) model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods. PMID:21801435

  4. Predictive Structure and Topology of Peroxisomal ATP-Binding Cassette (ABC Transporters

    Directory of Open Access Journals (Sweden)

    Pierre Andreoletti

    2017-07-01

    Full Text Available The peroxisomal ATP-binding Cassette (ABC transporters, which are called ABCD1, ABCD2 and ABCD3, are transmembrane proteins involved in the transport of various lipids that allow their degradation inside the organelle. Defective ABCD1 leads to the accumulation of very long-chain fatty acids and is associated with a complex and severe neurodegenerative disorder called X-linked adrenoleukodystrophy (X-ALD. Although the nucleotide-binding domain is highly conserved and characterized within the ABC transporters family, solid data are missing for the transmembrane domain (TMD of ABCD proteins. The lack of a clear consensus on the secondary and tertiary structure of the TMDs weakens any structure-function hypothesis based on the very diverse ABCD1 mutations found in X-ALD patients. Therefore, we first reinvestigated thoroughly the structure-function data available and performed refined alignments of ABCD protein sequences. Based on the 2.85  Å resolution crystal structure of the mitochondrial ABC transporter ABCB10, here we propose a structural model of peroxisomal ABCD proteins that specifies the position of the transmembrane and coupling helices, and highlight functional motifs and putative important amino acid residues.

  5. Predictive Modeling of Structural Sensing for Aerospace Applications

    Science.gov (United States)

    2015-08-03

    concrete reinforcing bars, tendons, track rails, one-dimensional (1D) stiffeners, and so on (Bartoli et al., 2005; Loveday, 2008; Marzani et al., 2008...reflections at the vertical edge of the plate. The paper started with a review of the existing non-reflective boundary literature and identified three...used for conductive metallic structures and non-conductive compo- sites (e.g., glass fibre reinforced polymers), not including the fact that SH-PWAS

  6. Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

    Directory of Open Access Journals (Sweden)

    Anum Munir

    2016-03-01

    Full Text Available Hypothetical proteins (HPs are the proteins whose presence has been anticipated, yet in vivo function has not been built up. Illustrating the structural and functional privileged insights of these HPs might likewise prompt a superior comprehension of the protein-protein associations or networks in diverse types of life. Bananas (Musa acuminata spp., including sweet and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister grouped to the all-around considered Poales, which incorporate oats. Bananas are crucial for nourishment security in numerous tropical and subtropical nations and the most prominent organic product in industrialized nations. In the present study, the hypothetical protein of M. acuminata (Banana was chosen for analysis and modeling by distinctive bioinformatics apparatuses and databases. As indicated by primary and secondary structure analysis, XP_009393594.1 is a stable hydrophobic protein containing a noteworthy extent of α-helices; Homology modeling was done utilizing SWISS-MODEL server where the templates identity with XP_009393594.1 protein was less which demonstrated novelty of our protein. Ab initio strategy was conducted to produce its 3D structure. A few evaluations of quality assessment and validation parameters determined the generated protein model as stable with genuinely great quality. Functional analysis was completed by ProtFun 2.2, and KEGG (KAAS, recommended that the hypothetical protein is a transcription factor with cytoplasmic domain as zinc finger. The protein was observed to be vital for translation process, involved in metabolism, signaling and cellular processes, genetic information processing and Zinc ion binding. It is suggested that further test approval would help to anticipate the structures and functions of other uncharacterized proteins of different plants and living being.

  7. Prediction of Chloride Diffusion in Concrete Structure Using Meshless Methods

    OpenAIRE

    Yao, Ling; Li, Xiaolu; Zhang, Ling; Zhang, Lingling

    2016-01-01

    Degradation of RC structures due to chloride penetration followed by reinforcement corrosion is a serious problem in civil engineering. The numerical simulation methods at present mainly involve finite element methods (FEM), which are based on mesh generation. In this study, element-free Galerkin (EFG) and meshless weighted least squares (MWLS) methods are used to solve the problem of simulation of chloride diffusion in concrete. The range of a scaling parameter is presented using numerical e...

  8. Exponential Repulsion Improves Structural Predictability of Molecular Docking

    Czech Academy of Sciences Publication Activity Database

    Bazgier, Václav; Berka, K.; Otyepka, M.; Banáš, P.

    2016-01-01

    Roč. 37, č. 28 (2016), s. 2485-2494 ISSN 0192-8651 Institutional support: RVO:61389030 Keywords : cyclin-dependent kinases * structure-based design * scoring functions * cdk2 inhibitors * force-field * ligand interactions * drug discovery * purine * potent * protein-kinase-2 * molecular docking * dock 6.6 * drug design * cyclin-dependent kinase 2 * directory of decoys Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.229, year: 2016

  9. An efficient genetic algorithm for structure prediction at the nanoscale.

    Science.gov (United States)

    Lazauskas, Tomas; Sokol, Alexey A; Woodley, Scott M

    2017-03-17

    We have developed and implemented a new global optimization technique based on a Lamarckian genetic algorithm with the focus on structure diversity. The key process in the efficient search on a given complex energy landscape proves to be the removal of duplicates that is achieved using a topological analysis of candidate structures. The careful geometrical prescreening of newly formed structures and the introduction of new mutation move classes improve the rate of success further. The power of the developed technique, implemented in the Knowledge Led Master Code, or KLMC, is demonstrated by its ability to locate and explore a challenging double funnel landscape of a Lennard-Jones 38 atom system (LJ38). We apply the redeveloped KLMC to investigate three chemically different systems: ionic semiconductor (ZnO)1-32, metallic Ni13 and covalently bonded C60. All four systems have been systematically explored on the energy landscape defined using interatomic potentials. The new developments allowed us to successfully locate the double funnels of LJ38, find new local and global minima for ZnO clusters, extensively explore the Ni13 and C60 (the buckminsterfullerene, or buckyball) potential energy surfaces.

  10. Water-stable helical structure of tertiary amides of bicyclic β-amino acid bearing 7-azabicyclo[2.2.1]heptane. Full control of amide cis-trans equilibrium by bridgehead substitution.

    Science.gov (United States)

    Hosoya, Masahiro; Otani, Yuko; Kawahata, Masatoshi; Yamaguchi, Kentaro; Ohwada, Tomohiko

    2010-10-27

    Helical structures of oligomers of non-natural β-amino acids are significantly stabilized by intramolecular hydrogen bonding between main-chain amide moieties in many cases, but the structures are generally susceptible to the environment; that is, helices may unfold in protic solvents such as water. For the generation of non-hydrogen-bonded ordered structures of amides (tertiary amides in most cases), control of cis-trans isomerization is crucial, even though there is only a small sterical difference with respect to cis and trans orientations. We have established methods for synthesis of conformationally constrained β-proline mimics, that is, bridgehead-substituted 7-azabicyclo[2.2.1]heptane-2-endo-carboxylic acids. Our crystallographic, 1D- and 2D-NMR, and CD spectroscopic studies in solution revealed that a bridgehead methoxymethyl substituent completely biased the cis-trans equilibrium to the cis-amide structure along the main chain, and helical structures based on the cis-amide linkage were generated independently of the number of residues, from the minimalist dimer through the tetramer, hexamer, and up to the octamer, and irrespective of the solvent (e.g., water, alcohol, halogenated solvents, and cyclohexane). Generality of the control of the amide equilibrium by bridgehead substitution was also examined.

  11. Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

    Directory of Open Access Journals (Sweden)

    Sharma Gaurav

    2007-04-01

    Full Text Available Abstract Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for

  12. Structure Based Predictive Model for Coal Char Combustion

    Energy Technology Data Exchange (ETDEWEB)

    Robert Hurt; Joseph Calo; Robert Essenhigh; Christopher Hadad

    2000-12-30

    This unique collaborative project has taken a very fundamental look at the origin of structure, and combustion reactivity of coal chars. It was a combined experimental and theoretical effort involving three universities and collaborators from universities outside the U.S. and from U.S. National Laboratories and contract research companies. The project goal was to improve our understanding of char structure and behavior by examining the fundamental chemistry of its polyaromatic building blocks. The project team investigated the elementary oxidative attack on polyaromatic systems, and coupled with a study of the assembly processes that convert these polyaromatic clusters to mature carbon materials (or chars). We believe that the work done in this project has defined a powerful new science-based approach to the understanding of char behavior. The work on aromatic oxidation pathways made extensive use of computational chemistry, and was led by Professor Christopher Hadad in the Department of Chemistry at Ohio State University. Laboratory experiments on char structure, properties, and combustion reactivity were carried out at both OSU and Brown, led by Principle Investigators Joseph Calo, Robert Essenhigh, and Robert Hurt. Modeling activities were divided into two parts: first unique models of crystal structure development were formulated by the team at Brown (PI'S Hurt and Calo) with input from Boston University and significant collaboration with Dr. Alan Kerstein at Sandia and with Dr. Zhong-Ying chen at SAIC. Secondly, new combustion models were developed and tested, led by Professor Essenhigh at OSU, Dieter Foertsch (a collaborator at the University of Stuttgart), and Professor Hurt at Brown. One product of this work is the CBK8 model of carbon burnout, which has already found practical use in CFD codes and in other numerical models of pulverized fuel combustion processes, such as EPRI's NOxLOI Predictor. The remainder of the report consists of detailed

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  15. Hydrogeology, groundwater levels, and generalized potentiometric-surface map of the Green River Basin lower Tertiary aquifer system, 2010–14, in the northern Green River structural basin

    Science.gov (United States)

    Bartos, Timothy T.; Hallberg, Laura L.; Eddy-Miller, Cheryl

    2015-07-14

    In cooperation with the Bureau of Land Management, groundwater levels in wells located in the northern Green River Basin in Wyoming, an area of ongoing energy development, were measured by the U.S. Geological Survey from 2010 to 2014. The wells were completed in the uppermost aquifers of the Green River Basin lower Tertiary aquifer system, which is a complex regional aquifer system that provides water to most wells in the area. Except for near perennial streams, groundwater-level altitudes in most aquifers generally decreased with increasing depth, indicating a general downward potential for groundwater movement in the study area. Drilled depth of the wells was observed as a useful indicator of depth to groundwater such that deeper wells typically had a greater depth to groundwater. Comparison of a subset of wells included in this study that had historical groundwater levels that were measured during the 1960s and 1970s and again between 2012 and 2014 indicated that, overall, most of the wells showed a net decline in groundwater levels.

  16. Ar-40 to Ar-39 ages of the large impact structures Kara and Manicouagan and their relevance to the Cretaceous-Tertiary and the Triassic-Jurassic boundary

    Science.gov (United States)

    Trieloff, M.; Jessberger, E. K.

    1992-01-01

    Since the discovery of the Ir enrichment in Cretaceous-Tertiary boundary clays in 1980, the effects of a 10-km asteroid impacting on the Earth 65 Ma ago have been discussed as the possible reason for the mass extinction--including the extinction of the dinosaurs--at the end of the Cretaceous. But up to now no crater of this age that is large enough (ca. 200 km in diameter) has been found. One candidate is the Kara Crater in northern Siberia. Kolesnikov et al. determined a K-Ar isochron of 65.6 +/- 0.5 Ma, indistinguishable from the age of the K-T boundary and interpreted this as confirmation of earlier proposals that the Kara bolide would have been at least one of the K-T impactors. Koeberl et al. determined Ar-40 to Ar-39 ages ranging from 70 to 82 Ma and suggested an association to the Campanian-Maastrichtian boundary, another important extinction horizon 73 Ma ago. We dated four impact melts, KA2-306, KA2-305, SA1-302, and AN9-182. Results from the investigation are discussed.

  17. FLORA: a novel method to predict protein function from structure in diverse superfamilies.

    Directory of Open Access Journals (Sweden)

    Oliver C Redfern

    2009-08-01

    Full Text Available Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA that automatically generates structural motifs associated with different functional sub-families (FSGs within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2-3 fold increase in coverage at low error rates popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (alpha, beta, alphabeta and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues.

  18. Systematic evaluation of CS-Rosetta for membrane protein structure prediction with sparse NOE restraints.

    Science.gov (United States)

    Reichel, Katrin; Fisette, Olivier; Braun, Tatjana; Lange, Oliver F; Hummer, Gerhard; Schäfer, Lars V

    2017-05-01

    We critically test and validate the CS-Rosetta methodology for de novo structure prediction of α-helical membrane proteins (MPs) from NMR data, such as chemical shifts and NOE distance restraints. By systematically reducing the number and types of NOE restraints, we focus on determining the regime in which MP structures can be reliably predicted and pinpoint the boundaries of the approach. Five MPs of known structure were used as test systems, phototaxis sensory rhodopsin II (pSRII), a subdomain of pSRII, disulfide binding protein B (DsbB), microsomal prostaglandin E2 synthase-1 (mPGES-1), and translocator protein (TSPO). For pSRII and DsbB, where NMR and X-ray structures are available, resolution-adapted structural recombination (RASREC) CS-Rosetta yields structures that are as close to the X-ray structure as the published NMR structures if all available NMR data are used to guide structure prediction. For mPGES-1 and Bacillus cereus TSPO, where only X-ray crystal structures are available, highly accurate structures are obtained using simulated NMR data. One main advantage of RASREC CS-Rosetta is its robustness with respect to even a drastic reduction of the number of NOEs. Close-to-native structures were obtained with one randomly picked long-range NOEs for every 14, 31, 38, and 8 residues for full-length pSRII, the pSRII subdomain, TSPO, and DsbB, respectively, in addition to using chemical shifts. For mPGES-1, atomically accurate structures could be predicted even from chemical shifts alone. Our results show that atomic level accuracy for helical membrane proteins is achievable with CS-Rosetta using very sparse NOE restraint sets to guide structure prediction. Proteins 2017; 85:812-826. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure.

    Science.gov (United States)

    Francis, Stephen Starko; Plucinski, Mateusz M; Wallace, Amelia D; Riley, Lee W

    Social network structure is a fundamental determinant of human health, from infectious to chronic diseases. However, quantitative and unbiased approaches to measuring social network structure are lacking. We hypothesized that genetic relatedness of oral commensal bacteria could be used to infer social contact between humans, just as genetic relatedness of pathogens can be used to determine transmission chains of pathogens. We used a traditional, questionnaire survey-based method to characterize the contact network of the School of Public Health at a large research university. We then collected saliva from a subset of individuals to analyze their oral microflora using a modified deep sequencing multilocus sequence typing (MLST) procedure. We examined micro-evolutionary changes in the S. viridans group to uncover transmission patterns reflecting social network structure. We amplified seven housekeeping gene loci from the Streptococcus viridans group, a group of ubiquitous commensal bacteria, and sequenced the PCR products using next-generation sequencing. By comparing the generated S. viridans reads between pairs of individuals, we reconstructed the social network of the sampled individuals and compared it to the network derived from the questionnaire survey-based method. The genetic relatedness significantly (p-value social distance in the questionnaire-based network, and the reconstructed network closely matched the network derived from the questionnaire survey-based method. Oral commensal bacterial are thus likely transmitted through routine physical contact or shared environment. Their genetic relatedness can be used to represent a combination of social contact and shared physical space, therefore reconstructing networks of contact. This study provides the first step in developing a method to measure direct social contact based on commensal organism genotyping, potentially capable of unmasking hidden social networks that contribute to pathogen transmission.

  20. Predicting target DNA sequences of DNA-binding proteins based on unbound structures.

    Directory of Open Access Journals (Sweden)

    Chien-Yu Chen

    Full Text Available DNA-binding proteins such as transcription factors use DNA-binding domains (DBDs to bind to specific sequences in the genome to initiate many important biological functions. Accurate prediction of such target sequences, often represented by position weight matrices (PWMs, is an important step to understand many biological processes. Recent studies have shown that knowledge-based potential functions can be applied on protein-DNA co-crystallized structures to generate PWMs that are considerably consistent with experimental data. However, this success has not been extended to DNA-binding proteins lacking co-crystallized structures. This study aims at investigating the possibility of predicting the DNA sequences bound by DNA-binding proteins from the proteins' unbound structures (structures of the unbound state. Given an unbound query protein and a template complex, the proposed method first employs structure alignment to generate synthetic protein-DNA complexes for the query protein. Once a complex is available, an atomic-level knowledge-based potential function is employed to predict PWMs characterizing the sequences to which the query protein can bind. The evaluation of the proposed method is based on seven DNA-binding proteins, which have structures of both DNA-bound and unbound forms for prediction as well as annotated PWMs for validation. Since this work is the first attempt to predict target sequences of DNA-binding proteins from their unbound structures, three types of structural variations that presumably influence the prediction accuracy were examined and discussed. Based on the analyses conducted in this study, the conformational change of proteins upon binding DNA was shown to be the key factor. This study sheds light on the challenge of predicting the target DNA sequences of a protein lacking co-crystallized structures, which encourages more efforts on the structure alignment-based approaches in addition to docking- and homology

  1. Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

    Science.gov (United States)

    Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

    2017-10-01

    So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

  2. Predictive model for early math skills based on structural equations.

    Science.gov (United States)

    Aragón, Estíbaliz; Navarro, José I; Aguilar, Manuel; Cerda, Gamal; García-Sedeño, Manuel

    2016-12-01

    Early math skills are determined by higher cognitive processes that are particularly important for acquiring and developing skills during a child's early education. Such processes could be a critical target for identifying students at risk for math learning difficulties. Few studies have considered the use of a structural equation method to rationalize these relations. Participating in this study were 207 preschool students ages 59 to 72 months, 108 boys and 99 girls. Performance with respect to early math skills, early literacy, general intelligence, working memory, and short-term memory was assessed. A structural equation model explaining 64.3% of the variance in early math skills was applied. Early literacy exhibited the highest statistical significance (β = 0.443, p < 0.05), followed by intelligence (β = 0.286, p < 0.05), working memory (β = 0.220, p < 0.05), and short-term memory (β = 0.213, p < 0.05). Correlations between the independent variables were also significant (p < 0.05). According to the results, cognitive variables should be included in remedial intervention programs. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  3. Solution- and adsorbed-state structural ensembles predicted for the statherin-hydroxyapatite system.

    Science.gov (United States)

    Masica, David L; Gray, Jeffrey J

    2009-04-22

    We have developed a multiscale structure prediction technique to study solution- and adsorbed-state ensembles of biomineralization proteins. The algorithm employs a Metropolis Monte Carlo-plus-minimization strategy that varies all torsional and rigid-body protein degrees of freedom. We applied the technique to fold statherin, starting from a fully extended peptide chain in solution, in the presence of hydroxyapatite (HAp) (001), (010), and (100) monoclinic crystals. Blind (unbiased) predictions capture experimentally observed macroscopic and high-resolution structural features and show minimal statherin structural change upon adsorption. The dominant structural difference between solution and adsorbed states is an experimentally observed folding event in statherin's helical binding domain. Whereas predicted statherin conformers vary slightly at three different HAp crystal faces, geometric and chemical similarities of the surfaces allow structurally promiscuous binding. Finally, we compare blind predictions with those obtained from simulation biased to satisfy all previously published solid-state NMR (ssNMR) distance and angle measurements (acquired from HAp-adsorbed statherin). Atomic clashes in these structures suggest a plausible, alternative interpretation of some ssNMR measurements as intermolecular rather than intramolecular. This work demonstrates that a combination of ssNMR and structure prediction could effectively determine high-resolution protein structures at biomineral interfaces.

  4. Predicting Homogeneous Pilus Structure from Monomeric Data and Sparse Constraints

    Directory of Open Access Journals (Sweden)

    Ke Xiao

    2015-01-01

    Full Text Available Type IV pili (T4P and T2SS (Type II Secretion System pseudopili are filaments extending beyond microbial surfaces, comprising homologous subunits called “pilins.” In this paper, we presented a new approach to predict pseudo atomic models of pili combining ambiguous symmetric constraints with sparse distance information obtained from experiments and based neither on electronic microscope (EM maps nor on accurate a priori symmetric details. The approach was validated by the reconstruction of the gonococcal (GC pilus from Neisseria gonorrhoeae, the type IVb toxin-coregulated pilus (TCP from Vibrio cholerae, and pseudopilus of the pullulanase T2SS (the PulG pilus from Klebsiella oxytoca. In addition, analyses of computational errors showed that subunits should be treated cautiously, as they are slightly flexible and not strictly rigid bodies. A global sampling in a wider range was also implemented and implied that a pilus might have more than one but fewer than many possible intact conformations.

  5. Bad to the bone: facial structure predicts unethical behaviour.

    Science.gov (United States)

    Haselhuhn, Michael P; Wong, Elaine M

    2012-02-07

    Researchers spanning many scientific domains, including primatology, evolutionary biology and psychology, have sought to establish an evolutionary basis for morality. While researchers have identified social and cognitive adaptations that support ethical behaviour, a consensus has emerged that genetically determined physical traits are not reliable signals of unethical intentions or actions. Challenging this view, we show that genetically determined physical traits can serve as reliable predictors of unethical behaviour if they are also associated with positive signals in intersex and intrasex selection. Specifically, we identify a key physical attribute, the facial width-to-height ratio, which predicts unethical behaviour in men. Across two studies, we demonstrate that men with wider faces (relative to facial height) are more likely to explicitly deceive their counterparts in a negotiation, and are more willing to cheat in order to increase their financial gain. Importantly, we provide evidence that the link between facial metrics and unethical behaviour is mediated by a psychological sense of power. Our results demonstrate that static physical attributes can indeed serve as reliable cues of immoral action, and provide additional support for the view that evolutionary forces shape ethical judgement and behaviour.

  6. Reliability prediction for structures under cyclic loads and recurring inspections

    Directory of Open Access Journals (Sweden)

    Alberto W. S. Mello Jr

    2009-06-01

    Full Text Available This work presents a methodology for determining the reliability of fracture control plans for structures subjected to cyclic loads. It considers the variability of the parameters involved in the problem, such as initial flaw and crack growth curve. The probability of detection (POD curve of the field non-destructive inspection method and the condition/environment are used as important factors for structural confidence. According to classical damage tolerance analysis (DTA, inspection intervals are based on detectable crack size and crack growth rate. However, all variables have uncertainties, which makes the final result totally stochastic. The material properties, flight loads, engineering tools and even the reliability of inspection methods are subject to uncertainties which can affect significantly the final maintenance schedule. The present methodology incorporates all the uncertainties in a simulation process, such as Monte Carlo, and establishes a relationship between the reliability of the overall maintenance program and the proposed inspection interval, forming a “cascade” chart. Due to the scatter, it also defines the confidence level of the “acceptable” risk. As an example, the damage tolerance analysis (DTA results are presented for the upper cockpit longeron splice bolt of the BAF upgraded F-5EM. In this case, two possibilities of inspection intervals were found: one that can be characterized as remote risk, with a probability of failure (integrity nonsuccess of 1 in 10 million, per flight hour; and other as extremely improbable, with a probability of nonsuccess of 1 in 1 billion, per flight hour, according to aviation standards. These two results are compared with the classical military airplane damage tolerance requirements.

  7. STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION

    Energy Technology Data Exchange (ETDEWEB)

    Robert H. Hurt; Eric M. Suuberg

    2000-05-03

    This report is part on the ongoing effort at Brown University and Ohio State University to develop structure based models of coal combustion. A very fundamental approach is taken to the description of coal chars and their reaction processes, and the results are therefore expected to have broad applicability to the spectrum of carbon materials of interest in energy technologies. This quarter, our work on structure development in carbons continued. A combination of hot stage in situ and ex situ polarized light microscopy was used to identify the preferred orientational of graphene layers at gas interfaces in pitches used as carbon material precursors. The experiments show that edge-on orientation is the equilibrium state of the gas/pitch interface, implying that basal-rich surfaces have higher free energies than edge-rich surfaces in pitch. This result is in agreement with previous molecular modeling studies and TEM observations in the early stages of carbonization. The results may have important implications for the design of tailored carbons with edge-rich or basal-rich surfaces. In the computational chemistry task, we have continued our investigations into the reactivity of large aromatic rings. The role of H-atom abstraction as well as radical addition to monocyclic aromatic rings has been examined, and a manuscript is currently being revised after peer review. We have also shown that OH radical is more effective than H atom in the radical addition process with monocyclic rings. We have extended this analysis to H-atom and OH-radical addition to phenanthrene. Work on combustion kinetics focused on the theoretical analysis of the data previously gathered using thermogravametric analysis.

  8. Qualitative and quantitative structure-activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals.

    Science.gov (United States)

    Gupta, S; Basant, N; Singh, K P

    2015-01-01

    In this study, structure-activity relationship (SAR) models have been established for qualitative and quantitative prediction of the blood-brain barrier (BBB) permeability of chemicals. The structural diversity of the chemicals and nonlinear structure in the data were tested. The predictive and generalization ability of the developed SAR models were tested through internal and external validation procedures. In complete data, the QSAR models rendered ternary classification accuracy of >98.15%, while the quantitative SAR models yielded correlation (r(2)) of >0.926 between the measured and the predicted BBB permeability values with the mean squared error (MSE) 82.7% and r(2) > 0.905 (MSE quantitative models for predicting the BBB permeability of chemicals. Moreover, these models showed predictive performance superior to those reported earlier in the literature. This demonstrates the appropriateness of the developed SAR models to reliably predict the BBB permeability of new chemicals, which can be used for initial screening of the molecules in the drug development process.

  9. Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

    Science.gov (United States)

    Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

    2018-01-19

    Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing

  10. Protein asparagine deamidation prediction based on structures with machine learning methods.

    Directory of Open Access Journals (Sweden)

    Lei Jia

    Full Text Available Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isomerization, glycosylation, oxidation etc. A more accurate prediction method for potential hotspot residues would allow their elimination or reduction as early as possible in the drug discovery process. In this work, we focus on prediction models for asparagine (Asn deamidation. Sequence-based prediction method simply identifies the NG motif (amino acid asparagine followed by a glycine to be liable to deamidation. It still dominates deamidation evaluation process in most pharmaceutical setup due to its convenience. However, the simple sequence-based method is less accurate and often causes over-engineering a protein. We introduce structure-based prediction models by mining available experimental and structural data of deamidated proteins. Our training set contains 194 Asn residues from 25 proteins that all have available high-resolution crystal structures. Experimentally measured deamidation half-life of Asn in penta-peptides as well as 3D structure-based properties, such as solvent exposure, crystallographic B-factors, local secondary structure and dihedral angles etc., were used to train prediction models with several machine learning algorithms. The prediction tools were cross-validated as well as tested with an external test data set. The random forest model had high enrichment in ranking deamidated residues higher than non-deamidated residues while effectively eliminated false positive predictions. It is possible that such quantitative protein structure-function relationship tools can also be applied to other protein hotspot predictions. In addition, we extensively discussed metrics being used to evaluate the performance of predicting unbalanced data sets such as the deamidation case.

  11. Challenging the state-of-the-art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10

    Science.gov (United States)

    Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J. Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V.; Craig, Timothy K.; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C.; van Raaij, Mark J.; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

    2014-01-01

    For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, over 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this paper, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict trans-membrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin IL-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fibre protein gp17 from bacteriophage T7; the Bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. PMID:24318984

  12. STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION

    Energy Technology Data Exchange (ETDEWEB)

    CHRISTOPHER M. HADAD; JOSEPH M. CALO; ROBERT H. ESSENHIGH; ROBERT H. HURT

    1999-01-13

    Significant progress continued to be made during the past reporting quarter on both major technical tasks. During the reporting period at OSU, computational investigations were conducted of addition vs. abstraction reactions of H, O(3 P), and OH with monocyclic aromatic hydrocarbons. The potential energy surface for more than 80 unique reactions of H, O ( 3 P), and OH with aromatic hydrocarbons were determined at the B3LYP/6-31G(d) level of theory. The calculated transition state barriers and reaction free energies indicate that the addition channel is preferred at 298K, but that the abstraction channel becomes dominant at high temperatures. The thermodynamic preference for reactivity with aromatic hydrocarbons increases in the order O(3 P) < H < OH. Abstraction from six-membered aromatic rings is more facile than abstraction from five-membered aromatic rings. However, addition to five-membered rings is thermodynamically more favorable than addition to six-membered rings. The free energies for the abstraction and addition reactions of H, O, and OH with aromatic hydrocarbons and the characteristics of the respective transition states can be used to calculate the reaction rate constants for these important combustion reactions. Experimental work at Brown University on the effect of reaction on the structural evolution of different chars (i.e., phenolic resin char and chars produced from three different coals) have been investigated in a TGA/TPD-MS system. It has been found that samples of different age of these chars appeared to lose their "memory" concerning their initial structures at high burn-offs. During the reporting period, thermal desorption experiments of selected samples were conducted. These spectra show that the population of low temperature oxygen surface complexes, which are primarily responsible for reactivity, are more similar for the high burn-off than for the low burn-off samples of different ages; i.e., the population of active sites are more

  13. All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences.

    Science.gov (United States)

    Hayat, Sikander; Sander, Chris; Marks, Debora S; Elofsson, Arne

    2015-04-28

    Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-helical membrane proteins from sequence alignments alone, we developed an approach to predict the 3D structure of TMBs. The approach combines the maximum-entropy evolutionary coupling method for predicting residue contacts (EVfold) with a machine-learning approach (boctopus2) for predicting β-strands in the barrel. In a blinded test for 19 TMB proteins of known structure that have a sufficient number of diverse homologous sequences available, this combined method (EVfold_bb) predicts hydrogen-bonded residue pairs between adjacent β-strands at an accuracy of ∼70%. This accuracy is sufficient for the generation of all-atom 3D models. In the transmembrane barrel region, the average 3D structure accuracy [template-modeling (TM) score] of top-ranked models is 0.54 (ranging from 0.36 to 0.85), with a higher (44%) number of residue pairs in correct strand-strand registration than in earlier methods (18%). Although the nonbarrel regions are predicted less accurately overall, the evolutionary couplings identify some highly constrained loop residues and, for FecA protein, the barrel including the structure of a plug domain can be accurately modeled (TM score = 0.68). Lower prediction accuracy tends to be associated with insufficient sequence information and we therefore expect increasing numbers of β-barrel families to become accessible to accurate 3D structure prediction as the number of available sequences increases.

  14. Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars

    Directory of Open Access Journals (Sweden)

    Værum Morten

    2011-04-01

    Full Text Available Abstract Background The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state-of-the-art algorithms. The pfold model couples a stochastic context-free grammar to phylogenetic analysis for a high accuracy in predictions, but the time complexity of the algorithm and underflow errors have prevented its use for long alignments. Here we present PPfold, a multithreaded version of pfold, which is capable of predicting the structure of large RNA alignments accurately on practical timescales. Results We have distributed both the phylogenetic calculations and the inside-outside algorithm in PPfold, resulting in a significant reduction of runtime on multicore machines. We have addressed the floating-point underflow problems of pfold by implementing an extended-exponent datatype, enabling PPfold to be used for large-scale RNA structure predictions. We have also improved the user interface and portability: alongside standalone executable and Java source code of the program, PPfold is also available as a free plugin to the CLC Workbenches. We have evaluated the accuracy of PPfold using BRaliBase I tests, and demonstrated its practical use by predicting the secondary structure of an alignment of 24 complete HIV-1 genomes in 65 minutes on an 8-core machine and identifying several known structural elements in the prediction. Conclusions PPfold is the first parallelized comparative RNA structure prediction algorithm to date. Based on the pfold model, PPfold is capable of fast, high-quality predictions of large RNA secondary structures, such as the genomes of RNA viruses or long genomic transcripts. The techniques used in the parallelization of this algorithm may be of general applicability to other bioinformatics algorithms.

  15. Aromatic claw: A new fold with high aromatic content that evades structural prediction: Aromatic Claw

    Energy Technology Data Exchange (ETDEWEB)

    Sachleben, Joseph R. [Biomolecular NMR Core Facility, University of Chicago, Chicago Illinois; Adhikari, Aashish N. [Department of Chemistry, University of Chicago, Chicago Illinois; Gawlak, Grzegorz [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Hoey, Robert J. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Liu, Gaohua [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Joachimiak, Andrzej [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Biological Sciences Division, Argonne National Laboratory, Argonne Illinois; Montelione, Gaetano T. [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Sosnick, Tobin R. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Koide, Shohei [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Department of Biochemistry and Molecular Pharmacology and the Perlmutter Cancer Center, New York University School of Medicine, New York New York

    2016-11-10

    We determined the NMR structure of a highly aromatic (13%) protein of unknown function, Aq1974 from Aquifex aeolicus (PDB ID: 5SYQ). The unusual sequence of this protein has a tryptophan content five times the normal (six tryptophan residues of 114 or 5.2% while the average tryptophan content is 1.0%) with the tryptophans occurring in a WXW motif. It has no detectable sequence homology with known protein structures. Although its NMR spectrum suggested that the protein was rich in β-sheet, upon resonance assignment and solution structure determination, the protein was found to be primarily α-helical with a small two-stranded β-sheet with a novel fold that we have termed an Aromatic Claw. As this fold was previously unknown and the sequence unique, we submitted the sequence to CASP10 as a target for blind structural prediction. At the end of the competition, the sequence was classified a hard template based model; the structural relationship between the template and the experimental structure was small and the predictions all failed to predict the structure. CSRosetta was found to predict the secondary structure and its packing; however, it was found that there was little correlation between CSRosetta score and the RMSD between the CSRosetta structure and the NMR determined one. This work demonstrates that even in relatively small proteins, we do not yet have the capacity to accurately predict the fold for all primary sequences. The experimental discovery of new folds helps guide the improvement of structural prediction methods.

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

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2004-01-01

    than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines...

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

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2005-01-01

    than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines...

  18. Perception of organisational commitment, job satisfaction and turnover intentions in a post-merger South African tertiary institution

    Directory of Open Access Journals (Sweden)

    Adam Martin

    2008-09-01

    Full Text Available A merger can be considered both a phenomenological and signifcant life event for an organisation and its employees, and how people cope with and respond to a merger has a direct impact on the institutional performance in the short to medium term. It is within this context that post-merger perceptions of a tertiary institution were investigated. A predictive model (determined the “best” of 15 predefned models of turnover intentions was developed for employees of a South African tertiary institution (having undergone its own recent merging process. A systematic model-building process was carried out incorporating various techniques, among others structural equation modelling and step-wise linear regression. The fnal predictive model explained 47% of the variance in turnover intentions. Contrary to expectations, commitment does not correlate more strongly than satisfaction does with turnover intentions.

  19. Sexual selection predicts brain structure in dragon lizards.

    Science.gov (United States)

    Hoops, D; Ullmann, J F P; Janke, A L; Vidal-Garcia, M; Stait-Gardner, T; Dwihapsari, Y; Merkling, T; Price, W S; Endler, J A; Whiting, M J; Keogh, J S

    2017-02-01

    Phenotypic traits such as ornaments and armaments are generally shaped by sexual selection, which often favours larger and more elaborate males compared to females. But can sexual selection also influence the brain? Previous studies in vertebrates report contradictory results with no consistent pattern between variation in brain structure and the strength of sexual selection. We hypothesize that sexual selection will act in a consistent way on two vertebrate brain regions that directly regulate sexual behaviour: the medial preoptic nucleus (MPON) and the ventromedial hypothalamic nucleus (VMN). The MPON regulates male reproductive behaviour whereas the VMN regulates female reproductive behaviour and is also involved in male aggression. To test our hypothesis, we used high-resolution magnetic resonance imaging combined with traditional histology of brains in 14 dragon lizard species of the genus Ctenophorus that vary in the strength of precopulatory sexual selection. Males belonging to species that experience greater sexual selection had a larger MPON and a smaller VMN. Conversely, females did not show any patterns of variation in these brain regions. As the volumes of both these regions also correlated with brain volume (BV) in our models, we tested whether they show the same pattern of evolution in response to changes in BV and found that the do. Therefore, we show that the primary brain nuclei underlying reproductive behaviour in vertebrates can evolve in a mosaic fashion, differently between males and females, likely in response to sexual selection, and that these same regions are simultaneously evolving in concert in relation to overall brain size. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

  20. Introduction to structural bioinformatics.

    Science.gov (United States)

    Xu, Qin; Dai, Hao; Zhao, Tangzhen; Wei, Dongqing

    2015-01-01

    Structural Bioinformatics is one of the hot spots of interdisciplinary sciences and obtained amazing advances in recent years. The first chapter overviews the concept of structural bioinformatics, and briefly describe the contents of this book. The interdisciplinary corporations make it difficult to further divide structural bioinformatics, so the chapters in this book are roughly separated according to the different fields of their applications. That is, fundamental developments in methods of structural bioinformatics, tertiary structure prediction and folding mechanism analysis, the binding mechanism and the interactions between biological macromolecules and ligands, structure-based functional analysis of biological macromolecules, as well as the applications in drug design.

  1. Positive predictive value of non-invasive prenatal screening for fetal chromosome disorders using cell-free DNA in maternal serum: independent clinical experience of a tertiary referral center.

    Science.gov (United States)

    Neufeld-Kaiser, Whitney A; Cheng, Edith Y; Liu, Yajuan J

    2015-06-02

    Non-invasive prenatal screening (NIPS) for fetal chromosome abnormalities using cell-free deoxyribonucleic acid (cfDNA) in maternal serum has significantly influenced prenatal diagnosis of fetal aneuploidies since becoming clinically available in the fall of 2011. High sensitivity and specificity have been reported in multiple publications, nearly all of which have been sponsored by the commercial performing laboratories. Once results are returned, positive and negative predictive values (PPVs, NPVs) are the performance metrics most relevant to clinical management. The purpose of this report is to present independent data on the PPVs of NIPS in actual clinical practice. Charts were retrospectively reviewed for patients who had NIPS and were seen March 2012 to December 2013 in a tertiary academic referral center. NIPS results were compared to diagnostic genetic test results, fetal ultrasound results, and clinical phenotype/outcomes. The PPV was calculated using standard epidemiological methods. Correlation between screen results and both maternal age at delivery and gestational age at time of screening was assessed using Wilcoxon's rank sum test. Of 632 patients undergoing NIPS, 92 % of tests were performed in one of the four major commercial laboratories offering testing. However, all four laboratories are represented in both the normal and abnormal results groups. There were 55 abnormal NIPS results. Forty-one of 55 abnormal NIPS results were concordant with abnormal fetal outcomes, 12 were discordant, and 2 were undetermined. The PPV for all conditions included in the screen was 77.4 % (95 % CI, 63.4 - 87.3). Of 578 patients with normal NIPS results, normal pregnancy outcome was confirmed for 156 (27 %) patients. This incomplete follow-up of normal NIPS results does not affect PPV calculations, but it did preclude calculations of sensitivity, specificity, and NPV. Maternal age at delivery was significantly lower for patients with abnormal discordant results

  2. Adaptive Neuro-Fuzzy Inference System Models for Force Prediction of a Mechatronic Flexible Structure

    DEFF Research Database (Denmark)

    Achiche, S.; Shlechtingen, M.; Raison, M.

    2016-01-01

    This paper presents the results obtained from a research work investigating the performance of different Adaptive Neuro-Fuzzy Inference System (ANFIS) models developed to predict excitation forces on a dynamically loaded flexible structure. For this purpose, a flexible structure is equipped...

  3. From structure prediction to genomic screens for novel non-coding RNAs

    DEFF Research Database (Denmark)

    Gorodkin, Jan; Hofacker, Ivo L.

    2011-01-01

    Abstract: Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction...

  4. I-TASSER server: new development for protein structure and function predictions.

    Science.gov (United States)

    Yang, Jianyi; Zhang, Yang

    2015-07-01

    The I-TASSER server (http://zhanglab.ccmb.med.umich.edu/I-TASSER) is an online resource for automated protein structure prediction and structure-based function annotation. In I-TASSER, structural templates are first recognized from the PDB using multiple threading alignment approaches. Full-length structure models are then constructed by iterative fragment assembly simulations. The functional insights are finally derived by matching the predicted structure models with known proteins in the function databases. Although the server has been widely used for various biological and biomedical investigations, numerous comments and suggestions have been reported from the user community. In this article, we summarize recent developments on the I-TASSER server, which were designed to address the requirements from the user community and to increase the accuracy of modeling predictions. Focuses have been made on the introduction of new methods for atomic-level structure refinement, local structure quality estimation and biological function annotations. We expect that these new developments will improve the quality of the I-TASSER server and further facilitate its use by the community for high-resolution structure and function prediction. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Template-based quaternary structure prediction of proteins using enhanced profile-profile alignments.

    Science.gov (United States)

    Nakamura, Tsukasa; Oda, Toshiyuki; Fukasawa, Yoshinori; Tomii, Kentaro

    2017-11-27

    Proteins often exist as their multimeric forms when they function as so-called biological assemblies consisting of the specific number and arrangement of protein subunits. Consequently, elucidating biological assemblies is necessary to improve understanding of protein function. Template-Based Modeling (TBM), based on known protein structures, has been used widely for protein structure prediction. Actually, TBM has become an increasingly useful approach in recent years because of the increased amounts of information related to protein amino acid sequences and three-dimensional structures. An apparently similar situation exists for biological assembly structure prediction as protein complex structures in the PDB increase, although the inference of biological assemblies is not a trivial task. Many methods using TBM, including ours, have been developed for protein structure prediction. Using enhanced profile-profile alignments, we participated in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12), as the FONT team (Group # 480). Herein, we present experimental procedures and results of retrospective analyses using our approach for the Quaternary Structure Prediction category of CASP12. We performed profile-profile alignments of several types, based on FORTE, our profile-profile alignment algorithm, to identify suitable templates. Results show that these alignment results enable us to find templates in almost all possible cases. Moreover, we have come to understand the necessity of developing a model selection method that provides improved accuracy. Results also demonstrate that, to some extent, finding templates of protein complexes is useful even for MEDIUM and HARD assembly prediction. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

  6. Analysis of an optimal hidden Markov model for secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Gibrat Jean-François

    2006-12-01

    Full Text Available Abstract Background Secondary structure prediction is a useful first step toward 3D structure prediction. A number of successful secondary structure prediction methods use neural networks, but unfortunately, neural networks are not intuitively interpretable. On the contrary, hidden Markov models are graphical interpretable models. Moreover, they have been successfully used in many bioinformatic applications. Because they offer a strong statistical background and allow model interpretation, we propose a method based on hidden Markov models. Results Our HMM is designed without prior knowledge. It is chosen within a collection of models of increasing size, using statistical and accuracy criteria. The resulting model has 36 hidden states: 15 that model α-helices, 12 that model coil and 9 that model β-strands. Connections between hidden states and state emission probabilities reflect the organization of protein structures into secondary structure segments. We start by analyzing the model features and see how it offers a new vision of local structures. We then use it for secondary structure prediction. Our model appears to be very efficient on single sequences, with a Q3 score of 68.8%, more than one point above PSIPRED prediction on single sequences. A straightforward extension of the method allows the use of multiple sequence alignments, rising the Q3 score to 75.5%. Conclusion The hidden Markov model presented here achieves valuable prediction results using only a limited number of parameters. It provides an interpretable framework for protein secondary structure architecture. Furthermore, it can be used as a tool for generating protein sequences with a given secondary structure content.

  7. Structural properties of MHC class II ligands, implications for the prediction of MHC class II epitopes.

    Directory of Open Access Journals (Sweden)

    Kasper Winther Jørgensen

    Full Text Available Major Histocompatibility class II (MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100-200 peptides per allele to derive accurate description of their binding motif. Little work has been performed characterizing structural properties of MHC class II ligands. Here, we perform one such large-scale analysis. A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule.

  8. Conformational transitions upon ligand binding: holo-structure prediction from apo conformations.

    Directory of Open Access Journals (Sweden)

    Daniel Seeliger

    2010-01-01

    Full Text Available Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures, however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 A backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 A backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available.

  9. Structural features based genome-wide characterization and prediction of nucleosome organization

    Directory of Open Access Journals (Sweden)

    Gan Yanglan

    2012-03-01

    Full Text Available Abstract Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence

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

    Directory of Open Access Journals (Sweden)

    Yuan Zheng

    2009-10-01

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

  11. Structural features that predict real-value fluctuations of globular proteins.

    Science.gov (United States)

    Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

    2012-05-01

    It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

  12. Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

    Science.gov (United States)

    Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2016-08-07

    Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Model structural uncertainty quantification and hydrologic parameter and prediction error analysis using airborne electromagnetic data

    DEFF Research Database (Denmark)

    Minsley, B. J.; Christensen, Nikolaj Kruse; Christensen, Steen

    is never perfectly known, however, and incorrect assumptions can be a significant source of error when making model predictions. We describe a systematic approach for quantifying model structural uncertainty that is based on the integration of sparse borehole observations and large-scale airborne...... indicator simulation, we produce many realizations of model structure that are consistent with observed datasets and prior knowledge. Given estimates of model structural uncertainty, we incorporate hydrologic observations to evaluate the errors in hydrologic parameter or prediction errors that occur when...

  14. Synconset waves and chains: spiking onsets in synchronous populations predict and are predicted by network structure.

    Directory of Open Access Journals (Sweden)

    Mohan Raghavan

    Full Text Available Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define 'synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in 'synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest

  15. FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition.

    Science.gov (United States)

    Wang, Chao; Zhang, Haicang; Zheng, Wei-Mou; Xu, Dong; Zhu, Jianwei; Wang, Bing; Ning, Kang; Sun, Shiwei; Li, Shuai Cheng; Bu, Dongbo

    2016-02-01

    The protein structure prediction approaches can be categorized into template-based modeling (including homology modeling and threading) and free modeling. However, the existing threading tools perform poorly on remote homologous proteins. Thus, improving fold recognition for remote homologous proteins remains a challenge. Besides, the proteome-wide structure prediction poses another challenge of increasing prediction throughput. In this study, we presented FALCON@home as a protein structure prediction server focusing on remote homologue identification. The design of FALCON@home is based on the observation that a structural template, especially for remote homologous proteins, consists of conserved regions interweaved with highly variable regions. The highly variable regions lead to vague alignments in threading approaches. Thus, FALCON@home first extracts conserved regions from each template and then aligns a query protein with conserved regions only rather than the full-length template directly. This helps avoid the vague alignments rooted in highly variable regions, improving remote homologue identification. We implemented FALCON@home using the Berkeley Open Infrastructure of Network Computing (BOINC) volunteer computing protocol. With computation power donated from over 20,000 volunteer CPUs, FALCON@home shows a throughput as high as processing of over 1000 proteins per day. In the Critical Assessment of protein Structure Prediction (CASP11), the FALCON@home-based prediction was ranked the 12th in the template-based modeling category. As an application, the structures of 880 mouse mitochondria proteins were predicted, which revealed the significant correlation between protein half-lives and protein structural factors. FALCON@home is freely available at http://protein.ict.ac.cn/FALCON/. shuaicli@cityu.edu.hk, dbu@ict.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For

  16. STRUCTURAL SCALE LIFE PREDICTION OF AERO STRUCTURES EXPERIENCING COMBINED EXTREME ENVIRONMENTS

    Science.gov (United States)

    2017-07-01

    Using Complex Variables to Estimate the Derivatives of Nonlinear Reduced-Order Models,” AIAA-2016-1707, 57th AIAA/ ASME /ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, San Diego, CA, Jan 2016.

  17. Manual for the prediction of blast and fragment loadings on structures

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    The purpose of this manual is to provide Architect-Engineer (AE) firms guidance for the prediction of air blast, ground shock and fragment loadings on structures as a result of accidental explosions in or near these structures. Information in this manual is the result of an extensive literature survey and data gathering effort, supplemented by some original analytical studies on various aspects of blast phenomena. Many prediction equations and graphs are presented, accompanied by numerous example problems illustrating their use. The manual is complementary to existing structural design manuals and is intended to reflect the current state-of-the-art in prediction of blast and fragment loads for accidental explosions of high explosives at the Pantex Plant. In some instances, particularly for explosions within blast-resistant structures of complex geometry, rational estimation of these loads is beyond the current state-of-the-art.

  18. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures

    DEFF Research Database (Denmark)

    Andersen, P.H.; Nielsen, Morten; Lund, Ole

    2006-01-01

    .5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide......Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three....... We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15...

  19. Stereoinversion of tertiary alcohols to tertiary-alkyl isonitriles and amines.

    Science.gov (United States)

    Pronin, Sergey V; Reiher, Christopher A; Shenvi, Ryan A

    2013-09-12

    The SN2 reaction (bimolecular nucleophilic substitution) is a well-known chemical transformation that can be used to join two smaller molecules together into a larger molecule or to exchange one functional group for another. The SN2 reaction proceeds in a very predictable manner: substitution occurs with inversion of stereochemistry, resulting from the 'backside attack' of the electrophilic carbon by the nucleophile. A significant limitation of the SN2 reaction is its intolerance for tertiary carbon atoms: whereas primary and secondary alcohols are viable precursor substrates, tertiary alcohols and their derivatives usually either fail to react or produce stereochemical mixtures of products. Here we report the stereochemical inversion of chiral tertiary alcohols with a nitrogenous nucleophile facilitated by a Lewis-acid-catalysed solvolysis. The method is chemoselective against secondary and primary alcohols, thereby complementing the selectivity of the SN2 reaction. Furthermore, this method for carbon-nitrogen bond formation mimics a putative biosynthetic step in the synthesis of marine terpenoids and enables their preparation from the corresponding terrestrial terpenes. We expect that the general attributes of the methodology will allow chiral tertiary alcohols to be considered viable substrates for stereoinversion reactions.

  20. Crystal Structure Prediction could have helped the Experimentalists with Polymorphism in Benzamide!

    OpenAIRE

    2008-01-01

    Abstract Benzamide was the first molecular material for which polymorphism was reported as long as 176 years ago. Unfortunately, due to very similar cell metrics leading to massive peak overlap, the metastable form reported by Liebig escaped structural characterization by XRD until recently. With the help of crystal structure prediction this old riddle of ?Liebig's? polymorph of benzamide could have been solved many years earlier. Performing state of the art crystal structure predi...

  1. Exploring high-pressure FeB{sub 2}: Structural and electronic properties predictions

    Energy Technology Data Exchange (ETDEWEB)

    Harran, Ismail [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Al Fashir University (Sudan); Wang, Hongyan [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Chen, Yuanzheng, E-mail: cyz@calypso.org.cn [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Jia, Mingzhen [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Wu, Nannan [School of Mathematics, Physics and Biological Engineering, Inner Mongolia University of Science & Technology, Baotou, 014010 (China)

    2016-09-05

    The high pressure (HP) structural phase of FeB{sub 2} compound is investigated by using first-principles crystal structure prediction based on the CALYPSO technique. A thermodynamically stable phase of FeB{sub 2} with space group Imma is predicted at pressure above 225 GPa, which is characterized by a layered orthorhombic structure containing puckered graphite-like boron layers. Its electronic and mechanical properties are identified and analyzed. The feature of band structures favors the occurrence of superconductivity, whereas, the calculated Pugh's ratio reveals that the HP Imma structure exhibits ductile mechanical property. - Highlights: • The high pressure structural phase of FeB{sub 2} compound is firstly investigated by the CALYPSO technique. • A thermodynamically stable Imma phase of FeB{sub 2} is predicted at pressure above 225 GPa. • The Imma structure is characterized by a 2D boron network containing puckered graphite-like boron layers. • The band feature of Imma structure favors the occurrence of superconductivity. • The calculated Pugh's ratio suggests that the Imma structure exhibits ductile mechanical property.

  2. CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

    Science.gov (United States)

    Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

    2013-01-01

    We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

  3. Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

    Science.gov (United States)

    Jadaan, Osama M.; Powers, Lynn M.; Gyekenyesi, John P.

    1998-01-01

    High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and

  4. FlexStem: improving predictions of RNA secondary structures with pseudoknots by reducing the search space.

    Science.gov (United States)

    Chen, Xiang; He, Si-Min; Bu, Dongbo; Zhang, Fa; Wang, Zhiyong; Chen, Runsheng; Gao, Wen

    2008-09-15

    RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is proved to be NP-hard. Due to kinetic reasons the real RNA secondary structure often has local instead of global minimum free energy. This implies that we may improve the performance of RNA secondary structure prediction by taking kinetics into account and minimize free energy in a local area. we propose a novel algorithm named FlexStem to predict RNA secondary structures with pseudoknots. Still based on MFE criterion, FlexStem adopts comprehensive energy models that allow complex pseudoknots. Unlike classical thermodynamic methods, our approach aims to simulate the RNA folding process by successive addition of maximal stems, reducing the search space while maintaining or even improving the prediction accuracy. This reduced space is constructed by our maximal stem strategy and stem-adding rule induced from elaborate statistical experiments on real RNA secondary structures. The strategy and the rule also reflect the folding characteristic of RNA from a new angle and help compensate for the deficiency of merely relying on MFE in RNA structure prediction. We validate FlexStem by applying it to tRNAs, 5SrRNAs and a large number of pseudoknotted structures and compare it with the well-known algorithms such as RNAfold, PKNOTS, PknotsRG, HotKnots and ILM according to their overall sensitivities and specificities, as well as positive and negative controls on pseudoknots. The results show that FlexStem significantly increases the prediction accuracy through its local search strategy. Software is available at http://pfind.ict.ac.cn/FlexStem/. Supplementary data are available at Bioinformatics online.

  5. Toward a structure determination method for biomineral-associated protein using combined solid- state NMR and computational structure prediction.

    Science.gov (United States)

    Masica, David L; Ash, Jason T; Ndao, Moise; Drobny, Gary P; Gray, Jeffrey J

    2010-12-08

    Protein-biomineral interactions are paramount to materials production in biology, including the mineral phase of hard tissue. Unfortunately, the structure of biomineral-associated proteins cannot be determined by X-ray crystallography or solution nuclear magnetic resonance (NMR). Here we report a method for determining the structure of biomineral-associated proteins. The method combines solid-state NMR (ssNMR) and ssNMR-biased computational structure prediction. In addition, the algorithm is able to identify lattice geometries most compatible with ssNMR constraints, representing a quantitative, novel method for investigating crystal-face binding specificity. We use this method to determine most of the structure of human salivary statherin interacting with the mineral phase of tooth enamel. Computation and experiment converge on an ensemble of related structures and identify preferential binding at three crystal surfaces. The work represents a significant advance toward determining structure of biomineral-adsorbed protein using experimentally biased structure prediction. This method is generally applicable to proteins that can be chemically synthesized. Copyright © 2010 Elsevier Ltd. All rights reserved.

  6. Decisive role of structure in food microbial colonization and implications for predictive microbiology.

    Science.gov (United States)

    Noriega, E; Laca, A; Díaz, M

    2010-05-01

    Predictive models must consider the significant effect of the physical structure of the food on the magnitude and type of microbial growth. Before such models are developed, a thorough characterization of the food structure is mandatory because this information will determine the modeling approach. In this work, several physical structures common in poultry products were classified and described. Chicken breast skin and flesh and minced breasts were examined by scanning electron microscopy and compared with a meat-based model food. Such systems were surface or internally inoculated with Listeria innocua and incubated at 25 degrees C for 24 h. Different structures, including several substructures, found in the studied systems affected microbial distribution and growth. Based on these experimental findings, the most suitable type of model for each physical structure was determined. This information provides further clarification for predictive microbiology models.

  7. RNA 3D modules in genome-wide predictions of RNA 2D structure

    DEFF Research Database (Denmark)

    Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

    2015-01-01

    Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution....... These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D...

  8. Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins

    Directory of Open Access Journals (Sweden)

    Swapna Lakshmipuram S

    2012-05-01

    Full Text Available Abstract Background Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question “What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?” Results A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex. Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in

  9. MCTBI: a web server for predicting metal ion effects in RNA structures.

    Science.gov (United States)

    Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

    2017-08-01

    Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  10. Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11.

    Science.gov (United States)

    Zhang, Wenxuan; Yang, Jianyi; He, Baoji; Walker, Sara Elizabeth; Zhang, Hongjiu; Govindarajoo, Brandon; Virtanen, Jouko; Xue, Zhidong; Shen, Hong-Bin; Zhang, Yang

    2016-09-01

    We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score = 0.736 and RMSD = 2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made. Proteins 2016; 84(Suppl 1):76-86. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  11. A benchmark server using high resolution protein structure data, and benchmark results for membrane helix predictions.

    Science.gov (United States)

    Rath, Emma M; Tessier, Dominique; Campbell, Alexander A; Lee, Hong Ching; Werner, Tim; Salam, Noeris K; Lee, Lawrence K; Church, W Bret

    2013-03-27

    Helical membrane proteins are vital for the interaction of cells with their environment. Predicting the location of membrane helices in protein amino acid sequences provides substantial understanding of their structure and function and identifies membrane proteins in sequenced genomes. Currently there is no comprehensive benchmark tool for evaluating prediction methods, and there is no publication comparing all available prediction tools. Current benchmark literature is outdated, as recently determined membrane protein structures are not included. Current literature is also limited to global assessments, as specialised benchmarks for predicting specific classes of membrane proteins were not previously carried out. We present a benchmark server at http://sydney.edu.au/pharmacy/sbio/software/TMH_benchmark.shtml that uses recent high resolution protein structural data to provide a comprehensive assessment of the accuracy of existing membrane helix prediction methods. The server further allows a user to compare uploaded predictions generated by novel methods, permitting the comparison of these novel methods against all existing methods compared by the server. Benchmark metrics include sensitivity and specificity of predictions for membrane helix location and orientation, and many others. The server allows for customised evaluations such as assessing prediction method performances for specific helical membrane protein subtypes.We report results for custom benchmarks which illustrate how the server may be used for specialised benchmarks. Which prediction method is the best performing method depends on which measure is being benchmarked. The OCTOPUS membrane helix prediction method is consistently one of the highest performing methods across all measures in the benchmarks that we performed. The benchmark server allows general and specialised assessment of existing and novel membrane helix prediction methods. Users can employ this benchmark server to determine the most

  12. NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure.

    Science.gov (United States)

    Turner, Douglas H; Mathews, David H

    2010-01-01

    The Nearest Neighbor Database (NNDB, http://rna.urmc.rochester.edu/NNDB) is a web-based resource for disseminating parameter sets for predicting nucleic acid secondary structure stabilities. For each set of parameters, the database includes the set of rules with descriptive text, sequence-dependent parameters in plain text and html, literature references to experiments and usage tutorials. The initial release covers parameters for predicting RNA folding free energy and enthalpy changes.

  13. NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure

    OpenAIRE

    Turner, Douglas H.; David H Mathews

    2009-01-01

    The Nearest Neighbor Database (NNDB, http://rna.urmc.rochester.edu/NNDB) is a web-based resource for disseminating parameter sets for predicting nucleic acid secondary structure stabilities. For each set of parameters, the database includes the set of rules with descriptive text, sequence-dependent parameters in plain text and html, literature references to experiments and usage tutorials. The initial release covers parameters for predicting RNA folding free energy and enthalpy changes.

  14. Seismic prediction and imaging of geological structures ahead of a tunnel using surface waves

    OpenAIRE

    Jetschny, Stefan

    2010-01-01

    To improve the performance and safety of tunnel constructions, we introduce a new seismic prediction method utilizing tunnel surface waves to detect relevant geological structures ahead of the tunnel face. On the basis of both synthetic and field data, we investigate the propagation characteristics of such surface waves propagating along the tunnel wall. We further introduce a simple but robust automatic prediction scheme that can estimate the distance to a reflector ahead of the tunnel.

  15. Crystal Structure of Mouse Thymidylate Synthase in Tertiary Complex with dUMP and Raltitrexed Reveals N-Terminus Architecture and Two Different Active Site Conformations

    Directory of Open Access Journals (Sweden)

    Anna Dowierciał

    2014-01-01

    Full Text Available The crystal structure of mouse thymidylate synthase (mTS in complex with substrate dUMP and antifolate inhibitor Raltitrexed is reported. The structure reveals, for the first time in the group of mammalian TS structures, a well-ordered segment of 13 N-terminal amino acids, whose ordered conformation is stabilized due to specific crystal packing. The structure consists of two homodimers, differing in conformation, one being more closed (dimer AB and thus supporting tighter binding of ligands, and the other being more open (dimer CD and thus allowing weaker binding of ligands. This difference indicates an asymmetrical effect of the binding of Raltitrexed to two independent mTS molecules. Conformational changes leading to a ligand-induced closing of the active site cleft are observed by comparing the crystal structures of mTS in three different states along the catalytic pathway: ligand-free, dUMP-bound, and dUMP- and Raltitrexed-bound. Possible interaction routes between hydrophobic residues of the mTS protein N-terminal segment and the active site are also discussed.

  16. Crystal structure of mouse thymidylate synthase in tertiary complex with dUMP and raltitrexed reveals N-terminus architecture and two different active site conformations.

    Science.gov (United States)

    Dowierciał, Anna; Wilk, Piotr; Rypniewski, Wojciech; Rode, Wojciech; Jarmuła, Adam

    2014-01-01

    The crystal structure of mouse thymidylate synthase (mTS) in complex with substrate dUMP and antifolate inhibitor Raltitrexed is reported. The structure reveals, for the first time in the group of mammalian TS structures, a well-ordered segment of 13 N-terminal amino acids, whose ordered conformation is stabilized due to specific crystal packing. The structure consists of two homodimers, differing in conformation, one being more closed (dimer AB) and thus supporting tighter binding of ligands, and the other being more open (dimer CD) and thus allowing weaker binding of ligands. This difference indicates an asymmetrical effect of the binding of Raltitrexed to two independent mTS molecules. Conformational changes leading to a ligand-induced closing of the active site cleft are observed by comparing the crystal structures of mTS in three different states along the catalytic pathway: ligand-free, dUMP-bound, and dUMP- and Raltitrexed-bound. Possible interaction routes between hydrophobic residues of the mTS protein N-terminal segment and the active site are also discussed.

  17. Gelification of Victorian Tertiary soft brown coal wood. II. Changes in chemical structure associated with variation in the degree of gelification

    Energy Technology Data Exchange (ETDEWEB)

    Russell, N.J.; Barron, P.F.

    1984-09-01

    The gross chemical structures of xylites and gelified soft brown coal woods, Latrobe Valley, Victoria, Australia, as determined by solid state nuclear magnetic resonance spectroscopy, are compared with those of present-day wood-derived materials prepared from an angiosperm, Eucalyptus regnans, and a gymnosperm (conifer), Pinus radiata. Also examined are the changes in the gross chemical structures of soft brown coal woods with increase in their degree of gelification and the relationship between these changes and variations in their chemical composition and microscopic appearance. The Victorian xylites exhibit greater affinities with the present-day gymnosperm than the present-day angiosperm. The progressive removal of cellulose with increasing degree of gelification can be equated with an increase in huminite reflectance, elimination of humotelinite autofluoresence and changes in the relative proportions of the humotelinite submacerals. The lignin structure of xylite is also modified during the gelification process, including the progressive loss of methoxyl groups and evidence of minor oxidation.

  18. PETcofold: predicting conserved interactions and structures of two multiple alignments of RNA sequences.

    Science.gov (United States)

    Seemann, Stefan E; Richter, Andreas S; Gesell, Tanja; Backofen, Rolf; Gorodkin, Jan

    2011-01-15

    Predicting RNA-RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA-RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA-RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences. PETcofold's ability to predict RNA-RNA interactions was evaluated on a carefully curated dataset of 32 bacterial small RNAs and their targets, which was manually extracted from the literature. For evaluation of both RNA-RNA interaction and structure prediction, we were able to extract only a few high-quality examples: one vertebrate small nucleolar RNA and four bacterial small RNAs. For these we show that the prediction can be improved by our comparative approach. Furthermore, PETcofold was evaluated on controlled data with phylogenetically simulated sequences enriched for covariance patterns at the interaction sites. We observed increased performance with increased amounts of covariance. The program PETcofold is available as source code and can be downloaded from http://rth.dk/resources/petcofold.

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

    Directory of Open Access Journals (Sweden)

    Vasconcelos Ana

    2008-11-01

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

  20. Who Has to Pay for Their Education? Evidence from European Tertiary Education

    Science.gov (United States)

    Lim, Gieyoung; Kim, Chong-Uk

    2013-01-01

    In this article, we investigate a positive tertiary education externality in 18 European countries. Using a simple Cobb-Douglas-type production function with constant returns to scale, we find that there are positive spillover effects from tertiary education in European countries. According to our model prediction, on average, 72,000 new employed…

  1. On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

    Science.gov (United States)

    Becker, Julien; Maes, Francis; Wehenkel, Louis

    2013-01-01

    Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix) together with the CSP (cysteine separation profile) are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to [Formula: see text

  2. Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

    Directory of Open Access Journals (Sweden)

    Borodovsky Mark

    2006-03-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

  3. On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

    Directory of Open Access Journals (Sweden)

    Julien Becker

    Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

  4. Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

    KAUST Repository

    Guturu, H.

    2013-11-11

    Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and \\'through-DNA\\' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

  5. ASTRO-FOLD 2.0: an Enhanced Framework for Protein Structure Prediction.

    Science.gov (United States)

    Subramani, A; Wei, Y; Floudas, C A

    2012-05-01

    The three-dimensional (3-D) structure prediction of proteins, given their amino acid sequence, is addressed using the first principles-based approach ASTRO-FOLD 2.0. The key features presented are: (1) Secondary structure prediction using a novel optimization-based consensus approach, (2) β-sheet topology prediction using mixed-integer linear optimization (MILP), (3) Residue-to-residue contact prediction using a high-resolution distance-dependent force field and MILP formulation, (4) Tight dihedral angle and distance bound generation for loop residues using dihedral angle clustering and non-linear optimization (NLP), (5) 3-D structure prediction using deterministic global optimization, stochastic conformational space annealing, and the full-atomistic ECEPP/3 potential, (6) Near-native structure selection using a traveling salesman problem-based clustering approach, ICON, and (7) Improved bound generation using chemical shifts of subsets of heavy atoms, generated by SPARTA and CS23D. Computational results of ASTRO-FOLD 2.0 on 47 blind targets of the recently concluded CASP9 experiment are presented.

  6. Towards Practical Carbonation Prediction and Modelling for Service Life Design of Reinforced Concrete Structures

    Science.gov (United States)

    Ekolu, O. S.

    2015-11-01

    Amongst the scientific community, the interest in durability of concrete structures has been high for quite a long time of over 40 years. Of the various causes of degradation of concrete structures, corrosion is the most widespread durability problem and carbonation is one of the two causes of steel reinforcement corrosion. While much scientific understanding has been gained from the numerous carbonation studies undertaken over the past years, it is still presently not possible to accurately predict carbonation and apply it in design of structures. This underscores the complex nature of the mechanisms as influenced by several interactive factors. Based on critical literature and some experience of the author, it is found that there still exist major challenges in establishing a mathematical constitutive relation for realistic carbonation prediction. While most current models employ permeability /diffusion as the main model property, analysis shows that the most practical material property would be compressive strength, which has a low coefficient of variation of 20% compared to 30 to 50% for permeability. This important characteristic of compressive strength, combined with its merit of simplicity and data availability at all stages of a structure's life, promote its potential use in modelling over permeability. By using compressive strength in carbonation prediction, the need for accelerated testing and permeability measurement can be avoided. This paper attempts to examine the issues associated with carbonation prediction, which could underlie the current lack of a sound established prediction method. Suggestions are then made for possible employment of different or alternative approaches.

  7. Fast computational methods for predicting protein structure from primary amino acid sequence

    Science.gov (United States)

    Agarwal, Pratul Kumar [Knoxville, TN

    2011-07-19

    The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.

  8. Computational Methods for Protein Structure Prediction and Modeling Volume 1: Basic Characterization

    CERN Document Server

    Xu, Ying; Liang, Jie

    2007-01-01

    Volume one of this two volume sequence focuses on the basic characterization of known protein structures as well as structure prediction from protein sequence information. The 11 chapters provide an overview of the field, covering key topics in modeling, force fields, classification, computational methods, and struture prediction. Each chapter is a self contained review designed to cover (1) definition of the problem and an historical perspective, (2) mathematical or computational formulation of the problem, (3) computational methods and algorithms, (4) performance results, (5) existing software packages, and (6) strengths, pitfalls, challenges, and future research directions.

  9. Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database.

    Science.gov (United States)

    Avdagic, Zikrija; Purisevic, Elvir; Omanovic, Samir; Coralic, Zlatan

    2009-03-01

    In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513.

  10. Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction.

    Science.gov (United States)

    Ferrari, T; Cattaneo, D; Gini, G; Golbamaki Bakhtyari, N; Manganaro, A; Benfenati, E

    2013-01-01

    This work proposes a new structure-activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence.

  11. Protein structure prediction using a docking-based hierarchical folding scheme.

    Science.gov (United States)

    Kifer, Ilona; Nussinov, Ruth; Wolfson, Haim J

    2011-06-01

    The pathways by which proteins fold into their specific native structure are still an unsolved mystery. Currently, many methods for protein structure prediction are available, and most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations toward each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method's abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the template-based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for template-based structure prediction, and in particular, the docking-basedranking technique presented here can be incorporated into any profile-profile comparison based method. Copyright © 2011 Wiley-Liss, Inc.

  12. Effect of Using Suboptimal Alignments in Template-Based Protein Structure Prediction

    Science.gov (United States)

    Chen, Hao; Kihara, Daisuke

    2010-01-01

    Computational protein structure prediction remains a challenging task in protein bioinformatics. In the recent years, the importance of template-based structure prediction is increasing due to the growing number of protein structures solved by the structural genomics projects. To capitalize the significant efforts and investments paid on the structural genomics projects, it is urgent to establish effective ways to use the solved structures as templates by developing methods for exploiting remotely related proteins that cannot be simply identified by homology. In this work, we examine the effect of employing suboptimal alignments in template-based protein structure prediction. We showed that suboptimal alignments are often more accurate than the optimal one, and such accurate suboptimal alignments can occur even at a very low rank of the alignment score. Suboptimal alignments contain a significant number of correct amino acid residue contacts. Moreover, suboptimal alignments can improve template-based models when used as input to Modeller. Finally, we employ suboptimal alignments for handling a contact potential in a probabilistic way in a threading program, SUPRB. The probabilistic contacts strategy outperforms the partly thawed approach which only uses the optimal alignment in defining residue contacts and also the reranking strategy, which uses the contact potential in reranking alignments. The comparison with existing methods in the template-recognition test shows that SUPRB is very competitive and outperform existing methods. PMID:21058297

  13. Protein structure prediction using residue- and fragment-environment potentials in CASP11.

    Science.gov (United States)

    Kim, Hyungrae; Kihara, Daisuke

    2016-09-01

    An accurate scoring function that can select near-native structure models from a pool of alternative models is key for successful protein structure prediction. For the critical assessment of techniques for protein structure prediction (CASP) 11, we have built a protocol of protein structure prediction that has novel coarse-grained scoring functions for selecting decoys as the heart of its pipeline. The score named PRESCO (Protein Residue Environment SCOre) developed recently by our group evaluates the native-likeness of local structural environment of residues in a structure decoy considering positions and the depth of side-chains of spatially neighboring residues. We also introduced a helix interaction potential as an additional scoring function for selecting decoys. The best models selected by PRESCO and the helix interaction potential underwent structure refinement, which includes side-chain modeling and relaxation with a short molecular dynamics simulation. Our protocol was successful, achieving the top rank in the free modeling category with a significant margin of the accumulated Z-score to the subsequent groups when the top 1 models were considered. Proteins 2016; 84(Suppl 1):105-117. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  14. Structure Prediction for Gland Segmentation with Hand-Crafted and Deep Convolutional Features.

    Science.gov (United States)

    Manivannan, Siyamalan; Li, Wenqi; Zhang, Jianguo; Trucco, Emanuele; McKenna, Stephen

    2017-09-08

    We present a novel method to segment instances of glandular structures from colon histopathology images. We use a structure learning approach which represents local spatial configurations of class labels, capturing structural information normally ignored by sliding-window methods. This allows us to reveal different spatial structures of pixel labels (e.g., locations between adjacent glands, or far from glands), and to identify correctly neighbouring glandular structures as separate instances. Exemplars of label structures are obtained via clustering and used to train support vector machine classifiers. The label structures predicted are then combined and post-processed to obtain segmentation maps. We combine hand-crafted, multi-scale image features with features computed by a deep convolutional network trained to map images to segmentation maps. We evaluate the proposed method on the public domain GlaS dataset, which allows extensive comparisons with recent, alternative methods. Using the GlaS contest protocol, our method achieves the overall best performance.

  15. LoopIng: a template-based tool for predicting the structure of protein loops.

    KAUST Repository

    Messih, Mario Abdel

    2015-08-06

    Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are not very effective in modeling their structure. However, loops are often involved in protein function, hence inferring their structure is important for predicting protein structure as well as function.We describe a method, LoopIng, based on the Random Forest automated learning technique, which, given a target loop, selects a structural template for it from a database of loop candidates. Compared to the most recently available methods, LoopIng is able to achieve similar accuracy for short loops (4-10 residues) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has the advantage of being very fast (on average: 1 min/loop).www.biocomputing.it/loopinganna.tramontano@uniroma1.itSupplementary data are available at Bioinformatics online.

  16. M3Ag17(SPh)12 Nanoparticles and Their Structure Prediction.

    Science.gov (United States)

    Wickramasinghe, Sameera; Atnagulov, Aydar; Yoon, Bokwon; Barnett, Robert N; Griffith, Wendell P; Landman, Uzi; Bigioni, Terry P

    2015-09-16

    Although silver nanoparticles are of great fundamental and practical interest, only one structure has been determined thus far: M4Ag44(SPh)30, where M is a monocation, and SPh is an aromatic thiolate ligand. This is in part due to the fact that no other molecular silver nanoparticles have been synthesized with aromatic thiolate ligands. Here we report the synthesis of M3Ag17(4-tert-butylbenzene-thiol)12, which has good stability and an unusual optical spectrum. We also present a rational strategy for predicting the structure of this molecule. First-principles calculations support the structural model, predict a HOMO-LUMO energy gap of 1.77 eV, and predict a new "monomer mount" capping motif, Ag(SR)3, for Ag nanoparticles. The calculated optical absorption spectrum is in good correspondence with the measured spectrum. Heteroatom substitution was also used as a structural probe. First-principles calculations based on the structural model predicted a strong preference for a single Au atom substitution in agreement with experiment.

  17. Predicting protein folding pathways at the mesoscopic level based on native interactions between secondary structure elements

    Directory of Open Access Journals (Sweden)

    Sze Sing-Hoi

    2008-07-01

    Full Text Available Abstract Background Since experimental determination of protein folding pathways remains difficult, computational techniques are often used to simulate protein folding. Most current techniques to predict protein folding pathways are computationally intensive and are suitable only for small proteins. Results By assuming that the native structure of a protein is known and representing each intermediate conformation as a collection of fully folded structures in which each of them contains a set of interacting secondary structure elements, we show that it is possible to significantly reduce the conformation space while still being able to predict the most energetically favorable folding pathway of large proteins with hundreds of residues at the mesoscopic level, including the pig muscle phosphoglycerate kinase with 416 residues. The model is detailed enough to distinguish between different folding pathways of structurally very similar proteins, including the streptococcal protein G and the peptostreptococcal protein L. The model is also able to recognize the differences between the folding pathways of protein G and its two structurally similar variants NuG1 and NuG2, which are even harder to distinguish. We show that this strategy can produce accurate predictions on many other proteins with experimentally determined intermediate folding states. Conclusion Our technique is efficient enough to predict folding pathways for both large and small proteins at the mesoscopic level. Such a strategy is often the only feasible choice for large proteins. A software program implementing this strategy (SSFold is available at http://faculty.cs.tamu.edu/shsze/ssfold.

  18. Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.

    Science.gov (United States)

    Redlich, Ronny; Opel, Nils; Grotegerd, Dominik; Dohm, Katharina; Zaremba, Dario; Bürger, Christian; Münker, Sandra; Mühlmann, Lisa; Wahl, Patricia; Heindel, Walter; Arolt, Volker; Alferink, Judith; Zwanzger, Peter; Zavorotnyy, Maxim; Kugel, Harald; Dannlowski, Udo

    2016-06-01

    Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified. To investigate whether certain factors identified by structural magnetic resonance imaging (MRI) techniques are able to predict ECT response. In this nonrandomized prospective study, gray matter structure was assessed twice at approximately 6 weeks apart using 3-T MRI and voxel-based morphometry. Patients were recruited through the inpatient service of the Department of Psychiatry, University of Muenster, from March 11, 2010, to March 27, 2015. Two patient groups with acute major depressive disorder were included. One group received an ECT series in addition to antidepressants (n = 24); a comparison sample was treated solely with antidepressants (n = 23). Both groups were compared with a sample of healthy control participants (n = 21). Binary pattern classification was used to predict ECT response by structural MRI that was performed before treatment. In addition, univariate analysis was conducted to predict reduction of the Hamilton Depression Rating Scale score by pretreatment gray matter volumes and to investigate ECT-related structural changes. One participant in the ECT sample was excluded from the analysis, leaving 67 participants (27 men and 40 women; mean [SD] age, 43.7 [10.6] years). The binary pattern classification yielded a successful prediction of ECT response, with accuracy rates of 78.3% (18 of 23 patients in the ECT sample) and sensitivity rates of 100% (13 of 13 who responded to ECT). Furthermore, a support vector regression yielded a significant prediction of relative reduction in the Hamilton Depression Rating Scale score. The principal findings of the univariate model indicated a positive association between pretreatment subgenual cingulate volume and individual ECT response (Montreal Neurological Institute [MNI] coordinates x = 8, y = 21, z = -18

  19. Tertiary classes–after Chern-Simons theory

    Indian Academy of Sciences (India)

    J.N. Iyer Institute of Mathematical Sciences Chennai, India

    2013-11-08

    Nov 8, 2013 ... Euler characteristic class. In early twentieth century, the notion of local product structure, i.e. fiber spaces and their generalizations appeared, in the study of topological spaces (with additional structures). J.N. Iyer. IMSc, Chennai. Tertiary classes–after Chern-Simons theory ...

  20. Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

    Science.gov (United States)

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna

    2014-12-01

    Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

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

    Science.gov (United States)

    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.

  2. Critical assessment of methods of protein structure prediction (CASP)-round IX

    KAUST Repository

    Moult, John

    2011-01-01

    This article is an introduction to the special issue of the journal PROTEINS, dedicated to the ninth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Methods for modeling protein structure continue to advance, although at a more modest pace than in the early CASP experiments. CASP developments of note are indications of improvement in model accuracy for some classes of target, an improved ability to choose the most accurate of a set of generated models, and evidence of improvement in accuracy for short "new fold" models. In addition, a new analysis of regions of models not derivable from the most obvious template structure has revealed better performance than expected.

  3. Predictive value of tender joints compared to synovitis for structural damage in rheumatoid arthritis

    Science.gov (United States)

    Cheung, Peter P; Mari, Karine; Devauchelle-Pensec, Valérie; Jousse-Joulin, Sandrine; D'Agostino, Maria Antonietta; Chalès, Gérard; Gaudin, Philippe; Mariette, Xavier; Saraux, Alain; Dougados, Maxime

    2016-01-01

    Objective To evaluate the predictive value of tender joints compared to synovitis for structural damage in rheumatoid arthritis (RA). Methods A post hoc analysis was performed on a prospective 2-year study of 59 patients with active RA starting on antitumour necrosis factor (TNF). Tenderness and synovitis was assessed clinically at baseline, followed by blinded ultrasound assessment (B-mode and power Doppler ultrasound (PDUS)) on the hands and feet (2 wrists, 10 metacarpophalangeal, 10 proximal interphalangeal and 10 metatarsophalangeal (MTP) joints). Radiographs of these joints were performed at baseline and at 2 years. The risk of radiographic progression with respect to the presence of baseline tenderness or synovitis, as well as its persistence (after 4 months of anti-TNF), was estimated by OR (95% CI). Results Baseline tender joints were the least predictive for radiographic progression (OR=1.53 (95% CI 1.02 to 2.29) pjoints with the presence of synovitis were predictive of radiographic progression (OR=1.89 (95% CI 1.25 to 2.85) p=0.002), especially seen in the MTP joints. Non-tender joints with no synovitis were negatively predictive (OR=0.57 (95% CI 0.39 to 0.82) p=0.003). Persistence of tender joints was negatively predictive (OR=0.38 (95% CI 0.18 to 0.78) p=0.009) while persistence of synovitis was predictive (OR=2.41 (95% CI 1.24 to 4.67) p=0.01) of radiographic progression. Conclusions Synovitis is better than tenderness to predict for subsequent structural progression. However, coexistence of tenderness and synovitis at the level of an individual joint is predictive of structural damage, particularly in the MTP joints. Trial registration number NCT00444691. PMID:27042336

  4. Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

    Science.gov (United States)

    Will, Sebastian; Jabbari, Hosna

    2016-01-01

    RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

  5. Predictive Measurement of the Structure of Land Use in an Urban Agglomeration Space

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2017-12-01

    Full Text Available The scientific measurement of land use in space is an essential task in urban agglomeration studies, and the fractal feature is one of the most powerful tools for describing the phenomenon of space. However, previous research on the fractal feature of land use has mostly been conducted in urban space, and examines the fractal feature of different land use types, respectively; thus, the measurement of the relationship between different land use types was not realized. Meanwhile, previous prediction methods used for spatial land use mostly relied on subjective abstraction of the evolution, theoretically, regardless of whether they were calibrated, so that complete coverage of all the mechanisms could not be guaranteed. Based on this, here, we treat the land use structure in urban agglomeration space as the research object, and attempt to establish a fractal measure method for the relationship between different land use types in the space of urban agglomeration. At the same time, we use the allometric relationship between “entirety” and “local” to establish an objective forecast model for the land use structure in urban agglomeration space based on gray prediction theory, to achieve a predictive measurement of the structure of land use in urban agglomeration space. Finally, this study applied the methods on the Beijing–Tianjin–Hebei urban agglomeration to analyze the evolution of the stability of the structure of land use and achieve predictive measurement of the structure of land use. The results of the case study show that the methods proposed in this study can obtain the measurement of the relationship between different land use types and the land use prediction that does not depend on the subjective exploration of the evolution law. Compared with the measurement methods that analyzed the fractal feature of different land types, respectively, and the prediction methods that rely on subjective choice, the methods presented in this

  6. Effect of ultrasonic processing on the changes in activity, aggregation and the secondary and tertiary structure of polyphenol oxidase in oriental sweet melon (Cucumis melo var. makuwa Makino).

    Science.gov (United States)

    Liu, Siyu; Liu, Yan; Huang, Xingjian; Yang, Wenjin; Hu, Wanfeng; Pan, Siyi

    2017-03-01

    Polyphenol oxidase (PPO) mainly contributes to the browning reaction of fruits and vegetables and causes serious damage to the quality of sweet melon products. However, traditional methods to inactivate browning may induce more unexpected risks than ultrasonic processing. Meanwhile, there are no reports on the effect of ultrasound on PPO directly purified from sweet melon. The PPO in the original juice was less inactivated than the purified form when treated with ultrasound. As for purified PPO, superior to thermal treatment, less heat was needed to inactivate the PPO with ultrasonic treatment. At intensity lower than 200 W, ultrasound did not significantly affect the structure and activity of PPO (P > 0.05), and latent PPO was activated. At intensity higher than 200 W, ultrasound inactivated PPO, induced aggregation and dissociation of PPO particles and significantly decreased the α-helix structure content. Low-frequency high-intensity ultrasound caused an inactivation effect and conformational changes of purified PPO from oriental sweet melons. Changes in the PPO structure induced by ultrasound eventually inactivated the enzyme. Ultrasound may be a potential method to inactivate PPO in oriental sweet melons. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  7. Inactivation, aggregation, secondary and tertiary structural changes of germin-like protein in Satsuma mandarine with high polyphenol oxidase activity induced by ultrasonic processing.

    Science.gov (United States)

    Huang, Nana; Cheng, Xi; Hu, Wanfeng; Pan, Siyi

    2015-02-01

    The inhibition of Polyphenol oxidase (PPO) in plants has been widely researched for their important roles in browning reaction. A newly found germin-like protein (GLP) with high PPO activity in Satsuma mandarine was inactivated by low-frequency high-intensity ultrasonic (20 kHz) processing. The effects of ultrasound on PPO activity and structure of GLP were investigated using dynamic light scattering (DLS) analysis, transmission electron microscopy (TEM), circular dichroism (CD) spectral measurement and fluorescence spectral measurement. The lowest PPO activity achieved was 27.4% following ultrasonication for 30 min at 400 W. DLS analysis showed ultrasound caused both aggregation and dissociation of GLP particles. TEM images also demonstrated protein aggregation phenomena. CD spectra exhibited a certain number of loss in α-helix structure content. Fluorescence spectra showed remarkable increase in fluorescence intensity with tiny blue-shift following ultrasonication. In conclusion, ultrasound applied in this study induced structural changes of GLP and eventually inactivated PPO activity. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Development of a criterion for predicting residual strength of composite structures damaged by impact loading

    OpenAIRE

    Ricardo de Medeiros

    2016-01-01

    Advanced aerospace materials, including fibre reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging not only the current damage prediction, detection, and quantification methodologies, but also the residual life of the structure. The main objective of this work consists of developing theoretical and experimental studies about residual strength for composite structures, which are damaged by impact loading, aided by a S...

  9. Predicting Future Deterioration of Hydraulic Steel Structures with Markov Chain and Multivariate Samples of Statistical Distributions

    OpenAIRE

    Riveros, Guillermo A.; Elias Arredondo

    2014-01-01

    Combined effects of several complex phenomena cause the deterioration of elements of steel hydraulic structures on the nation’s lock systems: loss of protective systems, corrosion, cracking and fatigue, impacts, and overloads. This paper presents examples of deterioration of steel hydraulic structures. A method for predicting future deterioration based on current conditions is also presented. This paper also includes a procedure for developing deterioration curves when condition state data is...

  10. Predicting Future Deterioration of Hydraulic Steel Structures with Markov Chain and Multivariate Samples of Statistical Distributions

    Directory of Open Access Journals (Sweden)

    Guillermo A. Riveros

    2014-01-01

    Full Text Available Combined effects of several complex phenomena cause the deterioration of elements of steel hydraulic structures on the nation’s lock systems: loss of protective systems, corrosion, cracking and fatigue, impacts, and overloads. This paper presents examples of deterioration of steel hydraulic structures. A method for predicting future deterioration based on current conditions is also presented. This paper also includes a procedure for developing deterioration curves when condition state data is available.

  11. Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

    Science.gov (United States)

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

    2013-01-01

    The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences. PMID:23935998

  12. Predictors of Attrition and Achievement in a Tertiary Bridging Program

    Science.gov (United States)

    Whannell, Robert

    2013-01-01

    This study examines the attrition and achievement of a sample of 295 students in an on-campus tertiary bridging program at a regional university. A logistic regression analysis using enrolment status, age and the number of absences from scheduled classes at week three of the semester as predictor variables correctly predicted 92.8 percent of…

  13. Management of necrotizing enterocolitis: experience at a tertiary ...

    African Journals Online (AJOL)

    The aim of this study was to determine the incidence of NEC and identify the factors predicting the surgical management and also to determine the mortality due to NEC at our tertiary care neonatal unit in Oman. Materials and methods The parameters studied included sex-based differences, gestational age at birth, birth ...

  14. Management of necrotizing enterocolitis: experience at a tertiary ...

    African Journals Online (AJOL)

    Introduction Necrotizing enterocolitis (NEC) is the most common surgical emergency in the neonatal intensive care unit. The aim of this study was to determine the incidence of NEC and identify the factors predicting the surgical management and also to determine the mortality due to. NEC at our tertiary care neonatal unit in ...

  15. De novo structure prediction of globular proteins aided by sequence variation-derived contacts.

    Directory of Open Access Journals (Sweden)

    Tomasz Kosciolek

    Full Text Available The advent of high accuracy residue-residue intra-protein contact prediction methods enabled a significant boost in the quality of de novo structure predictions. Here, we investigate the potential benefits of combining a well-established fragment-based folding algorithm--FRAGFOLD, with PSICOV, a contact prediction method which uses sparse inverse covariance estimation to identify co-varying sites in multiple sequence alignments. Using a comprehensive set of 150 diverse globular target proteins, up to 266 amino acids in length, we are able to address the effectiveness and some limitations of such approaches to globular proteins in practice. Overall we find that using fragment assembly with both statistical potentials and predicted contacts is significantly better than either statistical potentials or contacts alone. Results show up to nearly 80% of correct predictions (TM-score ≥0.5 within analysed dataset and a mean TM-score of 0.54. Unsuccessful modelling cases emerged either from conformational sampling problems, or insufficient contact prediction accuracy. Nevertheless, a strong dependency of the quality of final models on the fraction of satisfied predicted long-range contacts was observed. This not only highlights the importance of these contacts on determining the protein fold, but also (combined with other ensemble-derived qualities provides a powerful guide as to the choice of correct models and the global quality of the selected model. A proposed quality assessment scoring function achieves 0.93 precision and 0.77 recall for the discrimination of correct folds on our dataset of decoys. These findings suggest the approach is well-suited for blind predictions on a variety of globular proteins of unknown 3D structure, provided that enough homologous sequences are available to construct a large and accurate multiple sequence alignment for the initial contact prediction step.

  16. GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure.

    Science.gov (United States)

    Baek, Minkyung; Park, Taeyong; Heo, Lim; Park, Chiwook; Seok, Chaok

    2017-04-06

    Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. Prediction of protein secondary structure using probability based features and a hybrid system.

    Science.gov (United States)

    Ghanty, Pradip; Pal, Nikhil R; Mudi, Rajani K

    2013-10-01

    In this paper, we propose some co-occurrence probability-based features for prediction of protein secondary structure. The features are extracted using occurrence/nonoccurrence of secondary structures in the protein sequences. We explore two types of features: position-specific (based on position of amino acid on fragments of protein sequences) as well as position-independent (independent of amino acid position on fragments of protein sequences). We use a hybrid system, NEUROSVM, consisting of neural networks and support vector machines for classification of secondary structures. We propose two schemes NSVMps and NSVM for protein secondary structure prediction. The NSVMps uses position-specific probability-based features and NEUROSVM classifier whereas NSVM uses the same classifier with position-independent probability-based features. The proposed method falls in the single-sequence category of methods because it does not use any sequence profile information such as position specific scoring matrices (PSSM) derived from PSI-BLAST. Two widely used datasets RS126 and CB513 are used in the experiments. The results obtained using the proposed features and NEUROSVM classifier are better than most of the existing single-sequence prediction methods. Most importantly, the results using NSVMps that are obtained using lower dimensional features, are comparable to those by other existing methods. The NSVMps and NSVM are finally tested on target proteins of the critical assessment of protein structure prediction experiment-9 (CASP9). A larger dataset is used to compare the performance of the proposed methods with that of two recent single-sequence prediction methods. We also investigate the impact of presence of different amino acid residues (in protein sequences) that are responsible for the formation of different secondary structures.

  18. Critical assessment of methods of protein structure prediction (CASP) - round x

    KAUST Repository

    Moult, John

    2013-12-17

    This article is an introduction to the special issue of the journal PROTEINS, dedicated to the tenth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. The 10 CASP experiments span almost 20 years of progress in the field of protein structure modeling, and there have been enormous advances in methods and model accuracy in that period. Notable in this round is the first sustained improvement of models with refinement methods, using molecular dynamics. For the first time, we tested the ability of modeling methods to make use of sparse experimental three-dimensional contact information, such as may be obtained from new experimental techniques, with encouraging results. On the other hand, new contact prediction methods, though holding considerable promise, have yet to make an impact in CASP testing. The nature of CASP targets has been changing in recent CASPs, reflecting shifts in experimental structural biology, with more irregular structures, more multi-domain and multi-subunit structures, and less standard versions of known folds. When allowance is made for these factors, we continue to see steady progress in the overall accuracy of models, particularly resulting from improvement of non-template regions.

  19. External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics.

    Science.gov (United States)

    Devillers, J; Pandard, P; Richard, B

    2013-01-01

    Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.

  20. Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

    Science.gov (United States)

    Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

    2017-05-01

    Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  1. Differential effects of CSF-1R D802V and KIT D816V homologous mutations on receptor tertiary structure and allosteric communication.

    Directory of Open Access Journals (Sweden)

    Priscila Da Silva Figueiredo Celestino Gomes

    Full Text Available The colony stimulating factor-1 receptor (CSF-1R and the stem cell factor receptor KIT, type III receptor tyrosine kinases (RTKs, are important mediators of signal transduction. The normal functions of these receptors can be compromised by gain-of-function mutations associated with different physiopatological impacts. Whereas KIT D816V/H mutation is a well-characterized oncogenic event and principal cause of systemic mastocytosis, the homologous CSF-1R D802V has not been identified in human cancers. The KIT D816V oncogenic mutation triggers resistance to the RTK inhibitor Imatinib used as first line treatment against chronic myeloid leukemia and gastrointestinal tumors. CSF-1R is also sensitive to Imatinib and this sensitivity is altered by mutation D802V. Previous in silico characterization of the D816V mutation in KIT evidenced that the mutation caused a structure reorganization of the juxtamembrane region (JMR and facilitated its departure from the kinase domain (KD. In this study, we showed that the equivalent CSF-1R D802V mutation does not promote such structural effects on the JMR despite of a reduction on some key H-bonds interactions controlling the JMR binding to the KD. In addition, this mutation disrupts the allosteric communication between two essential regulatory fragments of the receptors, the JMR and the A-loop. Nevertheless, the mutation-induced shift towards an active conformation observed in KIT D816V is not observed in CSF-1R D802V. The distinct impact of equivalent mutation in two homologous RTKs could be associated with the sequence difference between both receptors in the native form, particularly in the JMR region. A local mutation-induced perturbation on the A-loop structure observed in both receptors indicates the stabilization of an inactive non-inhibited form, which Imatinib cannot bind.

  2. Differential effects of CSF-1R D802V and KIT D816V homologous mutations on receptor tertiary structure and allosteric communication.

    Science.gov (United States)

    Da Silva Figueiredo Celestino Gomes, Priscila; Panel, Nicolas; Laine, Elodie; Pascutti, Pedro Geraldo; Solary, Eric; Tchertanov, Luba

    2014-01-01

    The colony stimulating factor-1 receptor (CSF-1R) and the stem cell factor receptor KIT, type III receptor tyrosine kinases (RTKs), are important mediators of signal transduction. The normal functions of these receptors can be compromised by gain-of-function mutations associated with different physiopatological impacts. Whereas KIT D816V/H mutation is a well-characterized oncogenic event and principal cause of systemic mastocytosis, the homologous CSF-1R D802V has not been identified in human cancers. The KIT D816V oncogenic mutation triggers resistance to the RTK inhibitor Imatinib used as first line treatment against chronic myeloid leukemia and gastrointestinal tumors. CSF-1R is also sensitive to Imatinib and this sensitivity is altered by mutation D802V. Previous in silico characterization of the D816V mutation in KIT evidenced that the mutation caused a structure reorganization of the juxtamembrane region (JMR) and facilitated its departure from the kinase domain (KD). In this study, we showed that the equivalent CSF-1R D802V mutation does not promote such structural effects on the JMR despite of a reduction on some key H-bonds interactions controlling the JMR binding to the KD. In addition, this mutation disrupts the allosteric communication between two essential regulatory fragments of the receptors, the JMR and the A-loop. Nevertheless, the mutation-induced shift towards an active conformation observed in KIT D816V is not observed in CSF-1R D802V. The distinct impact of equivalent mutation in two homologous RTKs could be associated with the sequence difference between both receptors in the native form, particularly in the JMR region. A local mutation-induced perturbation on the A-loop structure observed in both receptors indicates the stabilization of an inactive non-inhibited form, which Imatinib cannot bind.

  3. MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

    Science.gov (United States)

    Yin, Xi; Yang, Jing; Xiao, Feng; Yang, Yang; Shen, Hong-Bin

    2018-03-01

    Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue-residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A TMH, 87.1% of A P, 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. [Figure not available: see fulltext.

  4. Predicting community structure in snakes on Eastern Nearctic islands using ecological neutral theory and phylogenetic methods.

    Science.gov (United States)

    Burbrink, Frank T; McKelvy, Alexander D; Pyron, R Alexander; Myers, Edward A

    2015-11-22

    Predicting species presence and richness on islands is important for understanding the origins of communities and how likely it is that species will disperse and resist extinction. The equilibrium theory of island biogeography (ETIB) and, as a simple model of sampling abundances, the unified neutral theory of biodiversity (UNTB), predict that in situations where mainland to island migration is high, species-abundance relationships explain the presence of taxa on islands. Thus, more abundant mainland species should have a higher probability of occurring on adjacent islands. In contrast to UNTB, if certain groups have traits that permit them to disperse to islands better than other taxa, then phylogeny may be more predictive of which taxa will occur on islands. Taking surveys of 54 island snake communities in the Eastern Nearctic along with mainland communities that have abundance data for each species, we use phylogenetic assembly methods and UNTB estimates to predict island communities. Species richness is predicted by island area, whereas turnover from the mainland to island communities is random with respect to phylogeny. Community structure appears to be ecologically neutral and abundance on the mainland is the best predictor of presence on islands. With regard to young and proximate islands, where allopatric or cladogenetic speciation is not a factor, we find that simple neutral models following UNTB and ETIB predict the structure of island communities. © 2015 The Author(s).

  5. Structure- and sequence-based function prediction for non-homologous proteins.

    Science.gov (United States)

    Sael, Lee; Chitale, Meghana; Kihara, Daisuke

    2012-06-01

    The structural genomics projects have been accumulating an increasing number of protein structures, many of which remain functionally unknown. In parallel effort to experimental methods, computational methods are expected to make a significant contribution for functional elucidation of such proteins. However, conventional computational methods that transfer functions from homologous proteins do not help much for these uncharacterized protein structures because they do not have apparent structural or sequence similarity with the known proteins. Here, we briefly review two avenues of computational function prediction methods, i.e. structure-based methods and sequence-based methods. The focus is on our recent developments of local structure-based and sequence-based methods, which can effectively extract function information from distantly related proteins. Two structure-based methods, Pocket-Surfer and Patch-Surfer, identify similar known ligand binding sites for pocket regions in a query protein without using global protein fold similarity information. Two sequence-based methods, protein function prediction and extended similarity group, make use of weakly similar sequences that are conventionally discarded in homology based function annotation. Combined together with experimental methods we hope that computational methods will make leading contribution in functional elucidation of the protein structures.

  6. Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

    Science.gov (United States)

    Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

    2017-04-12

    Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

  7. Prediction of protein structural features by use of artificial neural networks

    DEFF Research Database (Denmark)

    Petersen, Bent

    . There is a huge over-representation of DNA sequences when comparing the amount of experimentally verified proteins with the amount of DNA sequences. The academic and industrial research community therefore has to rely on structure predictions instead of waiting for the time consuming experimentally determined...

  8. Bioinformatical approaches to RNA structure prediction & Sequencing of an ancient human genome

    DEFF Research Database (Denmark)

    Lindgreen, Stinus

    Stinus Lindgreen has been working in two different fields during his Ph.D. The first part has been focused on computational approaches to predict the structure of non-coding RNA molecules at the base pairing level. This has resulted in the analysis of various measures of the base pairing potentia...

  9. Relative Packing Groups in Template-Based Structure Prediction: Cooperative Effects of True Positive Constraints

    Science.gov (United States)

    Day, Ryan; Qu, Xiaotao; Swanson, Rosemarie; Bohannan, Zach; Bliss, Robert

    2011-01-01

    Abstract Most current template-based structure prediction methods concentrate on finding the correct backbone conformation and then packing sidechains within that backbone. Our packing-based method derives distance constraints from conserved relative packing groups (RPGs). In our refinement approach, the RPGs provide a level of resolution that restrains global topology while allowing conformational sampling. In this study, we test our template-based structure prediction method using 51 prediction units from CASP7 experiments. RPG-based constraints are able to substantially improve approximately two-thirds of starting templates. Upon deeper investigation, we find that true positive spatial constraints, especially those non-local in sequence, derived from the RPGs were important to building nearer native models. Surprisingly, the fraction of incorrect or false positive constraints does not strongly influence the quality of the final candidate. This result indicates that our RPG-based true positive constraints sample the self-consistent, cooperative interactions of the native structure. The lack of such reinforcing cooperativity explains the weaker effect of false positive constraints. Generally, these findings are encouraging indications that RPGs will improve template-based structure prediction. PMID:21210729