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Sample records for protein model selection

  1. NEW MDS AND CLUSTERING BASED ALGORITHMS FOR PROTEIN MODEL QUALITY ASSESSMENT AND SELECTION.

    PubMed

    Wang, Qingguo; Shang, Charles; Xu, Dong; Shang, Yi

    2013-10-25

    In protein tertiary structure prediction, assessing the quality of predicted models is an essential task. Over the past years, many methods have been proposed for the protein model quality assessment (QA) and selection problem. Despite significant advances, the discerning power of current methods is still unsatisfactory. In this paper, we propose two new algorithms, CC-Select and MDS-QA, based on multidimensional scaling and k-means clustering. For the model selection problem, CC-Select combines consensus with clustering techniques to select the best models from a given pool. Given a set of predicted models, CC-Select first calculates a consensus score for each structure based on its average pairwise structural similarity to other models. Then, similar structures are grouped into clusters using multidimensional scaling and clustering algorithms. In each cluster, the one with the highest consensus score is selected as a candidate model. For the QA problem, MDS-QA combines single-model scoring functions with consensus to determine more accurate assessment score for every model in a given pool. Using extensive benchmark sets of a large collection of predicted models, we compare the two algorithms with existing state-of-the-art quality assessment methods and show significant improvement. PMID:24808625

  2. NEW MDS AND CLUSTERING BASED ALGORITHMS FOR PROTEIN MODEL QUALITY ASSESSMENT AND SELECTION

    PubMed Central

    WANG, QINGGUO; SHANG, CHARLES; XU, DONG

    2014-01-01

    In protein tertiary structure prediction, assessing the quality of predicted models is an essential task. Over the past years, many methods have been proposed for the protein model quality assessment (QA) and selection problem. Despite significant advances, the discerning power of current methods is still unsatisfactory. In this paper, we propose two new algorithms, CC-Select and MDS-QA, based on multidimensional scaling and k-means clustering. For the model selection problem, CC-Select combines consensus with clustering techniques to select the best models from a given pool. Given a set of predicted models, CC-Select first calculates a consensus score for each structure based on its average pairwise structural similarity to other models. Then, similar structures are grouped into clusters using multidimensional scaling and clustering algorithms. In each cluster, the one with the highest consensus score is selected as a candidate model. For the QA problem, MDS-QA combines single-model scoring functions with consensus to determine more accurate assessment score for every model in a given pool. Using extensive benchmark sets of a large collection of predicted models, we compare the two algorithms with existing state-of-the-art quality assessment methods and show significant improvement. PMID:24808625

  3. Knowledge of Native Protein-Protein Interfaces Is Sufficient To Construct Predictive Models for the Selection of Binding Candidates.

    PubMed

    Popov, Petr; Grudinin, Sergei

    2015-10-26

    Selection of putative binding poses is a challenging part of virtual screening for protein-protein interactions. Predictive models to filter out binding candidates with the highest binding affinities comprise scoring functions that assign a score to each binding pose. Existing scoring functions are typically deduced by collecting statistical information about interfaces of native conformations of protein complexes along with interfaces of a large generated set of non-native conformations. However, the obtained scoring functions become biased toward the method used to generate the non-native conformations, i.e., they may not recognize near-native interfaces generated with a different method. The present study demonstrates that knowledge of only native protein-protein interfaces is sufficient to construct well-discriminative predictive models for the selection of binding candidates. Here we introduce a new scoring method that comprises a knowledge-based potential called KSENIA deduced from structural information about the native interfaces of 844 crystallographic protein-protein complexes. We derive KSENIA using convex optimization with a training set composed of native protein complexes and their near-native conformations obtained using deformations along the low-frequency normal modes. As a result, our knowledge-based potential has only marginal bias toward a method used to generate putative binding poses. Furthermore, KSENIA is smooth by construction, which allows it to be used along with rigid-body optimization to refine the binding poses. Using several test benchmarks, we demonstrate that our method discriminates well native and near-native conformations of protein complexes from non-native ones. Our methodology can be easily adapted to the recognition of other types of molecular interactions, such as protein-ligand, protein-RNA, etc. KSENIA will be made publicly available as a part of the SAMSON software platform at https://team.inria.fr/nano-d/software . PMID

  4. Selective Precipitation of Proteins.

    PubMed

    Matulis, Daumantas

    2016-01-01

    Selective precipitation of proteins can be used as a bulk method to recover the majority of proteins from a crude lysate, as a selective method to fractionate a subset of proteins from a protein solution, or as a very specific method to recover a single protein of interest from a purification step. This unit describes a number of methods suitable for selective precipitation. In each of the protocols that are outlined, the physical or chemical basis of the precipitation process, the parameters that can be varied for optimization, and the basic steps for developing an optimized precipitation are described.

  5. Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

    PubMed Central

    Huang, Lei; Liao, Li; Wu, Cathy H.

    2016-01-01

    Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

  6. Natural selection, protein engineering, and the last riboorganism: rational model building in biochemistry.

    PubMed

    Benner, S A; Allemann, R K; Ellington, A D; Ge, L; Glasfeld, A; Leanz, G F; Krauch, T; MacPherson, L J; Moroney, S; Piccirilli, J A

    1987-01-01

    A detailed study of the chemical behavior of modern catalysts (here, exemplified by dehydrogenases dependent on NAD+) allows us to construct models that distinguish between selected and drifting behaviors in biological macromolecules. These models enable us to manipulate rationally the properties of enzymes, here to design an "acetaldehyde reductase" dependent on NAD+ that is faster than any given us by nature. When applied to the origin of protein catalysis, models that explain the structures of ribo-cofactors (e.g., NAD+) must postulate a metabolically complex breakthrough organism. This means that: (1) The view from the present day back to the truly primeval organism is obscured; it is futile to try to deduce the detailed structure of the first life by examining the behaviors of modern organisms. (2) Riboorganisms dominated life on earth for a long time before translation evolved; indeed, fossils of riboorganisms might already be known. (3) Using organic synthesis, we have expanded the number of bases available for making RNA and making accessible RNA molecules that are likely to be intrinsically better catalysts. PMID:2456885

  7. Weak Selection and Protein Evolution

    PubMed Central

    Akashi, Hiroshi; Osada, Naoki; Ohta, Tomoko

    2012-01-01

    The “nearly neutral” theory of molecular evolution proposes that many features of genomes arise from the interaction of three weak evolutionary forces: mutation, genetic drift, and natural selection acting at its limit of efficacy. Such forces generally have little impact on allele frequencies within populations from generation to generation but can have substantial effects on long-term evolution. The evolutionary dynamics of weakly selected mutations are highly sensitive to population size, and near neutrality was initially proposed as an adjustment to the neutral theory to account for general patterns in available protein and DNA variation data. Here, we review the motivation for the nearly neutral theory, discuss the structure of the model and its predictions, and evaluate current empirical support for interactions among weak evolutionary forces in protein evolution. Near neutrality may be a prevalent mode of evolution across a range of functional categories of mutations and taxa. However, multiple evolutionary mechanisms (including adaptive evolution, linked selection, changes in fitness-effect distributions, and weak selection) can often explain the same patterns of genome variation. Strong parameter sensitivity remains a limitation of the nearly neutral model, and we discuss concave fitness functions as a plausible underlying basis for weak selection. PMID:22964835

  8. Selective Inhibitors of Protein Methyltransferases

    PubMed Central

    2015-01-01

    Mounting evidence suggests that protein methyltransferases (PMTs), which catalyze methylation of histone and nonhistone proteins, play a crucial role in diverse biological processes and human diseases. In particular, PMTs have been recognized as major players in regulating gene expression and chromatin state. PMTs are divided into two categories: protein lysine methyltransferases (PKMTs) and protein arginine methyltransferases (PRMTs). There has been a steadily growing interest in these enzymes as potential therapeutic targets and therefore discovery of PMT inhibitors has also been pursued increasingly over the past decade. Here, we present a perspective on selective, small-molecule inhibitors of PMTs with an emphasis on their discovery, characterization, and applicability as chemical tools for deciphering the target PMTs’ physiological functions and involvement in human diseases. We highlight the current state of PMT inhibitors and discuss future directions and opportunities for PMT inhibitor discovery. PMID:25406853

  9. Model Selection for Geostatistical Models

    SciTech Connect

    Hoeting, Jennifer A.; Davis, Richard A.; Merton, Andrew A.; Thompson, Sandra E.

    2006-02-01

    We consider the problem of model selection for geospatial data. Spatial correlation is typically ignored in the selection of explanatory variables and this can influence model selection results. For example, the inclusion or exclusion of particular explanatory variables may not be apparent when spatial correlation is ignored. To address this problem, we consider the Akaike Information Criterion (AIC) as applied to a geostatistical model. We offer a heuristic derivation of the AIC in this context and provide simulation results that show that using AIC for a geostatistical model is superior to the often used approach of ignoring spatial correlation in the selection of explanatory variables. These ideas are further demonstrated via a model for lizard abundance. We also employ the principle of minimum description length (MDL) to variable selection for the geostatistical model. The effect of sampling design on the selection of explanatory covariates is also explored.

  10. Understanding protein evolution: from protein physics to Darwinian selection.

    PubMed

    Zeldovich, Konstantin B; Shakhnovich, Eugene I

    2008-01-01

    Efforts in whole-genome sequencing and structural proteomics start to provide a global view of the protein universe, the set of existing protein structures and sequences. However, approaches based on the selection of individual sequences have not been entirely successful at the quantitative description of the distribution of structures and sequences in the protein universe because evolutionary pressure acts on the entire organism, rather than on a particular molecule. In parallel to this line of study, studies in population genetics and phenomenological molecular evolution established a mathematical framework to describe the changes in genome sequences in populations of organisms over time. Here, we review both microscopic (physics-based) and macroscopic (organism-level) models of protein-sequence evolution and demonstrate that bridging the two scales provides the most complete description of the protein universe starting from clearly defined, testable, and physiologically relevant assumptions.

  11. Quantitative Rheological Model Selection

    NASA Astrophysics Data System (ADS)

    Freund, Jonathan; Ewoldt, Randy

    2014-11-01

    The more parameters in a rheological the better it will reproduce available data, though this does not mean that it is necessarily a better justified model. Good fits are only part of model selection. We employ a Bayesian inference approach that quantifies model suitability by balancing closeness to data against both the number of model parameters and their a priori uncertainty. The penalty depends upon prior-to-calibration expectation of the viable range of values that model parameters might take, which we discuss as an essential aspect of the selection criterion. Models that are physically grounded are usually accompanied by tighter physical constraints on their respective parameters. The analysis reflects a basic principle: models grounded in physics can be expected to enjoy greater generality and perform better away from where they are calibrated. In contrast, purely empirical models can provide comparable fits, but the model selection framework penalizes their a priori uncertainty. We demonstrate the approach by selecting the best-justified number of modes in a Multi-mode Maxwell description of PVA-Borax. We also quantify relative merits of the Maxwell model relative to powerlaw fits and purely empirical fits for PVA-Borax, a viscoelastic liquid, and gluten.

  12. Protein solubility modeling

    NASA Technical Reports Server (NTRS)

    Agena, S. M.; Pusey, M. L.; Bogle, I. D.

    1999-01-01

    A thermodynamic framework (UNIQUAC model with temperature dependent parameters) is applied to model the salt-induced protein crystallization equilibrium, i.e., protein solubility. The framework introduces a term for the solubility product describing protein transfer between the liquid and solid phase and a term for the solution behavior describing deviation from ideal solution. Protein solubility is modeled as a function of salt concentration and temperature for a four-component system consisting of a protein, pseudo solvent (water and buffer), cation, and anion (salt). Two different systems, lysozyme with sodium chloride and concanavalin A with ammonium sulfate, are investigated. Comparison of the modeled and experimental protein solubility data results in an average root mean square deviation of 5.8%, demonstrating that the model closely follows the experimental behavior. Model calculations and model parameters are reviewed to examine the model and protein crystallization process. Copyright 1999 John Wiley & Sons, Inc.

  13. Mass Spectrometric-Based Selected Reaction Monitoring of Protein Phosphorylation during Symbiotic Signaling in the Model Legume, Medicago truncatula

    PubMed Central

    Maeda, Junko; Barrett-Wilt, Gregory A.; Sussman, Michael R.

    2016-01-01

    Unlike the major cereal crops corn, rice, and wheat, leguminous plants such as soybean and alfalfa can meet their nitrogen requirement via endosymbiotic associations with soil bacteria. The establishment of this symbiosis is a complex process playing out over several weeks and is facilitated by the exchange of chemical signals between these partners from different kingdoms. Several plant components that are involved in this signaling pathway have been identified, but there is still a great deal of uncertainty regarding the early events in symbiotic signaling, i.e., within the first minutes and hours after the rhizobial signals (Nod factors) are perceived at the plant plasma membrane. The presence of several protein kinases in this pathway suggests a mechanism of signal transduction via posttranslational modification of proteins in which phosphate is added to the hydroxyl groups of serine, threonine and tyrosine amino acid side chains. To monitor the phosphorylation dynamics and complement our previous untargeted 'discovery' approach, we report here the results of experiments using a targeted mass spectrometric technique, Selected Reaction Monitoring (SRM) that enables the quantification of phosphorylation targets with great sensitivity and precision. Using this approach, we confirm a rapid change in the level of phosphorylation in 4 phosphosites of at least 4 plant phosphoproteins that have not been previously characterized. This detailed analysis reveals aspects of the symbiotic signaling mechanism in legumes that, in the long term, will inform efforts to engineer this nitrogen-fixing symbiosis in important non-legume crops such as rice, wheat and corn. PMID:27203723

  14. On the ion selectivity in Ca-binding proteins: the cyclo(-L-Pro-Gly-)3 peptide as a model.

    PubMed Central

    Sussman, F; Weinstein, H

    1989-01-01

    Calcium plays a crucial role in many cellular processes. Its functions are directly dependent on the high specificity for Ca2+ exhibited by the proteins and ion carriers that bind divalent ions. To elucidate the basis for this specificity we have calculated the relative energies of solvation of calcium and magnesium ions in complexes with cyclo(-L-Pro-Gly-)3, a small synthetic peptide that binds Ca2+ with an affinity comparable to those of the naturally occurring proteins. The results show that the ion selectivity of the peptide resides in the difference in the solvation energies of the competing ions in water. Although the peptide is able to complex Mg2+ better than Ca2+ in the stoichiometries in which cyclo(-L-Pro-Gly-)3 binds divalent ions, it is not always able to provide as much stabilization for Mg2+ as water does. These results also explain why cyclo(-L-Pro-Gly-)3 binds Ca2+ and Mg2+ with different stoichiometries and indicate the source for expected differences in the structures of complexes of the two ions. Images PMID:2813364

  15. Mass Spectrometric-Based Selected Reaction Monitoring of Protein Phosphorylation during Symbiotic Signaling in the Model Legume, Medicago truncatula.

    PubMed

    Van Ness, Lori K; Jayaraman, Dhileepkumar; Maeda, Junko; Barrett-Wilt, Gregory A; Sussman, Michael R; Ané, Jean-Michel

    2016-01-01

    Unlike the major cereal crops corn, rice, and wheat, leguminous plants such as soybean and alfalfa can meet their nitrogen requirement via endosymbiotic associations with soil bacteria. The establishment of this symbiosis is a complex process playing out over several weeks and is facilitated by the exchange of chemical signals between these partners from different kingdoms. Several plant components that are involved in this signaling pathway have been identified, but there is still a great deal of uncertainty regarding the early events in symbiotic signaling, i.e., within the first minutes and hours after the rhizobial signals (Nod factors) are perceived at the plant plasma membrane. The presence of several protein kinases in this pathway suggests a mechanism of signal transduction via posttranslational modification of proteins in which phosphate is added to the hydroxyl groups of serine, threonine and tyrosine amino acid side chains. To monitor the phosphorylation dynamics and complement our previous untargeted 'discovery' approach, we report here the results of experiments using a targeted mass spectrometric technique, Selected Reaction Monitoring (SRM) that enables the quantification of phosphorylation targets with great sensitivity and precision. Using this approach, we confirm a rapid change in the level of phosphorylation in 4 phosphosites of at least 4 plant phosphoproteins that have not been previously characterized. This detailed analysis reveals aspects of the symbiotic signaling mechanism in legumes that, in the long term, will inform efforts to engineer this nitrogen-fixing symbiosis in important non-legume crops such as rice, wheat and corn. PMID:27203723

  16. Protein structure modeling with MODELLER.

    PubMed

    Webb, Benjamin; Sali, Andrej

    2014-01-01

    Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at atomic resolution using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In this chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.

  17. Modeling Protein Expression and Protein Signaling Pathways

    PubMed Central

    Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

    2015-01-01

    High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

  18. Selection maintaining protein stability at equilibrium.

    PubMed

    Miyazawa, Sanzo

    2016-02-21

    The common understanding of protein evolution has been that neutral mutations are fixed by random drift, and a proportion of neutral mutations depending on the strength of structural and functional constraints primarily determines evolutionary rate. Recently it was indicated that fitness costs due to misfolded proteins are a determinant of evolutionary rate and selection originating in protein stability is a driving force of protein evolution. Here we examine protein evolution under the selection maintaining protein stability. Protein fitness is a generic form of fitness costs due to misfolded proteins; s=κexp(ΔG/kT)(1-exp(ΔΔG/kT)), where s and ΔΔG are selective advantage and stability change of a mutant protein, ΔG is the folding free energy of the wildtype protein, and κ is a parameter representing protein abundance and indispensability. The distribution of ΔΔG is approximated to be a bi-Gaussian distribution, which represents structurally slightly- or highly-constrained sites. Also, the mean of the distribution is negatively proportional to ΔG. The evolution of this gene has an equilibrium point (ΔGe) of protein stability, the range of which is consistent with observed values in the ProTherm database. The probability distribution of Ka/Ks, the ratio of nonsynonymous to synonymous substitution rate per site, over fixed mutants in the vicinity of the equilibrium shows that nearly neutral selection is predominant only in low-abundant, non-essential proteins of ΔGe>-2.5 kcal/mol. In the other proteins, positive selection on stabilizing mutations is significant to maintain protein stability at equilibrium as well as random drift on slightly negative mutations, although the average 〈Ka/Ks〉 is less than 1. Slow evolutionary rates can be caused by both high protein abundance/indispensability and large effective population size, which produces positive shifts of ΔΔG through decreasing ΔGe, and strong structural constraints, which directly make

  19. Young proteins experience more variable selection pressures than old proteins.

    PubMed

    Vishnoi, Anchal; Kryazhimskiy, Sergey; Bazykin, Georgii A; Hannenhalli, Sridhar; Plotkin, Joshua B

    2010-11-01

    It is well known that young proteins tend to experience weaker purifying selection and evolve more quickly than old proteins. Here, we show that, in addition, young proteins tend to experience more variable selection pressures over time than old proteins. We demonstrate this pattern in three independent taxonomic groups: yeast, Drosophila, and mammals. The increased variability of selection pressures on young proteins is highly significant even after controlling for the fact that young proteins are typically shorter and experience weaker purifying selection than old proteins. The majority of our results are consistent with the hypothesis that the function of a young gene tends to change over time more readily than that of an old gene. At the same time, our results may be caused in part by young genes that serve constant functions over time, but nevertheless appear to evolve under changing selection pressures due to depletion of adaptive mutations. In either case, our results imply that the evolution of a protein-coding sequence is partly determined by its age and origin, and not only by the phenotypic properties of the encoded protein. We discuss, via specific examples, the consequences of these findings for understanding of the sources of evolutionary novelty.

  20. Computer Models of Proteins

    NASA Technical Reports Server (NTRS)

    2000-01-01

    Dr. Marc Pusey (seated) and Dr. Craig Kundrot use computers to analyze x-ray maps and generate three-dimensional models of protein structures. With this information, scientists at Marshall Space Flight Center can learn how proteins are made and how they work. The computer screen depicts a proten structure as a ball-and-stick model. Other models depict the actual volume occupied by the atoms, or the ribbon-like structures that are crucial to a protein's function.

  1. Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement

    PubMed Central

    Jiang, Hanlun; Sheong, Fu Kit; Zhu, Lizhe; Gao, Xin; Bernauer, Julie; Huang, Xuhui

    2015-01-01

    Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems. PMID:26181723

  2. Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement.

    PubMed

    Jiang, Hanlun; Sheong, Fu Kit; Zhu, Lizhe; Gao, Xin; Bernauer, Julie; Huang, Xuhui

    2015-07-01

    Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems.

  3. Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement.

    PubMed

    Jiang, Hanlun; Sheong, Fu Kit; Zhu, Lizhe; Gao, Xin; Bernauer, Julie; Huang, Xuhui

    2015-07-01

    Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems. PMID:26181723

  4. Selective memory generalization by spatial patterning of protein synthesis

    PubMed Central

    O’Donnell, Cian; Sejnowski, Terrence J.

    2014-01-01

    Summary Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings we proposed a novel two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. PMID:24742462

  5. Individual Influence on Model Selection

    ERIC Educational Resources Information Center

    Sterba, Sonya K.; Pek, Jolynn

    2012-01-01

    Researchers in psychology are increasingly using model selection strategies to decide among competing models, rather than evaluating the fit of a given model in isolation. However, such interest in model selection outpaces an awareness that one or a few cases can have disproportionate impact on the model ranking. Though case influence on the fit…

  6. Targeting Human Central Nervous System Protein Kinases: An Isoform Selective p38αMAPK Inhibitor That Attenuates Disease Progression in Alzheimer’s Disease Mouse Models

    PubMed Central

    2015-01-01

    The first kinase inhibitor drug approval in 2001 initiated a remarkable decade of tyrosine kinase inhibitor drugs for oncology indications, but a void exists for serine/threonine protein kinase inhibitor drugs and central nervous system indications. Stress kinases are of special interest in neurological and neuropsychiatric disorders due to their involvement in synaptic dysfunction and complex disease susceptibility. Clinical and preclinical evidence implicates the stress related kinase p38αMAPK as a potential neurotherapeutic target, but isoform selective p38αMAPK inhibitor candidates are lacking and the mixed kinase inhibitor drugs that are promising in peripheral tissue disease indications have limitations for neurologic indications. Therefore, pursuit of the neurotherapeutic hypothesis requires kinase isoform selective inhibitors with appropriate neuropharmacology features. Synaptic dysfunction disorders offer a potential for enhanced pharmacological efficacy due to stress-induced activation of p38αMAPK in both neurons and glia, the interacting cellular components of the synaptic pathophysiological axis, to be modulated. We report a novel isoform selective p38αMAPK inhibitor, MW01-18-150SRM (=MW150), that is efficacious in suppression of hippocampal-dependent associative and spatial memory deficits in two distinct synaptic dysfunction mouse models. A synthetic scheme for biocompatible product and positive outcomes from pharmacological screens are presented. The high-resolution crystallographic structure of the p38αMAPK/MW150 complex documents active site binding, reveals a potential low energy conformation of the bound inhibitor, and suggests a structural explanation for MW150’s exquisite target selectivity. As far as we are aware, MW150 is without precedent as an isoform selective p38MAPK inhibitor or as a kinase inhibitor capable of modulating in vivo stress related behavior. PMID:25676389

  7. Modeling Natural Selection

    ERIC Educational Resources Information Center

    Bogiages, Christopher A.; Lotter, Christine

    2011-01-01

    In their research, scientists generate, test, and modify scientific models. These models can be shared with others and demonstrate a scientist's understanding of how the natural world works. Similarly, students can generate and modify models to gain a better understanding of the content, process, and nature of science (Kenyon, Schwarz, and Hug…

  8. Cytosolic Selection Systems To Study Protein Stability

    PubMed Central

    Malik, Ajamaluddin; Mueller-Schickert, Antje

    2014-01-01

    Here we describe biosensors that provide readouts for protein stability in the cytosolic compartment of prokaryotes. These biosensors consist of tripartite sandwich fusions that link the in vitro stability or aggregation susceptibility of guest proteins to the in vivo resistance of host cells to the antibiotics kanamycin, spectinomycin, and nourseothricin. These selectable markers confer antibiotic resistance in a wide range of hosts and are easily quantifiable. We show that mutations within guest proteins that affect their stability alter the antibiotic resistances of the cells expressing the biosensors in a manner that is related to the in vitro stabilities of the mutant guest proteins. In addition, we find that polyglutamine tracts of increasing length are associated with an increased tendency to form amyloids in vivo and, in our sandwich fusion system, with decreased resistance to aminoglycoside antibiotics. We demonstrate that our approach allows the in vivo analysis of protein stability in the cytosolic compartment without the need for prior structural and functional knowledge. PMID:25266385

  9. Modeling Mercury in Proteins

    SciTech Connect

    Smith, Jeremy C; Parks, Jerry M

    2016-01-01

    Mercury (Hg) is a naturally occurring element that is released into the biosphere both by natural processes and anthropogenic activities. Although its reduced, elemental form Hg(0) is relatively non-toxic, other forms such as Hg2+ and, in particular, its methylated form, methylmercury, are toxic, with deleterious effects on both ecosystems and humans. Microorganisms play important roles in the transformation of mercury in the environment. Inorganic Hg2+ can be methylated by certain bacteria and archaea to form methylmercury. Conversely, bacteria also demethylate methylmercury and reduce Hg2+ to relatively inert Hg(0). Transformations and toxicity occur as a result of mercury interacting with various proteins. Clearly, then, understanding the toxic effects of mercury and its cycling in the environment requires characterization of these interactions. Computational approaches are ideally suited to studies of mercury in proteins because they can provide a detailed picture and circumvent issues associated with toxicity. Here we describe computational methods for investigating and characterizing how mercury binds to proteins, how inter- and intra-protein transfer of mercury is orchestrated in biological systems, and how chemical reactions in proteins transform the metal. We describe quantum chemical analyses of aqueous Hg(II), which reveal critical factors that determine ligand binding propensities. We then provide a perspective on how we used chemical reasoning to discover how microorganisms methylate mercury. We also highlight our combined computational and experimental studies of the proteins and enzymes of the mer operon, a suite of genes that confers mercury resistance in many bacteria. Lastly, we place work on mercury in proteins in the context of what is needed for a comprehensive multi-scale model of environmental mercury cycling.

  10. Protein recognition and selection through conformational and mutually induced fit

    PubMed Central

    Wang, Qian; Zhang, Pengzhi; Hoffman, Laurel; Tripathi, Swarnendu; Homouz, Dirar; Liu, Yin; Waxham, M. Neal; Cheung, Margaret S.

    2013-01-01

    Protein–protein interactions drive most every biological process, but in many instances the domains mediating recognition are disordered. How specificity in binding is attained in the absence of defined structure contrasts with well-established experimental and theoretical work describing ligand binding to protein. The signaling protein calmodulin presents a unique opportunity to investigate mechanisms for target recognition given that it interacts with several hundred different targets. By advancing coarse-grained computer simulations and experimental techniques, mechanistic insights were gained in defining the pathways leading to recognition and in how target selectivity can be achieved at the molecular level. A model requiring mutually induced conformational changes in both calmodulin and target proteins was necessary and broadly informs how proteins can achieve both high affinity and high specificity. PMID:24297894

  11. Launch vehicle selection model

    NASA Technical Reports Server (NTRS)

    Montoya, Alex J.

    1990-01-01

    Over the next 50 years, humans will be heading for the Moon and Mars to build scientific bases to gain further knowledge about the universe and to develop rewarding space activities. These large scale projects will last many years and will require large amounts of mass to be delivered to Low Earth Orbit (LEO). It will take a great deal of planning to complete these missions in an efficient manner. The planning of a future Heavy Lift Launch Vehicle (HLLV) will significantly impact the overall multi-year launching cost for the vehicle fleet depending upon when the HLLV will be ready for use. It is desirable to develop a model in which many trade studies can be performed. In one sample multi-year space program analysis, the total launch vehicle cost of implementing the program reduced from 50 percent to 25 percent. This indicates how critical it is to reduce space logistics costs. A linear programming model has been developed to answer such questions. The model is now in its second phase of development, and this paper will address the capabilities of the model and its intended uses. The main emphasis over the past year was to make the model user friendly and to incorporate additional realistic constraints that are difficult to represent mathematically. We have developed a methodology in which the user has to be knowledgeable about the mission model and the requirements of the payloads. We have found a representation that will cut down the solution space of the problem by inserting some preliminary tests to eliminate some infeasible vehicle solutions. The paper will address the handling of these additional constraints and the methodology for incorporating new costing information utilizing learning curve theory. The paper will review several test cases that will explore the preferred vehicle characteristics and the preferred period of construction, i.e., within the next decade, or in the first decade of the next century. Finally, the paper will explore the interaction

  12. Modeling Mercury in Proteins.

    PubMed

    Parks, J M; Smith, J C

    2016-01-01

    Mercury (Hg) is a naturally occurring element that is released into the biosphere both by natural processes and anthropogenic activities. Although its reduced, elemental form Hg(0) is relatively nontoxic, other forms such as Hg(2+) and, in particular, its methylated form, methylmercury, are toxic, with deleterious effects on both ecosystems and humans. Microorganisms play important roles in the transformation of mercury in the environment. Inorganic Hg(2+) can be methylated by certain bacteria and archaea to form methylmercury. Conversely, bacteria also demethylate methylmercury and reduce Hg(2+) to relatively inert Hg(0). Transformations and toxicity occur as a result of mercury interacting with various proteins. Clearly, then, understanding the toxic effects of mercury and its cycling in the environment requires characterization of these interactions. Computational approaches are ideally suited to studies of mercury in proteins because they can provide a detailed molecular picture and circumvent issues associated with toxicity. Here, we describe computational methods for investigating and characterizing how mercury binds to proteins, how inter- and intraprotein transfer of mercury is orchestrated in biological systems, and how chemical reactions in proteins transform the metal. We describe quantum chemical analyses of aqueous Hg(II), which reveal critical factors that determine ligand-binding propensities. We then provide a perspective on how we used chemical reasoning to discover how microorganisms methylate mercury. We also highlight our combined computational and experimental studies of the proteins and enzymes of the mer operon, a suite of genes that confer mercury resistance in many bacteria. Lastly, we place work on mercury in proteins in the context of what is needed for a comprehensive multiscale model of environmental mercury cycling.

  13. Modeling Mercury in Proteins.

    PubMed

    Parks, J M; Smith, J C

    2016-01-01

    Mercury (Hg) is a naturally occurring element that is released into the biosphere both by natural processes and anthropogenic activities. Although its reduced, elemental form Hg(0) is relatively nontoxic, other forms such as Hg(2+) and, in particular, its methylated form, methylmercury, are toxic, with deleterious effects on both ecosystems and humans. Microorganisms play important roles in the transformation of mercury in the environment. Inorganic Hg(2+) can be methylated by certain bacteria and archaea to form methylmercury. Conversely, bacteria also demethylate methylmercury and reduce Hg(2+) to relatively inert Hg(0). Transformations and toxicity occur as a result of mercury interacting with various proteins. Clearly, then, understanding the toxic effects of mercury and its cycling in the environment requires characterization of these interactions. Computational approaches are ideally suited to studies of mercury in proteins because they can provide a detailed molecular picture and circumvent issues associated with toxicity. Here, we describe computational methods for investigating and characterizing how mercury binds to proteins, how inter- and intraprotein transfer of mercury is orchestrated in biological systems, and how chemical reactions in proteins transform the metal. We describe quantum chemical analyses of aqueous Hg(II), which reveal critical factors that determine ligand-binding propensities. We then provide a perspective on how we used chemical reasoning to discover how microorganisms methylate mercury. We also highlight our combined computational and experimental studies of the proteins and enzymes of the mer operon, a suite of genes that confer mercury resistance in many bacteria. Lastly, we place work on mercury in proteins in the context of what is needed for a comprehensive multiscale model of environmental mercury cycling. PMID:27497164

  14. Modeling Epistasis in Genomic Selection.

    PubMed

    Jiang, Yong; Reif, Jochen C

    2015-10-01

    Modeling epistasis in genomic selection is impeded by a high computational load. The extended genomic best linear unbiased prediction (EG-BLUP) with an epistatic relationship matrix and the reproducing kernel Hilbert space regression (RKHS) are two attractive approaches that reduce the computational load. In this study, we proved the equivalence of EG-BLUP and genomic selection approaches, explicitly modeling epistatic effects. Moreover, we have shown why the RKHS model based on a Gaussian kernel captures epistatic effects among markers. Using experimental data sets in wheat and maize, we compared different genomic selection approaches and concluded that prediction accuracy can be improved by modeling epistasis for selfing species but may not for outcrossing species. PMID:26219298

  15. Comparative Protein Structure Modeling Using MODELLER.

    PubMed

    Webb, Benjamin; Sali, Andrej

    2014-09-08

    Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

  16. Hierarchy and extremes in selections from pools of randomized proteins.

    PubMed

    Boyer, Sébastien; Biswas, Dipanwita; Kumar Soshee, Ananda; Scaramozzino, Natale; Nizak, Clément; Rivoire, Olivier

    2016-03-29

    Variation and selection are the core principles of Darwinian evolution, but quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in the context of populations of partially randomized proteins selected for binding to well-defined targets. We built several minimal protein libraries, screened them in vitro by phage display, and analyzed their response to selection by high-throughput sequencing. A statistical analysis of the results reveals two main findings. First, libraries with the same sequence diversity but built around different "frameworks" typically have vastly different responses; second, the distribution of responses of the best binders in a library follows a simple scaling law. We show how an elementary probabilistic model based on extreme value theory rationalizes the latter finding. Our results have implications for designing synthetic protein libraries, estimating the density of functional biomolecules in sequence space, characterizing diversity in natural populations, and experimentally investigating evolvability (i.e., the potential for future evolution). PMID:26969726

  17. Hierarchy and extremes in selections from pools of randomized proteins

    PubMed Central

    Boyer, Sébastien; Biswas, Dipanwita; Kumar Soshee, Ananda; Scaramozzino, Natale; Nizak, Clément; Rivoire, Olivier

    2016-01-01

    Variation and selection are the core principles of Darwinian evolution, but quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in the context of populations of partially randomized proteins selected for binding to well-defined targets. We built several minimal protein libraries, screened them in vitro by phage display, and analyzed their response to selection by high-throughput sequencing. A statistical analysis of the results reveals two main findings. First, libraries with the same sequence diversity but built around different “frameworks” typically have vastly different responses; second, the distribution of responses of the best binders in a library follows a simple scaling law. We show how an elementary probabilistic model based on extreme value theory rationalizes the latter finding. Our results have implications for designing synthetic protein libraries, estimating the density of functional biomolecules in sequence space, characterizing diversity in natural populations, and experimentally investigating evolvability (i.e., the potential for future evolution). PMID:26969726

  18. SIENA: Efficient Compilation of Selective Protein Binding Site Ensembles.

    PubMed

    Bietz, Stefan; Rarey, Matthias

    2016-01-25

    Structural flexibility of proteins has an important influence on molecular recognition and enzymatic function. In modeling, structure ensembles are therefore often applied as a valuable source of alternative protein conformations. However, their usage is often complicated by structural artifacts and inconsistent data annotation. Here, we present SIENA, a new computational approach for the automated assembly and preprocessing of protein binding site ensembles. Starting with an arbitrarily defined binding site in a single protein structure, SIENA searches for alternative conformations of the same or sequentially closely related binding sites. The method is based on an indexed database for identifying perfect k-mer matches and a recently published algorithm for the alignment of protein binding site conformations. Furthermore, SIENA provides a new algorithm for the interaction-based selection of binding site conformations which aims at covering all known ligand-binding geometries. Various experiments highlight that SIENA is able to generate comprehensive and well selected binding site ensembles improving the compatibility to both known and unconsidered ligand molecules. Starting with the whole PDB as data source, the computation time of the whole ensemble generation takes only a few seconds. SIENA is available via a Web service at www.zbh.uni-hamburg.de/siena .

  19. Model selection for logistic regression models

    NASA Astrophysics Data System (ADS)

    Duller, Christine

    2012-09-01

    Model selection for logistic regression models decides which of some given potential regressors have an effect and hence should be included in the final model. The second interesting question is whether a certain factor is heterogeneous among some subsets, i.e. whether the model should include a random intercept or not. In this paper these questions will be answered with classical as well as with Bayesian methods. The application show some results of recent research projects in medicine and business administration.

  20. Modeling Protein Self Assembly

    ERIC Educational Resources Information Center

    Baker, William P.; Jones, Carleton Buck; Hull, Elizabeth

    2004-01-01

    Understanding the structure and function of proteins is an important part of the standards-based science curriculum. Proteins serve vital roles within the cell and malfunctions in protein self assembly are implicated in degenerative diseases. Experience indicates that this topic is a difficult one for many students. We have found that the concept…

  1. Modeling Protein Domain Function

    ERIC Educational Resources Information Center

    Baker, William P.; Jones, Carleton "Buck"; Hull, Elizabeth

    2007-01-01

    This simple but effective laboratory exercise helps students understand the concept of protein domain function. They use foam beads, Styrofoam craft balls, and pipe cleaners to explore how domains within protein active sites interact to form a functional protein. The activity allows students to gain content mastery and an understanding of the…

  2. Posterior Predictive Bayesian Phylogenetic Model Selection

    PubMed Central

    Lewis, Paul O.; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn

    2014-01-01

    We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand–Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. [Bayesian; conditional predictive ordinate; CPO; L-measure; LPML; model selection; phylogenetics; posterior predictive.] PMID:24193892

  3. An extended cure model and model selection.

    PubMed

    Peng, Yingwei; Xu, Jianfeng

    2012-04-01

    We propose a novel interpretation for a recently proposed Box-Cox transformation cure model, which leads to a natural extension of the cure model. Based on the extended model, we consider an important issue of model selection between the mixture cure model and the bounded cumulative hazard cure model via the likelihood ratio test, score test and Akaike's Information Criterion (AIC). Our empirical study shows that AIC is informative and both the score test and the likelihood ratio test have adequate power to differentiate between the mixture cure model and the bounded cumulative hazard cure model when the sample size is large. We apply the tests and AIC methods to leukemia and colon cancer data to examine the appropriateness of the cure models considered for them in the literature.

  4. Protein Significance Analysis in Selected Reaction Monitoring (SRM) Measurements*

    PubMed Central

    Chang, Ching-Yun; Picotti, Paola; Hüttenhain, Ruth; Heinzelmann-Schwarz, Viola; Jovanovic, Marko; Aebersold, Ruedi; Vitek, Olga

    2012-01-01

    Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that provides sensitive and accurate protein detection and quantification in complex biological mixtures. Statistical and computational tools are essential for the design and analysis of SRM experiments, particularly in studies with large sample throughput. Currently, most such tools focus on the selection of optimized transitions and on processing signals from SRM assays. Little attention is devoted to protein significance analysis, which combines the quantitative measurements for a protein across isotopic labels, peptides, charge states, transitions, samples, and conditions, and detects proteins that change in abundance between conditions while controlling the false discovery rate. We propose a statistical modeling framework for protein significance analysis. It is based on linear mixed-effects models and is applicable to most experimental designs for both isotope label-based and label-free SRM workflows. We illustrate the utility of the framework in two studies: one with a group comparison experimental design and the other with a time course experimental design. We further verify the accuracy of the framework in two controlled data sets, one from the NCI-CPTAC reproducibility investigation and the other from an in-house spike-in study. The proposed framework is sensitive and specific, produces accurate results in broad experimental circumstances, and helps to optimally design future SRM experiments. The statistical framework is implemented in an open-source R-based software package SRMstats, and can be used by researchers with a limited statistics background as a stand-alone tool or in integration with the existing computational pipelines. PMID:22190732

  5. Evasin-4, a tick-derived chemokine-binding protein with broad selectivity can be modified for use in preclinical disease models.

    PubMed

    Déruaz, Maud; Bonvin, Pauline; Severin, India C; Johnson, Zoë; Krohn, Sonja; Power, Christine A; Proudfoot, Amanda E I

    2013-10-01

    Rhipicephalus sanguineus, the common brown dog tick, produces several chemokine-binding proteins which are secreted into the host in its saliva to modulate the host response during feeding. Two of these demonstrate very restricted selectivity profiles. Here, we describe the characterization of the third, which we named Evasin-4. Evasin-4 was difficult to produce recombinantly using its native signal peptide in HEK cells, but expressed very well using the urokinase-type plasminogen activator signal peptide. Using SPR, Evasin-4 was shown to bind most CC chemokines. Investigation of the neutralization properties by inhibition of chemokine-induced chemotaxis showed that binding and neutralization did not correlate in all cases. Two major anomalies were observed: no binding was observed to CCL2 and CCL13, yet Evasin-4 was able to inhibit chemotaxis induced by these chemokines. Conversely, binding to CCL25 was observed, but Evasin-4 did not inhibit CCL25-induced chemotaxis. Size-exclusion chromatography confirmed that Evasin-4 forms a complex with CCL2 and CCL18. In accordance with the standard properties of unmodified small proteins, Evasin-4 was rapidly cleared following in vivo administration. To enhance the in vivo half-life and optimize its potential as a therapeutic agent, Fc fusions of Evasin-4 were created. Both the N- and C-terminal fusions were shown to retain binding activity, with the C-terminal fusion showing a modest reduction in potency. PMID:23910450

  6. Selected Tether Applications Cost Model

    NASA Technical Reports Server (NTRS)

    Keeley, Michael G.

    1988-01-01

    Diverse cost-estimating techniques and data combined into single program. Selected Tether Applications Cost Model (STACOM 1.0) is interactive accounting software tool providing means for combining several independent cost-estimating programs into fully-integrated mathematical model capable of assessing costs, analyzing benefits, providing file-handling utilities, and putting out information in text and graphical forms to screen, printer, or plotter. Program based on Lotus 1-2-3, version 2.0. Developed to provide clear, concise traceability and visibility into methodology and rationale for estimating costs and benefits of operations of Space Station tether deployer system.

  7. Functional properties of select edible oilseed proteins.

    PubMed

    Sharma, Girdhari M; Su, Mengna; Joshi, Aditya U; Roux, Kenneth H; Sathe, Shridhar K

    2010-05-12

    Borate saline buffer (0.1 M, pH 8.45) solubilized proteins from almond, Brazil nut, cashew nut, hazelnut, macadamia, pine nut, pistachio, Spanish peanut, Virginia peanut, and soybean seeds were prepared from the corresponding defatted flour. The yield was in the range from 10.6% (macadamia) to 27.4% (almond). The protein content, on a dry weight basis, of the lyophilized preparations ranged from 69.23% (pine nut) to 94.80% (soybean). Isolated proteins from Brazil nut had the lightest and hazelnut the darkest color. Isolated proteins exhibited good solubility in aqueous media. Foaming capacity (<40% overrun) and stability (<1 h) of the isolated proteins were poor to fair. Almond proteins had the highest viscosity among the tested proteins. Oil-holding capacity of the isolated proteins ranged from 2.8 (macadamia) to 7 (soybean) g of oil/g of protein. Least gelation concentrations (% w/v) for almond, Brazil nut, cashew, hazelnut, macadamia, pine nut, pistachio, Spanish peanut, Virginia peanut, and soybean were, respectively, 6, 8, 8, 12, 20, 12, 10, 14, 14, and 16.

  8. Functional properties of select edible oilseed proteins.

    PubMed

    Sharma, Girdhari M; Su, Mengna; Joshi, Aditya U; Roux, Kenneth H; Sathe, Shridhar K

    2010-05-12

    Borate saline buffer (0.1 M, pH 8.45) solubilized proteins from almond, Brazil nut, cashew nut, hazelnut, macadamia, pine nut, pistachio, Spanish peanut, Virginia peanut, and soybean seeds were prepared from the corresponding defatted flour. The yield was in the range from 10.6% (macadamia) to 27.4% (almond). The protein content, on a dry weight basis, of the lyophilized preparations ranged from 69.23% (pine nut) to 94.80% (soybean). Isolated proteins from Brazil nut had the lightest and hazelnut the darkest color. Isolated proteins exhibited good solubility in aqueous media. Foaming capacity (<40% overrun) and stability (<1 h) of the isolated proteins were poor to fair. Almond proteins had the highest viscosity among the tested proteins. Oil-holding capacity of the isolated proteins ranged from 2.8 (macadamia) to 7 (soybean) g of oil/g of protein. Least gelation concentrations (% w/v) for almond, Brazil nut, cashew, hazelnut, macadamia, pine nut, pistachio, Spanish peanut, Virginia peanut, and soybean were, respectively, 6, 8, 8, 12, 20, 12, 10, 14, 14, and 16. PMID:20201552

  9. Posterior predictive Bayesian phylogenetic model selection.

    PubMed

    Lewis, Paul O; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn

    2014-05-01

    We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand-Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. PMID:24193892

  10. A refined atomic scale model of the Saccharomyces cerevisiae K+-translocation protein Trk1p combined with experimental evidence confirms the role of selectivity filter glycines and other key residues.

    PubMed

    Zayats, Vasilina; Stockner, Thomas; Pandey, Saurabh Kumar; Wörz, Katharina; Ettrich, Rüdiger; Ludwig, Jost

    2015-05-01

    Potassium ion (K+) uptake in yeast is mediated mainly by the Trk1/2 proteins that enable cells to survive on external K+ concentration as low as a few μM. Fungal Trks are related to prokaryotic TRK and Ktr and plant HKT K+ transport systems. Overall sequence similarity is very low, thus requiring experimental verification of homology models. Here a refined structural model of the Saccharomyces cerevisiae Trk1 is presented that was obtained by combining homology modeling, molecular dynamics simulation and experimental verification through functional analysis of mutants. Structural models and experimental results showed that glycines within the selectivity filter, conserved among the K-channel/transporter family, are not only important for protein function, but are also required for correct folding/membrane targeting. A conserved aspartic acid in the PA helix (D79) and a lysine in the M2D helix (K1147) were proposed earlier to interact. Our results suggested individual roles of these residues in folding, structural integrity and function. While mutations of D79 completely abolished protein folding, mutations at position 1147 were tolerated to some extent. Intriguingly, a secondary interaction of D79 with R76 could enhance folding/stability of Trk1 and enable a fraction of Trk1[K1147A] to fold. The part of the ion permeation path containing the selectivity filter is shaped similar to that of ion channels. However below the selectivity filter it is obstructed or regulated by a proline containing loop. The presented model could provide the structural basis for addressing the long standing question if Trk1 is a passive or active ion-translocation system.

  11. Comparative Protein Structure Modeling Using MODELLER.

    PubMed

    Webb, Benjamin; Sali, Andrej

    2016-01-01

    Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc. PMID:27322406

  12. Comparative Protein Structure Modeling Using MODELLER.

    PubMed

    Webb, Benjamin; Sali, Andrej

    2016-06-20

    Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc.

  13. Cytoprotective-selective activated protein C therapy for ischemic stroke

    PubMed Central

    Mosnier, Laurent O.; Zlokovic, Berislav V.; Griffin, John H.

    2014-01-01

    Summary Despite years of research and efforts to translate stroke research to clinical therapy, ischemic stroke remains a major cause of death, disability, and diminished quality of life. Primary and secondary preventive measures combined with improved quality of care have made significant progress. However, no novel drug for ischemic stroke therapy has been approved in the past decade. Numerous studies have shown beneficial effects of activated protein C (APC) in rodent stroke models. In addition to its natural anticoagulant functions, APC conveys multiple direct cytoprotective effects on many different cell types that involve multiple receptors including protease activated receptor (PAR) 1, PAR3, and the endothelial protein C receptor (EPCR). Application of molecular engineered APC variants with altered selectivity profiles to rodent stroke models demonstrated that the beneficial effects of APC primarily require its cytoprotective activities but not its anticoagulant activities. Extensive basic, preclinical, and clinical research provided a compelling rationale based on strong evidence for translation of APC therapy that has led to the clinical development of the cytoprotective-selective APC variant, 3K3A-APC, for ischemic stroke. Recent identification of non-canonical PAR1 and PAR3 activation by APC that give rise to novel tethered-ligands capable of inducing biased cytoprotective signaling as opposed to the canonical signaling provides a mechanistic explanation for how APC-mediated PAR activation can selectively induce cytoprotective signaling pathways. Collectively, these paradigm-shifting discoveries provide detailed insights into the receptor targets and the molecular mechanisms for neuroprotection by cytoprotective-selective 3K3A-APC, which is currently a biologic drug in clinical trials for ischemic stroke. PMID:25230930

  14. Oregano Essential Oil Improves Intestinal Morphology and Expression of Tight Junction Proteins Associated with Modulation of Selected Intestinal Bacteria and Immune Status in a Pig Model.

    PubMed

    Zou, Yi; Xiang, Quanhang; Wang, Jun; Peng, Jian; Wei, Hongkui

    2016-01-01

    Oregano essential oil (OEO) has long been used to improve the health of animals, particularly the health of intestine, which is generally attributed to its antimicrobial and anti-inflammatory effects. However, how OEO acts in the intestine of pig is still unclear. This study was aimed at elucidating how OEO promotes the intestinal barrier integrity in a pig model. Pigs were fed a control diet alone or one supplemented with 25 mg/kg of OEO for 4 weeks. The OEO-treated pigs showed decreased (P < 0.05) endotoxin level in serum and increased (P < 0.05) villus height and expression of occludin and zonula occludens-1 (ZO-1) in the jejunum. These results demonstrated that the integrity of intestinal barrier was improved by OEO treatment. The OEO-treated pigs had a lower (P < 0.05) population of Escherichia coli in the jejunum, ileum, and colon than the control. This is in accordance with the greater inactivation (P < 0.05) of inflammation, which was reflected by the mitogen-activated protein kinase (MAPK), protein kinase B (Akt), and nuclear factor κB (NF-κB) signaling pathways and expression of inflammatory cytokines in the jejunum. Our results show that OEO promotes intestinal barrier integrity, probably through modulating intestinal bacteria and immune status in pigs. PMID:27314026

  15. Oregano Essential Oil Improves Intestinal Morphology and Expression of Tight Junction Proteins Associated with Modulation of Selected Intestinal Bacteria and Immune Status in a Pig Model

    PubMed Central

    Zou, Yi; Xiang, Quanhang; Wang, Jun; Peng, Jian; Wei, Hongkui

    2016-01-01

    Oregano essential oil (OEO) has long been used to improve the health of animals, particularly the health of intestine, which is generally attributed to its antimicrobial and anti-inflammatory effects. However, how OEO acts in the intestine of pig is still unclear. This study was aimed at elucidating how OEO promotes the intestinal barrier integrity in a pig model. Pigs were fed a control diet alone or one supplemented with 25 mg/kg of OEO for 4 weeks. The OEO-treated pigs showed decreased (P < 0.05) endotoxin level in serum and increased (P < 0.05) villus height and expression of occludin and zonula occludens-1 (ZO-1) in the jejunum. These results demonstrated that the integrity of intestinal barrier was improved by OEO treatment. The OEO-treated pigs had a lower (P < 0.05) population of Escherichia coli in the jejunum, ileum, and colon than the control. This is in accordance with the greater inactivation (P < 0.05) of inflammation, which was reflected by the mitogen-activated protein kinase (MAPK), protein kinase B (Akt), and nuclear factor κB (NF-κB) signaling pathways and expression of inflammatory cytokines in the jejunum. Our results show that OEO promotes intestinal barrier integrity, probably through modulating intestinal bacteria and immune status in pigs. PMID:27314026

  16. Refinement and Selection of Near-native Protein Structures

    NASA Astrophysics Data System (ADS)

    Zhang, Jiong; Zhang, Jingfen; Shang, Yi; Xu, Dong; Kosztin, Ioan

    2013-03-01

    In recent years in silico protein structure prediction reached a level where a variety of servers can generate large pools of near-native structures. However, the identification and further refinement of the best structures from the pool of decoys continue to be problematic. To address these issues, we have developed a selective refinement protocol (based on the Rosetta software package), and a molecular dynamics (MD) simulation based ranking method (MDR). The refinement of the selected structures is done by employing Rosetta's relax mode, subject to certain constraints. The selection of the final best models is done with MDR by testing their relative stability against gradual heating during all atom MD simulations. We have implemented the selective refinement protocol and the MDR method in our fully automated server Mufold-MD. Assessments of the performance of the Mufold-MD server in the CASP10 competition and other tests will be presented. This work was supported by grants from NIH. Computer time was provided by the University of Missouri Bioinformatics Consortium.

  17. Protein designs in HP models

    NASA Astrophysics Data System (ADS)

    Gupta, Arvind; Khodabakhshi, Alireza Hadj; Maňuch, Ján; Rafiey, Arash; Stacho, Ladislav

    2009-07-01

    The inverse protein folding problem is that of designing an amino acid sequence which folds into a prescribed shape. This problem arises in drug design where a particular structure is necessary to ensure proper protein-protein interactions and could have applications in nanotechnology. A major challenge in designing proteins with native folds that attain a specific shape is to avoid proteins that have multiple native folds (unstable proteins). In this technical note we present our results on protein designs in the variant of Hydrophobic-Polar (HP) model introduced by Dill [6] on 2D square lattice. The HP model distinguishes only polar and hydrophobic monomers and only counts the number of hydrophobic contacts in the energy function. To achieve better stability of our designs we use the Hydrophobic-Polar-Cysteine (HPC) model which distinguishes the third type of monomers called "cysteines" and incorporates also the disulfid bridges (SS-bridges) into the energy function. We present stable designs in 2D square lattice and 3D hexagonal prism lattice in the HPC model.

  18. Protein Engineering and Selection Using Yeast Surface Display.

    PubMed

    Angelini, Alessandro; Chen, Tiffany F; de Picciotto, Seymour; Yang, Nicole J; Tzeng, Alice; Santos, Michael S; Van Deventer, James A; Traxlmayr, Michael W; Wittrup, K Dane

    2015-01-01

    Yeast surface display is a powerful technology for engineering a broad range of protein scaffolds. This protocol describes the process for de novo isolation of protein binders from large combinatorial libraries displayed on yeast by using magnetic bead separation followed by flow cytometry-based selection. The biophysical properties of isolated single clones are subsequently characterized, and desired properties are further enhanced through successive rounds of mutagenesis and flow cytometry selections, resulting in protein binders with increased stability, affinity, and specificity for target proteins of interest. PMID:26060067

  19. Selection for Genes Encoding Secreted Proteins and Receptors

    NASA Astrophysics Data System (ADS)

    Klein, Robert D.; Gu, Qimin; Goddard, Audrey; Rosenthal, Arnon

    1996-07-01

    Extracellular proteins play an essential role in the formation, differentiation, and maintenance of multicellular organisms. Despite that, the systematic identification of genes encoding these proteins has not been possible. We describe here a highly efficient method to isolate genes encoding secreted and membrane-bound proteins by using a single-step selection in yeast. Application of this method, termed signal peptide selection, to various tissues yielded 559 clones that appear to encode known or novel extracellular proteins. These include members of the transforming growth factor and epidermal growth factor protein families, endocrine hormones, tyrosine kinase receptors, serine/threonine kinase receptors, seven transmembrane receptors, cell adhesion molecules, extracellular matrix proteins, plasma proteins, and ion channels. The eventual identification of most, or all, extracellular signaling molecules will advance our understanding of fundamental biological processes and our ability to intervene in disease states.

  20. Transition Metal-Free Tryptophan-Selective Bioconjugation of Proteins.

    PubMed

    Seki, Yohei; Ishiyama, Takashi; Sasaki, Daisuke; Abe, Junpei; Sohma, Youhei; Oisaki, Kounosuke; Kanai, Motomu

    2016-08-31

    Chemical modifications of native proteins can facilitate production of supernatural protein functions that are not easily accessible by complementary methods relying on genetic manipulations. However, accomplishing precise control over selectivity while maintaining structural integrity and homogeneity still represents a formidable challenge. Herein, we report a transition metal-free method for tryptophan-selective bioconjugation of proteins that is based on an organoradical and operates under ambient conditions. This method exhibits low levels of cross-reactivity and leaves higher-order structures of the protein and various functional groups therein unaffected. The strategy to target less abundant amino acids contributes to the formation of structurally homogeneous conjugates, which may even be suitable for protein crystallography. The absence of toxic metals and biochemically incompatible conditions allows a rapid functional modulation of native proteins such as antibodies and pathogenic aggregative proteins, and this method may thus easily find therapeutic applications. PMID:27534812

  1. Computational tools for protein modeling.

    PubMed

    Xu, D; Xu, Y; Uberbacher, E C

    2000-07-01

    Protein modeling is playing a more and more important role in protein and peptide sciences due to improvements in modeling methods, advances in computer technology, and the huge amount of biological data becoming available. Modeling tools can often predict the structure and shed some light on the function and its underlying mechanism. They can also provide insight to design experiments and suggest possible leads for drug design. This review attempts to provide a comprehensive introduction to major computer programs, especially on-line servers, for protein modeling. The review covers the following aspects: (1) protein sequence comparison, including sequence alignment/search, sequence-based protein family classification, domain parsing, and phylogenetic classification; (2) sequence annotation, including annotation/prediction of hydrophobic profiles, transmembrane regions, active sites, signaling sites, and secondary structures; (3) protein structure analysis, including visualization, geometry analysis, structure comparison/classification, dynamics, and electrostatics; (4) three-dimensional structure prediction, including homology modeling, fold recognition using threading, ab initio prediction, and docking. We will address what a user can expect from the computer tools in terms of their strengths and limitations. We will also discuss the major challenges and the future trends in the field. A collection of the links of tools can be found at http://compbio.ornl.gov/structure/resource/.

  2. The receptor proteins: pivotal roles in selective autophagy.

    PubMed

    Xu, Zhijie; Yang, Lifang; Xu, San; Zhang, Zhibao; Cao, Ya

    2015-08-01

    Autophagy is a highly regulated and multistep biological process whereby cells under metabolic, proteotoxic, or other stresses remove dysfunctional organelles and/or misfolded/polyubiquitinated proteins by shuttling them via specialized structures called autophagosomes to the lysosome for degradation. Although autophagy is generally considered to be a non-selective process, accumulating evidence suggests that it can also selectively degrade specific target cargoes. These selective targets include proteins, mitochondria, and even invading bacteria. The discovery and characterization of autophagic adapters, such as p62/Sequestosome 1 (SQSTM1) and Neighbor of BRCA1 gene 1 (NBR1), have provided mechanistic insights into selective autophagy. These receptors are all able to act as cargo receptors for the degradation of ubiquitinated substrates. This review mainly summarizes the most up-to-date findings regarding the key receptor proteins that play important roles in regulating selective autophagy.

  3. Fuzzy Clustering-Based Modeling of Surface Interactions and Emulsions of Selected Whey Protein Concentrate Combined to i-Carrageenan and Gum Arabic Solutions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Gums and proteins are valuable ingredients with a wide spectrum of applications. Surface properties (surface tension, interfacial tension, emulsion activity index “EAI” and emulsion stability index “ESI”) of 4% whey protein concentrate (WPC) in a combination with '- carrageenan (0.05%, 0.1%, and 0.5...

  4. Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry.

    PubMed

    Ludwig, Christina; Claassen, Manfred; Schmidt, Alexander; Aebersold, Ruedi

    2012-03-01

    For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the "best flyer" hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R(2) of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM

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

    PubMed

    Rainer, Matthias; Bonn, Günther K

    2015-01-01

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

  6. Development of target protein-selective degradation inducer for protein knockdown.

    PubMed

    Itoh, Yukihiro; Ishikawa, Minoru; Kitaguchi, Risa; Sato, Shinichi; Naito, Mikihiko; Hashimoto, Yuichi

    2011-05-15

    Our previous technique for inducing selective degradation of target proteins with ester-type SNIPER (Specific and Nongenetic Inhibitor-of-apoptosis-proteins (IAPs)-dependent Protein ERaser) degrades both the target proteins and IAPs. Here, we designed a small-molecular amide-type SNIPER to overcome this issue. As proof of concept, we synthesized and biologically evaluated an amide-type SNIPER which induces selective degradation of cellular retinoic acid binding protein II (CRABP-II), but not IAPs. Such small-molecular, amide-type SNIPERs that induce target protein-selective degradation without affecting IAPs should be effective tools to study the biological roles of target proteins in living cells.

  7. Binding-regulated click ligation for selective detection of proteins.

    PubMed

    Cao, Ya; Han, Peng; Wang, Zhuxin; Chen, Weiwei; Shu, Yongqian; Xiang, Yang

    2016-04-15

    Herein, a binding-regulated click ligation (BRCL) strategy for endowing selective detection of proteins is developed with the incorporation of small-molecule ligand and clickable DNA probes. The fundamental principle underlying the strategy is the regulating capability of specific protein-ligand binding against the ligation between clickable DNA probes, which could efficiently combine the detection of particular protein with enormous DNA-based sensing technologies. In this work, the feasibly of the BRCL strategy is first verified through agarose gel electrophoresis and electrochemical impedance spectroscopy measurements, and then confirmed by transferring it to a nanomaterial-assisted fluorescence assay. Significantly, the BRCL strategy-based assay is able to respond to target protein with desirable selectivity, attributing to the specific recognition between small-molecule ligand and its target. Further experiments validate the general applicability of the sensing method by tailoring the ligand toward different proteins (i.e., avidin and folate receptor), and demonstrate its usability in complex biological samples. To our knowledge, this work pioneers the practice of click chemistry in probing specific small-molecule ligand-protein binding, and therefore may pave a new way for selective detection of proteins.

  8. Selective molecular transport through the protein shell of a bacterial microcompartment organelle.

    PubMed

    Chowdhury, Chiranjit; Chun, Sunny; Pang, Allan; Sawaya, Michael R; Sinha, Sharmistha; Yeates, Todd O; Bobik, Thomas A

    2015-03-10

    Bacterial microcompartments are widespread prokaryotic organelles that have important and diverse roles ranging from carbon fixation to enteric pathogenesis. Current models for microcompartment function propose that their outer protein shell is selectively permeable to small molecules, but whether a protein shell can mediate selective permeability and how this occurs are unresolved questions. Here, biochemical and physiological studies of structure-guided mutants are used to show that the hexameric PduA shell protein of the 1,2-propanediol utilization (Pdu) microcompartment forms a selectively permeable pore tailored for the influx of 1,2-propanediol (the substrate of the Pdu microcompartment) while restricting the efflux of propionaldehyde, a toxic intermediate of 1,2-propanediol catabolism. Crystal structures of various PduA mutants provide a foundation for interpreting the observed biochemical and phenotypic data in terms of molecular diffusion across the shell. Overall, these studies provide a basis for understanding a class of selectively permeable channels formed by nonmembrane proteins.

  9. Model selection bias and Freedman's paradox

    USGS Publications Warehouse

    Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.

    2010-01-01

    In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.

  10. IRT Model Selection Methods for Dichotomous Items

    ERIC Educational Resources Information Center

    Kang, Taehoon; Cohen, Allan S.

    2007-01-01

    Fit of the model to the data is important if the benefits of item response theory (IRT) are to be obtained. In this study, the authors compared model selection results using the likelihood ratio test, two information-based criteria, and two Bayesian methods. An example illustrated the potential for inconsistency in model selection depending on…

  11. Selective Uptake and Refolding of Globular Proteins in Coacervate Microdroplets.

    PubMed

    Martin, Nicolas; Li, Mei; Mann, Stephen

    2016-06-14

    Intrinsic differences in the molecular sequestration of folded and unfolded proteins within poly(diallyldimethylammonium) (PDDA)/poly(acrylate) (PAA) coacervate microdroplets are exploited to establish membrane-free microcompartments that support protein refolding, facilitate the recovery of secondary structure and enzyme activity, and enable the selective uptake and exclusion of folded and unfolded biomolecules, respectively. Native bovine serum albumin, carbonic anhydrase, and α-chymotrypsin are preferentially sequestered within positively charged coacervate microdroplets, and the unfolding of these proteins in the presence of increasing amounts of urea results in an exponential decrease in the equilibrium partition constants as well as the kinetic release of unfolded molecules from the droplets into the surrounding continuous phase. Slow refolding in the presence of positively charged microdroplets leads to the resequestration of functional proteins and the restoration of enzymatic activity; however, fast refolding results in protein aggregation at the droplet surface. In contrast, slow and fast refolding in the presence of negatively charged PDDA/PAA droplets gives rise to reduced protein aggregation and misfolding by interactions at the droplet surface to give increased levels of protein renaturation. Together, our observations provide new insights into the bottom-up design and construction of self-assembling microcompartments capable of supporting the selective uptake and refolding of globular proteins.

  12. Photo selective protein immobilization using bovine serum albumin

    NASA Astrophysics Data System (ADS)

    Kim, Wan-Joong; Kim, Ansoon; Huh, Chul; Park, Chan Woo; Ah, Chil Seong; Kim, Bong Kyu; Yang, Jong-Heon; Chung, Kwang Hyo; Choi, Yo Han; Hong, Jongcheol; Sung, Gun Yong

    2012-11-01

    A simple and selective technique which immobilizes protein onto a solid substrate by using UV illumination has been developed. In protein immobilization, a Bovine serum albumin (BSA) performed bifunctional role as a cross-linker between substrate and proteins and as a blocker inhibiting a nonspecific protein adsorption. A new photo-induced protein immobilization process has been investigated at each step by fluorescence microscopy, ellipsometry, and Fourier transform infrared (FT-IR) spectroscopy. A UV photomask has been used to induce selective protein immobilization on target regions of the surface of the SiO2 substrates under UV illumination with negligible nonspecific binding. The UV illumination also showed improved photostability than the conventional methods which employed bifunctional photo-crosslinker molecules of photo-reactive diazirine. This new UV illumination-based photo-addressable protein immobilization provides a new approach for developing novel protein microarrays for multiplexed sensing as well as other types of bio-immobilization in biomedical devices and biotechnologies.

  13. Zeolite Nanoparticles for Selective Sorption of Plasma Proteins

    PubMed Central

    Rahimi, M.; Ng, E.-P.; Bakhtiari, K.; Vinciguerra, M.; Ahmad, H. Ali; Awala, H.; Mintova, S.; Daghighi, M.; Bakhshandeh Rostami, F.; de Vries, M.; Motazacker, M. M.; Peppelenbosch, M. P.; Mahmoudi, M.; Rezaee, F.

    2015-01-01

    The affinity of zeolite nanoparticles (diameter of 8–12 nm) possessing high surface area and high pore volume towards human plasma proteins has been investigated. The protein composition (corona) of zeolite nanoparticles has been shown to be more dependent on the plasma protein concentrations and the type of zeolites than zeolite nanoparticles concentration. The number of proteins present in the corona of zeolite nanoparticles at 100% plasma (in vivo state) is less than with 10% plasma exposure. This could be due to a competition between the proteins to occupy the corona of the zeolite nanoparticles. Moreover, a high selective adsorption for apolipoprotein C-III (APOC-III) and fibrinogen on the zeolite nanoparticles at high plasma concentration (100%) was observed. While the zeolite nanoparticles exposed to low plasma concentration (10%) exhibited a high selective adsorption for immunoglobulin gamma (i.e. IGHG1, IGHG2 and IGHG4) proteins. The zeolite nanoparticles can potentially be used for selectively capture of APOC-III in order to reduce the activation of lipoprotein lipase inhibition during hypertriglyceridemia treatment. The zeolite nanoparticles can be adapted to hemophilic patients (hemophilia A (F-VIII deficient) and hemophilia B (F-IX deficient)) with a risk of bleeding, and thus might be potentially used in combination with the existing therapy. PMID:26616161

  14. Zeolite Nanoparticles for Selective Sorption of Plasma Proteins.

    PubMed

    Rahimi, M; Ng, E-P; Bakhtiari, K; Vinciguerra, M; Ali Ahmad, H; Awala, H; Mintova, S; Daghighi, M; Bakhshandeh Rostami, F; de Vries, M; Motazacker, M M; Peppelenbosch, M P; Mahmoudi, M; Rezaee, F

    2015-01-01

    The affinity of zeolite nanoparticles (diameter of 8-12 nm) possessing high surface area and high pore volume towards human plasma proteins has been investigated. The protein composition (corona) of zeolite nanoparticles has been shown to be more dependent on the plasma protein concentrations and the type of zeolites than zeolite nanoparticles concentration. The number of proteins present in the corona of zeolite nanoparticles at 100% plasma (in vivo state) is less than with 10% plasma exposure. This could be due to a competition between the proteins to occupy the corona of the zeolite nanoparticles. Moreover, a high selective adsorption for apolipoprotein C-III (APOC-III) and fibrinogen on the zeolite nanoparticles at high plasma concentration (100%) was observed. While the zeolite nanoparticles exposed to low plasma concentration (10%) exhibited a high selective adsorption for immunoglobulin gamma (i.e. IGHG1, IGHG2 and IGHG4) proteins. The zeolite nanoparticles can potentially be used for selectively capture of APOC-III in order to reduce the activation of lipoprotein lipase inhibition during hypertriglyceridemia treatment. The zeolite nanoparticles can be adapted to hemophilic patients (hemophilia A (F-VIII deficient) and hemophilia B (F-IX deficient)) with a risk of bleeding, and thus might be potentially used in combination with the existing therapy. PMID:26616161

  15. Zeolite Nanoparticles for Selective Sorption of Plasma Proteins

    NASA Astrophysics Data System (ADS)

    Rahimi, M.; Ng, E.-P.; Bakhtiari, K.; Vinciguerra, M.; Ahmad, H. Ali; Awala, H.; Mintova, S.; Daghighi, M.; Bakhshandeh Rostami, F.; de Vries, M.; Motazacker, M. M.; Peppelenbosch, M. P.; Mahmoudi, M.; Rezaee, F.

    2015-11-01

    The affinity of zeolite nanoparticles (diameter of 8-12 nm) possessing high surface area and high pore volume towards human plasma proteins has been investigated. The protein composition (corona) of zeolite nanoparticles has been shown to be more dependent on the plasma protein concentrations and the type of zeolites than zeolite nanoparticles concentration. The number of proteins present in the corona of zeolite nanoparticles at 100% plasma (in vivo state) is less than with 10% plasma exposure. This could be due to a competition between the proteins to occupy the corona of the zeolite nanoparticles. Moreover, a high selective adsorption for apolipoprotein C-III (APOC-III) and fibrinogen on the zeolite nanoparticles at high plasma concentration (100%) was observed. While the zeolite nanoparticles exposed to low plasma concentration (10%) exhibited a high selective adsorption for immunoglobulin gamma (i.e. IGHG1, IGHG2 and IGHG4) proteins. The zeolite nanoparticles can potentially be used for selectively capture of APOC-III in order to reduce the activation of lipoprotein lipase inhibition during hypertriglyceridemia treatment. The zeolite nanoparticles can be adapted to hemophilic patients (hemophilia A (F-VIII deficient) and hemophilia B (F-IX deficient)) with a risk of bleeding, and thus might be potentially used in combination with the existing therapy.

  16. Development of selective inhibitors for anti-apoptotic Bcl-2 proteins from BHI-1

    PubMed Central

    Xing, Chengguo; Wang, Liangyou; Tang, XiaoHu; Sham, Yuk Y

    2007-01-01

    A series of inhibitors for anti-apoptotic Bcl-2 proteins based on BHI-1 were synthesized and their binding interactions with Bcl-2, Bcl-XL, and Bcl-w were evaluated. It was found that modification of BHI-1 resulted in varied binding profiles among Bcl-2, Bcl-XL, and Bcl-w and a set of inhibitors with varied selectivity to Bcl-2, Bcl-XL, and Bcl-w protein have been identified. Molecular modeling of the interaction of the BHI-1 based analogs with the anti-apoptotic Bcl-2 proteins suggested that the binding site for the BHI-1 based inhibitor was the least conserved section among Bcl-2, Bcl-XL, and Bcl-w: targeting the non-conserved section may account for the observed selectivity of the BHI-1 based inhibitors among the anti-apoptotic Bcl-2 proteins. The validity of the model was supported by a strong correlation between the model-calculated binding energy and the experimental binding affinity. In summary, our studies suggest that most of the reported inhibitors for anti-apoptotic Bcl-2 proteins are nonselective and BHI-1 is a promising template to distinguish among Bcl-2, Bcl-XL, and Bcl-w by targeting the nonconserved domain among the anti-apoptotic Bcl-2 proteins. Molecular-modeling aided rational development of BHI-1 based selective inhibitor for anti-apoptotic Bcl-2 proteins is underway. PMID:17227711

  17. Student learning using the natural selection model

    NASA Astrophysics Data System (ADS)

    Mesmer, Karen Luann

    Students often have difficulty in learning natural selection, a major model in biology. This study examines what middle school students are capable of learning when taught about natural selection using a modeling approach. Students were taught the natural selection model including the components of population, variation, selective advantage, survival, heredity and reproduction. They then used the model to solve three case studies. Their learning was evaluated from responses on a pretest, a posttest and interviews. The results suggest that middle school students can identify components of the natural selection model in a Darwinian explanation, explain the significance of the components and relate them to each other as well as solve evolutionary problems using the model.

  18. Phylogenetic mixture models for proteins.

    PubMed

    Le, Si Quang; Lartillot, Nicolas; Gascuel, Olivier

    2008-12-27

    Standard protein substitution models use a single amino acid replacement rate matrix that summarizes the biological, chemical and physical properties of amino acids. However, site evolution is highly heterogeneous and depends on many factors: genetic code; solvent exposure; secondary and tertiary structure; protein function; etc. These impact the substitution pattern and, in most cases, a single replacement matrix is not enough to represent all the complexity of the evolutionary processes. This paper explores in maximum-likelihood framework phylogenetic mixture models that combine several amino acid replacement matrices to better fit protein evolution.We learn these mixture models from a large alignment database extracted from HSSP, and test the performance using independent alignments from TREEBASE.We compare unsupervised learning approaches, where the site categories are unknown, to supervised ones, where in estimations we use the known category of each site, based on its exposure or its secondary structure. All our models are combined with gamma-distributed rates across sites. Results show that highly significant likelihood gains are obtained when using mixture models compared with the best available single replacement matrices. Mixtures of matrices also improve over mixtures of profiles in the manner of the CAT model. The unsupervised approach tends to be better than the supervised one, but it appears difficult to implement and highly sensitive to the starting values of the parameters, meaning that the supervised approach is still of interest for initialization and model comparison. Using an unsupervised model involving three matrices, the average AIC gain per site with TREEBASE test alignments is 0.31, 0.49 and 0.61 compared with LG (named after Le & Gascuel 2008 Mol. Biol. Evol. 25, 1307-1320), WAG and JTT, respectively. This three-matrix model is significantly better than LG for 34 alignments (among 57), and significantly worse for 1 alignment only. Moreover

  19. Improving Binding Affinity and Selectivity of Computationally Designed Ligand-Binding Proteins Using Experiments.

    PubMed

    Tinberg, Christine E; Khare, Sagar D

    2016-01-01

    The ability to de novo design proteins that can bind small molecules has wide implications for synthetic biology and medicine. Combining computational protein design with the high-throughput screening of mutagenic libraries of computationally designed proteins is emerging as a general approach for creating binding proteins with programmable binding modes, affinities, and selectivities. The computational step enables the creation of a binding site in a protein that otherwise does not (measurably) bind the intended ligand, and targeted mutagenic screening allows for validation and refinement of the computational model as well as provides orders-of-magnitude increases in the binding affinity. Deep sequencing of mutagenic libraries can provide insights into the mutagenic binding landscape and enable further affinity improvements. Moreover, in such a combined computational-experimental approach where the binding mode is preprogrammed and iteratively refined, selectivity can be achieved (and modulated) by the placement of specified amino acid side chain groups around the ligand in defined orientations. Here, we describe the experimental aspects of a combined computational-experimental approach for designing-using the software suite Rosetta-proteins that bind a small molecule of choice and engineering, using fluorescence-activated cell sorting and high-throughput yeast surface display, high affinity and ligand selectivity. We illustrated the utility of this approach by performing the design of a selective digoxigenin (DIG)-binding protein that, after affinity maturation, binds DIG with picomolar affinity and high selectivity over structurally related steroids. PMID:27094290

  20. A Computational Model of Selection by Consequences

    ERIC Educational Resources Information Center

    McDowell, J. J.

    2004-01-01

    Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of…

  1. Fast infrared spectroscopy of protein dynamics: advancing sensitivity and selectivity.

    PubMed

    Koziol, Klemens L; Johnson, Philip J M; Stucki-Buchli, Brigitte; Waldauer, Steven A; Hamm, Peter

    2015-10-01

    2D-IR spectroscopy has matured to a powerful technique to study the structure and dynamics of peptides, but its extension to larger proteins is still in its infancy, the major limitations being sensitivity and selectivity. Site-selective information requires measuring single vibrational probes at sub-millimolar concentrations where most proteins are still stable, which is a severe challenge for conventional (FT)IR spectroscopy. Besides its ultrafast time-resolution, a so far largely underappreciated potential of 2D-IR spectroscopy lies in its sensitivity gain. The present paper sets the goals and outlines strategies how to use that sensitivity gain together with properly designed vibrational labels to make IR spectroscopy a versatile tool to study a wide class of proteins.

  2. Heterogeneity and restricted state selection in FRET with fluorescent proteins

    NASA Astrophysics Data System (ADS)

    Blacker, T. S.; Duchen, M. R.; Bain, A. J.

    2016-02-01

    Most fluorescent proteins exhibit multi-exponential fluorescence decays, indicating the presence of a heterogeneous excited state population. In the analysis of FRET to and between fluorescent proteins, it is often convenient to assume that a single interaction pathway is involved. However, in recent work we have shown that this assumption does not hold. Moreover, certain pathways can be highly constrained, leading to the potential misinterpretation of experimental data concerning protein-protein interactions. FRET and single-photon absorption both obey the same global electric dipole selection rules but differ greatly in the mechanism of the acceptor photoselection. In an isotropic medium, single-photon excitation accesses all acceptor transition dipole moment orientations with an equal probability. However, the FRET rate depends on the relative orientation of the donor and acceptor through the κ2 orientation parameter. We show how time- and spectrally- resolved fluorescence intensity and anisotropy decay measurements following direct acceptor excitation, combined with those of the interacting FRET pair, can be used to identify restricted FRET state selection and thus provide accurate measurements of protein-protein interaction dynamics.

  3. Improving a consensus approach for protein structure selection by removing redundancy.

    PubMed

    Wang, Qingguo; Shang, Yi; Xu, Dong

    2011-01-01

    In protein tertiary structure prediction, a crucial step is to select near-native structures from a large number of predicted structural models. Over the years, extensive research has been conducted for the protein structure selection problem with most approaches focusing on developing more accurate energy or scoring functions. Despite significant advances in this area, the discerning power of current approaches is still unsatisfactory. In this paper, we propose a novel consensus-based algorithm for the selection of predicted protein structures. Given a set of predicted models, our method first removes redundant structures to derive a subset of reference models. Then, a structure is ranked based on its average pairwise similarity to the reference models. Using the CASP8 data set containing a large collection of predicted models for 122 targets, we compared our method with the best CASP8 quality assessment (QA) servers, which are all consensus based, and showed that our QA scores correlate better with the GDT-TSs than those of the CASP8 QA servers. We also compared our method with the state-of-the-art scoring functions and showed its improved performance for near-native model selection. The GDT-TSs of the top models picked by our method are on average more than 8 percent better than the ones selected by the best performing scoring function. PMID:21519117

  4. Computational modeling of membrane proteins

    PubMed Central

    Leman, Julia Koehler; Ulmschneider, Martin B.; Gray, Jeffrey J.

    2014-01-01

    The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefitted from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. PMID:25355688

  5. Nanodiscs allow phage display selection for ligands to non-linear epitopes on membrane proteins.

    PubMed

    Pavlidou, Marina; Hänel, Karen; Möckel, Luis; Willbold, Dieter

    2013-01-01

    In this work, we exploited a method that uses polytopic membrane proteins as targets for phage display selections. Membrane proteins represent the largest class of drug targets and drug discovery is mostly based on the identification of ligands binding to target molecules. The screening of a phage display library for ligands against membrane proteins is typically hindered by the requirement of these proteins for a membrane environment, which is necessary to retain correct folding and epitope formation. Especially in proteins with multiple transmembrane domains, epitopes often are non-linear and consist of a combination of loops between transmembrane stretches of the proteins. Here, we have used bacteriorhodopsin (bR) as a model of polytopic membrane protein, assembled into nanoscale phospholipid bilayers, so called nanodiscs, to screen a phage display library for potential ligands. Nanodiscs provide a native-like environment to membrane proteins and thus selection of ligands can take place in a near physiological state. Screening a 12-mer phage display peptide library against bR nanodiscs led to the isolation of phage clones binding specifically to bR. We were further able to identify the binding site of selected phage clones proving that the clones bind to extramembranous, non-linear epitopes of bR. Thus, nanodiscs provide a suitable and general tool that allows screening of a phage display library against membrane proteins in a near native environment.

  6. A selection that reports on protein-protein interactions within a thermophilic bacterium.

    PubMed

    Nguyen, Peter Q; Silberg, Jonathan J

    2010-07-01

    Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions. PMID:20418388

  7. Modeling HIV-1 drug resistance as episodic directional selection.

    PubMed

    Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

    2012-01-01

    The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

  8. Model selection for amplitude analysis

    NASA Astrophysics Data System (ADS)

    Guegan, B.; Hardin, J.; Stevens, J.; Williams, M.

    2015-09-01

    Model complexity in amplitude analyses is often a priori under-constrained since the underlying theory permits a large number of possible amplitudes to contribute to most physical processes. The use of an overly complex model results in reduced predictive power and worse resolution on unknown parameters of interest. Therefore, it is common to reduce the complexity by removing from consideration some subset of the allowed amplitudes. This paper studies a method for limiting model complexity from the data sample itself through regularization during regression in the context of a multivariate (Dalitz-plot) analysis. The regularization technique applied greatly improves the performance. An outline of how to obtain the significance of a resonance in a multivariate amplitude analysis is also provided.

  9. A General Method for Insertion of Functional Proteins within Proteins via Combinatorial Selection of Permissive Junctions.

    PubMed

    Peng, Yingjie; Zeng, Wenwen; Ye, Hui; Han, Kyung Ho; Dharmarajan, Venkatasubramanian; Novick, Scott; Wilson, Ian A; Griffin, Patrick R; Friedman, Jeffrey M; Lerner, Richard A

    2015-08-20

    A major goal of modern protein chemistry is to create new proteins with different functions. One approach is to amalgamate secondary and tertiary structures from different proteins. This is difficult for several reasons, not the least of which is the fact that the junctions between secondary and tertiary structures are not degenerate and usually affect the function and folding of the entire complex. Here, we offer a solution to this problem by coupling a large combinatorial library of about 10(7) different N- and C-terminal junctions to a powerful system that selects for function. Using this approach, the entire Leptin and follicle-stimulating hormone (FSH) were inserted into an antibody. Complexes with full retention of function in vivo and in vitro, although rare, were found easily by using an autocrine selection system to search for hormonal activity. Such large diversity systems, when coupled to robust selection systems, should enable construction of novel therapeutic proteins.

  10. Steric selectivity in Na channels arising from protein polarization and mobile side chains.

    PubMed

    Boda, Dezso; Nonner, Wolfgang; Valiskó, Mónika; Henderson, Douglas; Eisenberg, Bob; Gillespie, Dirk

    2007-09-15

    Monte Carlo simulations of equilibrium selectivity of Na channels with a DEKA locus are performed over a range of radius R and protein dielectric coefficient epsilon(p). Selectivity arises from the balance of electrostatic forces and steric repulsion by excluded volume of ions and side chains of the channel protein in the highly concentrated and charged (approximately 30 M) selectivity filter resembling an ionic liquid. Ions and structural side chains are described as mobile charged hard spheres that assume positions of minimal free energy. Water is a dielectric continuum. Size selectivity (ratio of Na+ occupancy to K+ occupancy) and charge selectivity (Na+ to Ca2+) are computed in concentrations as low as 10(-5) M Ca2+. In general, small R reduces ion occupancy and favors Na+ over K+ because of steric repulsion. Small epsilon(p) increases occupancy and favors Na+ over Ca2+ because protein polarization amplifies the pore's net charge. Size selectivity depends on R and is independent of epsilon(p); charge selectivity depends on both R and epsilon(p). Thus, small R and epsilon(p) make an efficient Na channel that excludes K+ and Ca2+ while maximizing Na+ occupancy. Selectivity properties depend on interactions that cannot be described by qualitative or verbal models or by quantitative models with a fixed free energy landscape. PMID:17526571

  11. Constrained Selected Reaction Monitoring: Quantification of selected post-translational modifications and protein isoforms

    PubMed Central

    Liu, Xiaoqian; Jin, Zhicheng; O’Brien, Richard; Bathon, Joan; Dietz, Harry C.; Grote, Eric; Van Eyk, Jennifer E.

    2014-01-01

    Selected reaction monitoring (SRM) is a mass spectrometry method that can target signature peptides to provide for the detection and quantitation of specific proteins in complex biological samples. When quantifying a protein, peptides are generated using a specific protease such as trypsin, allowing the choice of signature peptides with robust signals. In contrast, signature peptide selection can be constrained when the goal is to monitor a specific post-translational modification (PTM) or protein isoform as the signature peptide must include the amino acid residue(s) of PTM attachment or sequence variation. This can force the selection of a signature peptide with a weak SRM response or one that is confounded by high background. In this article, additional steps that can be optimized to maximize peptide selection and assay performance of constrained SRM assays are discussed including tuning instrument parameters, fragmenting product ions, using a different protease, and enriching the sample. Examples are provided for selection of phosphorylated or citrullinated peptides and protein isoforms. PMID:23523700

  12. Karyoplasmic interaction selection strategy: a general strategy to detect protein-protein interactions in mammalian cells.

    PubMed Central

    Fearon, E R; Finkel, T; Gillison, M L; Kennedy, S P; Casella, J F; Tomaselli, G F; Morrow, J S; Van Dang, C

    1992-01-01

    We describe a strategy and reagents for study of protein-protein interactions in mammalian cells, termed the karyoplasmic interaction selection strategy (KISS). With this strategy, specific protein-protein interactions are identified by reconstitution of the functional activity of the yeast transcriptional activator GAL4 and the resultant transcription of a GAL4-regulated reporter gene. Reconstitution of GAL4 function results from specific interaction between two chimeric proteins: one contains the DNA-binding domain of GAL4; the other contains a transcriptional activation domain. Transcription of the reporter gene occurs if the two chimeric proteins can form a complex that reconstitutes the DNA-binding and transcriptional activation functions of GAL4. Using the KISS system, we demonstrate specific interactions for sequences from three different pairs of proteins that complex in the cytoplasm. In addition, we demonstrate that reporter genes encoding cell surface or drug-resistance markers can be specifically activated as a result of protein-protein interactions. With these selectable markers, the KISS system can be used to screen specialized cDNA libraries to identify novel protein interactions. Images PMID:1387709

  13. Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring*

    PubMed Central

    Lawless, Craig; Holman, Stephen W.; Brownridge, Philip; Lanthaler, Karin; Harman, Victoria M.; Watkins, Rachel; Hammond, Dean E.; Miller, Rebecca L.; Sims, Paul F. G.; Grant, Christopher M.; Eyers, Claire E.; Beynon, Robert J.

    2016-01-01

    Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. PMID:26750110

  14. Coarsening of protein clusters on subcellular drops exhibits strong and sudden size selectivity

    NASA Astrophysics Data System (ADS)

    Brown, Aidan; Rutenberg, Andrew

    2015-03-01

    Autophagy is an important process for the degradation of cellular components, with receptor proteins targeting substrates to downstream autophagy machinery. An important question is how receptor protein interactions lead to their selective accumulation on autophagy substrates. Receptor proteins have recently been observed in clusters, raising the possibility that clustering could affect autophagy selectivity. We investigate the clustering dynamics of the autophagy receptor protein NBR1. In addition to standard receptor protein domains, NBR1 has a ``J'' domain that anchors it to membranes, and a coiled-coil domain that enhances self-interaction. We model coarsening clusters of NBR1 on the surfaces of a polydisperse collection of drops, representing organelles. Despite the disconnected nature of the drop surfaces, we recover dynamical scaling of cluster sizes. Significantly, we find that at a well-defined time after coarsening begins, clusters evaporate from smaller drops and grow on larger drops. Thus, coarsening-driven size selection will localize protein clusters to larger substrates, leaving smaller substrates without clusters. This provides a possible physical mechanism for autophagy selectivity, and can explain reports of size selection during peroxisome degradation.

  15. Selective Inhibition on RAGE-binding AGEs Required by Bioactive Peptide Alpha-S2 Case in Protein from Goat Ethawah Breed Milk: Study of Biological Modeling

    PubMed Central

    Fatchiyah, Fatchiyah; Hardiyanti, Ferlany; Widodo, Nashi

    2015-01-01

    Background: Advanced Glycation End Products (AGE) play a pivotal role in the development various degenerative diseases such as diabetes, cardiovascular disease, stroke, neuropathy, and nephropathy. Different studies have been done to employ AGEs as drug targets for the diseases therapy. In previous study, we have found bioactive peptide from Ethawah goat milk for anti-diabetic that may work through inhibition of AGE receptor function. However, the mechanism of bioactive peptides inhibits AGE- AGE receptor (RAGE) bonding still not clear yet. Therefore we investigated the inhibition mechanism by calculate the potential energy binding among the peptides, AGEs and RAGE using molecular docking system. Methods: Modeling 3D-structure was predicted by SWISS-MODEL web server. The virtual interaction was analyzed by docking system using HEX 8.0, Pymol and Discovery Studio 4.0 software. Results: this study showed that AGEs (Argypirimidine, Imidazole, Pentosidine and Pyrraline) bind to C-domain of RAGE. The total energy binding of RAGE with Argypirimidine, Imidazole, Pentosidine and Pyrraline were 378.35kJ/mol, -74.57kJ/mol, -301.25kJ/mol and -400.72kJ/mol, respectively. We have found three peptides among eight peptides from Ethawah goat milk, which are able bind to C-domain of RAGE, there are CSN1S2 f41-47, CSN1S2 f182-189, and CSN1S2 f214-221. The CSN1S22 f41-47 at arginine residue 47 interacts with proline162, leusine163 and leusine158 of RAGE. The total binding energy between CSN1S2 f41-47, CSN1S2 f182-189, and CSN1S2 f214-221 with RAGE were -378.35 kJ/mol, -359.97kJ/mol, -356.78 kJ/mol, respectively. Total binding energy and binding pattern indicated that RAGE more prefer bind with peptide and block AGE bind to functional site of RAGE. Further analysis showed that complex peptide-RAGE shifted binding site of AGE on function domain RAGE. Conclusion: This study suggested that the peptides from Ethawah goat milk may act as an inhibitor of AGEs-RAGE interaction that impaired

  16. Study of protein complexes via homology modeling, applied to cysteine proteases and their protein inhibitors.

    PubMed

    Tastan Bishop, Ozlem; Kroon, Matthys

    2011-12-01

    This paper develops and evaluates large-scale calculation of 3D structures of protein complexes by homology modeling as a promising new approach for protein docking. The complexes investigated were papain-like cysteine proteases and their protein inhibitors, which play numerous roles in human and parasitic metabolisms. The structural modeling was performed in two parts. For the first part (evaluation set), nine crystal structure complexes were selected, 1325 homology models of known complexes were rebuilt by various templates including hybrids, allowing an analysis of the factors influencing the accuracy of the models. The important considerations for modeling the interface were protease coverage and inhibitor sequence identity. In the second part (study set), the findings of the evaluation set were used to select appropriate templates to model novel cysteine protease-inhibitor complexes from human and malaria parasites Plasmodium falciparum and Plasmodium vivax. The energy scores, considering the evaluation set, indicate that the models are of high accuracy. PMID:21365221

  17. The Ouroboros Model, selected facets.

    PubMed

    Thomsen, Knud

    2011-01-01

    The Ouroboros Model features a biologically inspired cognitive architecture. At its core lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. The activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed 'consumption analysis' is then checking how well such expectations fit with successive activations. Mismatches between anticipations based on previous experience and actual current data are highlighted and used for controlling the allocation of attention. A measure for the goodness of fit provides feedback as (self-) monitoring signal. The basic algorithm works for goal directed movements and memory search as well as during abstract reasoning. It is sketched how the Ouroboros Model can shed light on characteristics of human behavior including attention, emotions, priming, masking, learning, sleep and consciousness.

  18. A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

    PubMed Central

    Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.

    2013-01-01

    Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555

  19. Riboflavin-binding protein exhibits selective sweet suppression toward protein sweeteners.

    PubMed

    Maehashi, Kenji; Matano, Mami; Kondo, Azusa; Yamamoto, Yasushi; Udaka, Shigezo

    2007-02-01

    Riboflavin-binding protein (RBP) is well known as a riboflavin carrier protein in chicken egg and serum. A novel function of RBP was found as a sweet-suppressing protein. RBP, purified from hen egg white, suppressed the sweetness of protein sweeteners such as thaumatin, monellin, and lysozyme, whereas it did not suppress the sweetness of low molecular weight sweeteners such as sucrose, glycine, D-phenylalanine, saccharin, cyclamate, aspartame, and stevioside. Therefore, the sweet-suppressing activity of RBP was apparently selective to protein sweeteners. The sweet suppression by RBP was independent of binding of riboflavin with its molecule. Yolk RBP, with minor structural differences compared with egg white RBP, also elicited a weaker sweet suppression. However, other commercially available proteins including ovalbumin, ovomucoid, beta-lactogloblin, myoglobin, and albumin did not substantially alter the sweetness of protein sweeteners. Because a prerinse with RBP reduced the subsequent sweetness of protein sweeteners, whereas the enzymatic activity of lysozyme and the elution profile of lysozyme on gel permeation chromatography were not affected by RBP, it is suggested that the sweet suppression is caused by an interaction of RBP with a sweet taste receptor rather than with the protein sweeteners themselves. The selectivity in the sweet suppression by RBP is consistent with the existence of multiple interaction sites within a single sweet taste receptor.

  20. Detergent selection for enhanced extraction of membrane proteins.

    PubMed

    Arachea, Buenafe T; Sun, Zhen; Potente, Nina; Malik, Radhika; Isailovic, Dragan; Viola, Ronald E

    2012-11-01

    Generating stable conditions for membrane proteins after extraction from their lipid bilayer environment is essential for subsequent characterization. Detergents are the most widely used means to obtain this stable environment; however, different types of membrane proteins have been found to require detergents with varying properties for optimal extraction efficiency and stability after extraction. The extraction profiles of several detergent types have been examined for membranes isolated from bacteria and yeast, and for a set of recombinant target proteins. The extraction efficiencies of these detergents increase at higher concentrations, and were shown to correlate with their respective CMC values. Two alkyl sugar detergents, octyl-β-d-glucoside (OG) and 5-cyclohexyl-1-pentyl-β-d-maltoside (Cymal-5), and a zwitterionic surfactant, N-decylphosphocholine (Fos-choline-10), were generally effective in the extraction of a broad range of membrane proteins. However, certain detergents were more effective than others in the extraction of specific classes of integral membrane proteins, offering guidelines for initial detergent selection. The differences in extraction efficiencies among this small set of detergents supports the value of detergent screening and optimization to increase the yields of targeted membrane proteins.

  1. Adaptive Modeling Procedure Selection by Data Perturbation*

    PubMed Central

    Zhang, Yongli; Shen, Xiaotong

    2015-01-01

    Summary Many procedures have been developed to deal with the high-dimensional problem that is emerging in various business and economics areas. To evaluate and compare these procedures, modeling uncertainty caused by model selection and parameter estimation has to be assessed and integrated into a modeling process. To do this, a data perturbation method estimates the modeling uncertainty inherited in a selection process by perturbing the data. Critical to data perturbation is the size of perturbation, as the perturbed data should resemble the original dataset. To account for the modeling uncertainty, we derive the optimal size of perturbation, which adapts to the data, the model space, and other relevant factors in the context of linear regression. On this basis, we develop an adaptive data-perturbation method that, unlike its nonadaptive counterpart, performs well in different situations. This leads to a data-adaptive model selection method. Both theoretical and numerical analysis suggest that the data-adaptive model selection method adapts to distinct situations in that it yields consistent model selection and optimal prediction, without knowing which situation exists a priori. The proposed method is applied to real data from the commodity market and outperforms its competitors in terms of price forecasting accuracy. PMID:26640319

  2. Review and selection of unsaturated flow models

    SciTech Connect

    Reeves, M.; Baker, N.A.; Duguid, J.O.

    1994-04-04

    Since the 1960`s, ground-water flow models have been used for analysis of water resources problems. In the 1970`s, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970`s and well into the 1980`s focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M&O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing.

  3. Model Selection with the Linear Mixed Model for Longitudinal Data

    ERIC Educational Resources Information Center

    Ryoo, Ji Hoon

    2011-01-01

    Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

  4. Selection on rapidly evolving proteins in the Arabidopsis genome.

    PubMed Central

    Barrier, Marianne; Bustamante, Carlos D; Yu, Jiaye; Purugganan, Michael D

    2003-01-01

    Genes that have undergone positive or diversifying selection are likely to be associated with adaptive divergence between species. One indicator of adaptive selection at the molecular level is an excess of amino acid replacement fixed differences per replacement site relative to the number of synonymous fixed differences per synonymous site (omega = K(a)/K(s)). We used an evolutionary expressed sequence tag (EST) approach to estimate the distribution of omega among 304 orthologous loci between Arabidopsis thaliana and A. lyrata to identify genes potentially involved in the adaptive divergence between these two Brassicaceae species. We find that 14 of 304 genes (approximately 5%) have an estimated omega > 1 and are candidates for genes with increased selection intensities. Molecular population genetic analyses of 6 of these rapidly evolving protein loci indicate that, despite their high levels of between-species nonsynonymous divergence, these genes do not have elevated levels of intraspecific replacement polymorphisms compared to previously studied genes. A hierarchical Bayesian analysis of protein-coding region evolution within and between species also indicates that the selection intensities of these genes are elevated compared to previously studied A. thaliana nuclear loci. PMID:12618409

  5. Applying conformational selection theory to improve crossdocking efficiency in 3-phosphoinositide dependent protein kinase-1.

    PubMed

    Kotasthane, Anuja; Mulakala, Chandrika; Viswanadhan, Vellarkad N

    2014-03-01

    The emerging picture of biomolecular recognition is that of conformational selection followed by induced-fit. Conformational selection theory states that binding partners exist in various conformations in solution, with binding involving a "selection" between complementary conformers. In this study, we devise a docking protocol that mimics conformational selection in protein-ligand binding and demonstrate that it significantly enhances crossdocking accuracy over Glide's flexible docking protocol, which is widely used in the pharmaceutical industry. Our protocol uses a pregenerated conformational ensemble to simulate ligand flexibility. The ensemble was generated by thorough conformational sampling coupled with conformer minimization. The generated conformers were then rigidly docked in the active site of the protein along with a postdocking minimization step that allows limited induced fit effects to be modeled for the ligand. We illustrate the improved performance of our protocol through crossdocking of 31 ligands to cocomplexed proteins of the kinase 3-phosphoinositide dependent protein kinase-1 extracted from the crystal structures 1H1W (ATP bound), 1OKY (staurosporine bound) and 3QD0 (bound to a potent inhibitor). Consistent with conformational selection theory, the performance of our protocol was the best for crossdocking to the cognate protein bound to the natural ligand, ATP.

  6. Kinetic rate constant prediction supports the conformational selection mechanism of protein binding.

    PubMed

    Moal, Iain H; Bates, Paul A

    2012-01-01

    The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.

  7. Desired Alteration of Protein Affinities: Competitive Selection of Protein Variants Using Yeast Signal Transduction Machinery

    PubMed Central

    Kaishima, Misato; Fukuda, Nobuo; Ishii, Jun; Kondo, Akihiko

    2014-01-01

    Molecules that can control protein-protein interactions (PPIs) have recently drawn attention as new drug pipeline compounds. Here, we report a technique to screen desirable affinity-altered (affinity-enhanced and affinity-attenuated) protein variants. We previously constructed a screening system based on a target protein fused to a mutated G-protein γ subunit (Gγcyto) lacking membrane localization ability. This ability, required for signal transmission, is restored by recruiting Gγcyto into the membrane only when the target protein interacts with an artificially membrane-anchored candidate protein, thereby allowing interacting partners (Gγ recruitment system) to be searched and identified. In the present study, the Gγ recruitment system was altered by integrating the cytosolic expression of a third protein as a competitor to set a desirable affinity threshold. This enabled the reliable selection of both affinity-enhanced and affinity-attenuated protein variants. The presented approach may facilitate the development of therapeutic proteins that allow the control of PPIs. PMID:25244640

  8. Protein efficiency ratios and net protein ratios of selected protein foods.

    PubMed

    Mitchell, G V; Jenkins, M Y; Grundel, E

    1989-01-01

    As a part of a cooperative study initiated to assess both in vitro and in vivo protein quality methods, the protein efficiency ratio (PER) and net protein ratios (NPR) of 15 different protein sources were determined. Male weanling Sprague-Dawley rats were fed a 10% protein diet. Fourteen-day NPR and relative NPR (RNPR) values and 14- and 28-day PER and relative PER (RPER) values were calculated for each protein source. When protein quality values were expressed relative to ANRC casein, the 14- and 28-day PER data ranked the protein sources essentially in the same order. RPER values of nonfat dried skim milk (unheated) and tuna were more than 100% that of casein; nonfat dried skim milk (heated), chickpeas, and breakfast sausage were between 50 and 70% of that of casein; and pinto beans and rice-wheat gluten cereal did not support substantial growth of the rat. The NPR method did not always rank the protein sources in the same order as the PER method. For the poor quality proteins, RNPR values were much higher than the RPER values; however, the RNPR and RPER values agreed closely for high quality protein sources. PMID:2710752

  9. A sensorimotor paradigm for Bayesian model selection.

    PubMed

    Genewein, Tim; Braun, Daniel A

    2012-01-01

    Sensorimotor control is thought to rely on predictive internal models in order to cope efficiently with uncertain environments. Recently, it has been shown that humans not only learn different internal models for different tasks, but that they also extract common structure between tasks. This raises the question of how the motor system selects between different structures or models, when each model can be associated with a range of different task-specific parameters. Here we design a sensorimotor task that requires subjects to compensate visuomotor shifts in a three-dimensional virtual reality setup, where one of the dimensions can be mapped to a model variable and the other dimension to the parameter variable. By introducing probe trials that are neutral in the parameter dimension, we can directly test for model selection. We found that model selection procedures based on Bayesian statistics provided a better explanation for subjects' choice behavior than simple non-probabilistic heuristics. Our experimental design lends itself to the general study of model selection in a sensorimotor context as it allows to separately query model and parameter variables from subjects. PMID:23125827

  10. Polarizable protein model for Dissipative Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Peter, Emanuel; Lykov, Kirill; Pivkin, Igor

    2015-11-01

    In this talk, we present a novel polarizable protein model for the Dissipative Particle Dynamics (DPD) simulation technique, a coarse-grained particle-based method widely used in modeling of fluid systems at the mesoscale. We employ long-range electrostatics and Drude oscillators in combination with a newly developed polarizable water model. The protein in our model is resembled by a polarizable backbone and a simplified representation of the sidechains. We define the model parameters using the experimental structures of 2 proteins: TrpZip2 and TrpCage. We validate the model on folding of five other proteins and demonstrate that it successfully predicts folding of these proteins into their native conformations. As a perspective of this model, we will give a short outlook on simulations of protein aggregation in the bulk and near a model membrane, a relevant process in several Amyloid diseases, e.g. Alzheimer's and Diabetes II.

  11. Modeling mitochondrial protein evolution using structural information.

    PubMed

    Liò, Pietro; Goldman, Nick

    2002-04-01

    We present two new models of protein sequence evolution based on structural properties of mitochondrial proteins. We compare these models with others currently used in phylogenetic analyses, investigating their performance over both short and long evolutionary distances. We find that our models that incorporate secondary structure information from mitochondrial proteins are statistically comparable with existing models when studying 13 mitochondrial protein data sets from eutherian mammals. However, our models give a significantly improved description of the evolutionary process when used with 12 mitochondrial proteins from a broader range of organisms including fungi, plants, protists, and bacteria. Our models may thus be of use in estimating mitochondrial protein phylogenies and for the study of processes of mitochondrial protein evolution, in particular for distantly related organisms.

  12. An experimental framework for improved selection of binding proteins using SNAP display.

    PubMed

    Houlihan, Gillian; Gatti-Lafranconi, Pietro; Kaltenbach, Miriam; Lowe, David; Hollfelder, Florian

    2014-03-01

    Display technologies (e.g. phage and ribosome display) are powerful tools for selecting and evolving protein binders against various target molecules. SNAP display is a DNA display technology that is conducted entirely in vitro: DNA encoding a library of variants is encapsulated in water-in-oil droplets wherein in vitro protein expression and covalent coupling to the encoding DNA occurs. Here, we explore critical factors for the successful performance of SNAP display based on a set of experiments designed to measure and quantify to what extent they affect selection efficiency. We find that, in SNAP display, the reconstituted cell free expression system PURExpress led to 1.5-fold more active protein and achieved 3.5-fold greater DNA recovery in model selections compared to the RTS 100 Escherichia coli lysate based expression system. We report on the influence parameters including droplet occupancy, valency and selection stringency have on recovery and enrichment. An improved procedure involving bivalent display and stringent selection against a model target, Her2, led to a 10(7)-fold enrichment of a DARPin (H10-2-G3, known to bind Her2 with picomolar affinity) over a non-binding DARPin after three rounds of selection. Furthermore, when spiked into a mixture of DARPins with different affinities, DARPin H10-2-G3 outcompeted all other variants demonstrating SNAP display's ability to efficiently resolve clones with affinities in the nano- to picomolar range. These data establish SNAP display as an in vitro protein engineering tool for isolating protein binders and provide a framework for troubleshooting affinity selections.

  13. Melody Track Selection Using Discriminative Language Model

    NASA Astrophysics Data System (ADS)

    Wu, Xiao; Li, Ming; Suo, Hongbin; Yan, Yonghong

    In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.

  14. Multiscale modelling of ovarian follicular selection.

    PubMed

    Clément, Frédérique; Monniaux, Danielle

    2013-12-01

    In mammals, the number of ovulations at each ovarian cycle is determined during the terminal phase of follicular development by a tightly controlled follicle selection process. The mechanisms underlying follicle selection take place on different scales and different levels of the gonadotropic axis. These include the endocrine loops between the ovary and the hypothalamic-pituitary complex, the dynamics of follicle populations within the ovary and the dynamics of cell populations within ovarian follicles. A compartmental modelling approach was first designed to describe the cell dynamics in the selected follicle. It laid the basis for a multiscale model formulated with partial differential equations of conservation law type, resulting in the structuring of the follicular cell populations according to cell age and cell maturity. In this model, the selection occurs as a FSH (follicle stimulating hormone)-driven competition between simultaneously developing follicles. The selection output (mono-ovulation, poly-ovulation or anovulation) results from a subtle interplay between the hypothalamus, the pituitary gland and the ovaries, combined with slight differences in the initial conditions or ageing and maturation velocities of the competing follicles. This modelling approach is proposed as a useful complement to experimental studies of follicular development and in turn, the mechanisms of follicle selection raise challenging questions on the mathematical ground.

  15. An Ss Model with Adverse Selection.

    ERIC Educational Resources Information Center

    House, Christopher L.; Leahy, John V.

    2004-01-01

    We present a model of the market for a used durable in which agents face fixed costs of adjustment, the magnitude of which depends on the degree of adverse selection in the secondary market. We find that, unlike typical models, the sS bands in our model contract as the variance of the shock increases. We also analyze a dynamic version of the model…

  16. On the elementary processes of protein crystallization: Bond selection mechanism

    NASA Astrophysics Data System (ADS)

    Nanev, Christo N.

    2014-09-01

    The paper explores the application of bond selection mechanism (BSM) in protein crystal growth; previously, BSM was employed to explain the slow rate of protein crystal nucleation, equilibrium crystal shape and energy barrier in nucleus formation (C.N. Nanev, Prog. Cryst. Growth Charact. Mater. 59 (2013) 133-169). Now, the elementary growth processes are considered from BSM perspective and the crystal growth shape is tackled, the latter resulting from a strong directional kinetic anisotropy in step advancement rates in different crystallographic directions. The most significant surface patterns of growing protein crystals, such as two-dimensional nuclei and growth spiral shapes observed by atomic force microscopy (AFM), are also considered. The activation barrier associated with entering of a protein molecule into the kink site is evaluated and the start of the kinetic roughening is established. Crystal lattice bond energies are estimated (being well above the thermal energy, kBT) from the supersaturation dependence of 2D- into 1D-nuclei transformation.

  17. Maltodextrin-modified magnetic microspheres for selective enrichment of maltose binding proteins.

    PubMed

    Zheng, Jin; Ma, Chongjun; Sun, Yangfei; Pan, Miaorong; Li, Li; Hu, Xiaojian; Yang, Wuli

    2014-03-12

    In this work, maltodextrin-modified magnetic microspheres Fe3O4@SiO2-Maltodextrin (Fe3O4@SiO2-MD) with uniform size and fine morphology were synthesized through a facile and low-cost method. As the maltodextrins on the surface of microspheres were combined with maltose binding proteins (MBP), the magnetic microspheres could be applied to enriching standard MBP fused proteins. Then, the application of Fe3O4@SiO2-MD in one-step purification and immobilization of MBP fused proteins was demonstrated. For the model protein we examined, Fe3O4@SiO2-MD showed excellent binding selectivity and capacity against other Escherichia coli proteins in the crude cell lysate. Additionally, the maltodextrin-modified magnetic microspheres can be recycled for several times without significant loss of binding capacity.

  18. Automated sample plan selection for OPC modeling

    NASA Astrophysics Data System (ADS)

    Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

    2014-03-01

    It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

  19. Selective Blockade of Trypanosomatid Protein Synthesis by a Recombinant Antibody Anti-Trypanosoma cruzi P2β Protein

    PubMed Central

    Simonetti, Leandro; Duffy, Tomas; Longhi, Silvia A.; Gómez, Karina A.; Hoebeke, Johan; Levin, Mariano J.; Smulski, Cristian R.

    2012-01-01

    The ribosomal P proteins are located on the stalk of the ribosomal large subunit and play a critical role during the elongation step of protein synthesis. The single chain recombinant antibody C5 (scFv C5) directed against the C-terminal region of the Trypanosoma cruzi P2β protein (TcP2β) recognizes the conserved C-terminal end of all T. cruzi ribosomal P proteins. Although this region is highly conserved among different species, surface plasmon resonance analysis showed that the scFv C5 possesses very low affinity for the corresponding mammalian epitope, despite having only one single amino-acid change. Crystallographic analysis, in silico modelization and NMR assays support the analysis, increasing our understanding on the structural basis of epitope specificity. In vitro protein synthesis experiments showed that scFv C5 was able to specifically block translation by T. cruzi and Crithidia fasciculata ribosomes, but virtually had no effect on Rattus norvegicus ribosomes. Therefore, we used the scFv C5 coding sequence to make inducible intrabodies in Trypanosoma brucei. Transgenic parasites showed a strong decrease in their growth rate after induction. These results strengthen the importance of the P protein C terminal regions for ribosomal translation activity and suggest that trypanosomatid ribosomal P proteins could be a possible target for selective therapeutic agents that could be derived from structural analysis of the scFv C5 antibody paratope. PMID:22570698

  20. Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

    SciTech Connect

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K.; Schertler, Gebhard F. X.; Oprian, Daniel D.; Kern, Dorothee

    2015-12-24

    Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.

  1. Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

    DOE PAGESBeta

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K.; Schertler, Gebhard F. X.; Oprian, Daniel D.; Kern, Dorothee

    2015-12-24

    Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

  2. Conformational Selection in a Protein-Protein Interaction revealed by Dynamic Pathway Analysis

    PubMed Central

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K.; Schertler, Gebhard F. X.; Oprian, Daniel D.; Kern, Dorothee

    2015-01-01

    SUMMARY Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding. PMID:26725117

  3. Positively Selected Sites in Cetacean Myoglobins Contribute to Protein Stability

    PubMed Central

    Dasmeh, Pouria; Serohijos, Adrian W. R.; Kepp, Kasper P.; Shakhnovich, Eugene I.

    2013-01-01

    Since divergence ∼50 Ma ago from their terrestrial ancestors, cetaceans underwent a series of adaptations such as a ∼10–20 fold increase in myoglobin (Mb) concentration in skeletal muscle, critical for increasing oxygen storage capacity and prolonging dive time. Whereas the O2-binding affinity of Mbs is not significantly different among mammals (with typical oxygenation constants of ∼0.8–1.2 µM−1), folding stabilities of cetacean Mbs are ∼2–4 kcal/mol higher than for terrestrial Mbs. Using ancestral sequence reconstruction, maximum likelihood and Bayesian tests to describe the evolution of cetacean Mbs, and experimentally calibrated computation of stability effects of mutations, we observe accelerated evolution in cetaceans and identify seven positively selected sites in Mb. Overall, these sites contribute to Mb stabilization with a conditional probability of 0.8. We observe a correlation between Mb folding stability and protein abundance, suggesting that a selection pressure for stability acts proportionally to higher expression. We also identify a major divergence event leading to the common ancestor of whales, during which major stabilization occurred. Most of the positively selected sites that occur later act against other destabilizing mutations to maintain stability across the clade, except for the shallow divers, where late stability relaxation occurs, probably due to the shorter aerobic dive limits of these species. The three main positively selected sites 66, 5, and 35 undergo changes that favor hydrophobic folding, structural integrity, and intra-helical hydrogen bonds. PMID:23505347

  4. Selective inhibition of Biotin Protein Ligase from Staphylococcus aureus*

    PubMed Central

    Soares da Costa, Tatiana P.; Tieu, William; Yap, Min Y.; Pendini, Nicole R.; Polyak, Steven W.; Sejer Pedersen, Daniel; Morona, Renato; Turnidge, John D.; Wallace, John C.; Wilce, Matthew C. J.; Booker, Grant W.; Abell, Andrew D.

    2012-01-01

    There is a well documented need to replenish the antibiotic pipeline with new agents to combat the rise of drug resistant bacteria. One strategy to combat resistance is to discover new chemical classes immune to current resistance mechanisms that inhibit essential metabolic enzymes. Many of the obvious drug targets that have no homologous isozyme in the human host have now been investigated. Bacterial drug targets that have a closely related human homologue represent a new frontier in antibiotic discovery. However, to avoid potential toxicity to the host, these inhibitors must have very high selectivity for the bacterial enzyme over the human homolog. We have demonstrated that the essential enzyme biotin protein ligase (BPL) from the clinically important pathogen Staphylococcus aureus could be selectively inhibited. Linking biotin to adenosine via a 1,2,3 triazole yielded the first BPL inhibitor selective for S. aureus BPL over the human equivalent. The synthesis of new biotin 1,2,3-triazole analogues using click chemistry yielded our most potent structure (Ki 90 nm) with a >1100-fold selectivity for the S. aureus BPL over the human homologue. X-ray crystallography confirmed the mechanism of inhibitor binding. Importantly, the inhibitor showed cytotoxicity against S. aureus but not cultured mammalian cells. The biotin 1,2,3-triazole provides a novel pharmacophore for future medicinal chemistry programs to develop this new antibiotic class. PMID:22437830

  5. On spatial mutation-selection models

    SciTech Connect

    Kondratiev, Yuri; Kutoviy, Oleksandr E-mail: kutovyi@mit.edu; Minlos, Robert Pirogov, Sergey

    2013-11-15

    We discuss the selection procedure in the framework of mutation models. We study the regulation for stochastically developing systems based on a transformation of the initial Markov process which includes a cost functional. The transformation of initial Markov process by cost functional has an analytic realization in terms of a Kimura-Maruyama type equation for the time evolution of states or in terms of the corresponding Feynman-Kac formula on the path space. The state evolution of the system including the limiting behavior is studied for two types of mutation-selection models.

  6. Diamidine Compounds for Selective Inhibition of Protein Arginine Methyltransferase 1

    PubMed Central

    2015-01-01

    Protein arginine methylation is a posttranslational modification critical for a variety of biological processes. Misregulation of protein arginine methyltransferases (PRMTs) has been linked to many pathological conditions. Most current PRMT inhibitors display limited specificity and selectivity, indiscriminately targeting many methyltransferase enzymes that use S-adenosyl-l-methionine as a cofactor. Here we report diamidine compounds for specific inhibition of PRMT1, the primary type I enzyme. Docking, molecular dynamics, and MM/PBSA analysis together with biochemical assays were conducted to understand the binding modes of these inhibitors and the molecular basis of selective inhibition for PRMT1. Our data suggest that 2,5-bis(4-amidinophenyl)furan (1, furamidine, DB75), one leading inhibitor, targets the enzyme active site and is primarily competitive with the substrate and noncompetitive toward the cofactor. Furthermore, cellular studies revealed that 1 is cell membrane permeable and effectively inhibits intracellular PRMT1 activity and blocks cell proliferation in leukemia cell lines with different genetic lesions. PMID:24564570

  7. Stochastic model for protein flexibility analysis

    NASA Astrophysics Data System (ADS)

    Xia, Kelin; Wei, Guo-Wei

    2013-12-01

    Protein flexibility is an intrinsic property and plays a fundamental role in protein functions. Computational analysis of protein flexibility is crucial to protein function prediction, macromolecular flexible docking, and rational drug design. Most current approaches for protein flexibility analysis are based on Hamiltonian mechanics. We introduce a stochastic model to study protein flexibility. The essential idea is to analyze the free induction decay of a perturbed protein structural probability, which satisfies the master equation. The transition probability matrix is constructed by using probability density estimators including monotonically decreasing radial basis functions. We show that the proposed stochastic model gives rise to some of the best predictions of Debye-Waller factors or B factors for three sets of protein data introduced in the literature.

  8. Uncovering Molecular Bases Underlying Bone Morphogenetic Protein Receptor Inhibitor Selectivity

    PubMed Central

    Alsamarah, Abdelaziz; LaCuran, Alecander E.; Oelschlaeger, Peter; Hao, Jijun; Luo, Yun

    2015-01-01

    Abnormal alteration of bone morphogenetic protein (BMP) signaling is implicated in many types of diseases including cancer and heterotopic ossifications. Hence, small molecules targeting BMP type I receptors (BMPRI) to interrupt BMP signaling are believed to be an effective approach to treat these diseases. However, lack of understanding of the molecular determinants responsible for the binding selectivity of current BMP inhibitors has been a big hindrance to the development of BMP inhibitors for clinical use. To address this issue, we carried out in silico experiments to test whether computational methods can reproduce and explain the high selectivity of a small molecule BMP inhibitor DMH1 on BMPRI kinase ALK2 vs. the closely related TGF-β type I receptor kinase ALK5 and vascular endothelial growth factor receptor type 2 (VEGFR2) tyrosine kinase. We found that, while the rigid docking method used here gave nearly identical binding affinity scores among the three kinases; free energy perturbation coupled with Hamiltonian replica-exchange molecular dynamics (FEP/H-REMD) simulations reproduced the absolute binding free energies in excellent agreement with experimental data. Furthermore, the binding poses identified by FEP/H-REMD led to a quantitative analysis of physical/chemical determinants governing DMH1 selectivity. The current work illustrates that small changes in the binding site residue type (e.g. pre-hinge region in ALK2 vs. ALK5) or side chain orientation (e.g. Tyr219 in caALK2 vs. wtALK2), as well as a subtle structural modification on the ligand (e.g. DMH1 vs. LDN193189) will cause distinct binding profiles and selectivity among BMP inhibitors. Therefore, the current computational approach represents a new way of investigating BMP inhibitors. Our results provide critical information for designing exclusively selective BMP inhibitors for the development of effective pharmacotherapy for diseases caused by aberrant BMP signaling. PMID:26133550

  9. Uncovering Molecular Bases Underlying Bone Morphogenetic Protein Receptor Inhibitor Selectivity.

    PubMed

    Alsamarah, Abdelaziz; LaCuran, Alecander E; Oelschlaeger, Peter; Hao, Jijun; Luo, Yun

    2015-01-01

    Abnormal alteration of bone morphogenetic protein (BMP) signaling is implicated in many types of diseases including cancer and heterotopic ossifications. Hence, small molecules targeting BMP type I receptors (BMPRI) to interrupt BMP signaling are believed to be an effective approach to treat these diseases. However, lack of understanding of the molecular determinants responsible for the binding selectivity of current BMP inhibitors has been a big hindrance to the development of BMP inhibitors for clinical use. To address this issue, we carried out in silico experiments to test whether computational methods can reproduce and explain the high selectivity of a small molecule BMP inhibitor DMH1 on BMPRI kinase ALK2 vs. the closely related TGF-β type I receptor kinase ALK5 and vascular endothelial growth factor receptor type 2 (VEGFR2) tyrosine kinase. We found that, while the rigid docking method used here gave nearly identical binding affinity scores among the three kinases; free energy perturbation coupled with Hamiltonian replica-exchange molecular dynamics (FEP/H-REMD) simulations reproduced the absolute binding free energies in excellent agreement with experimental data. Furthermore, the binding poses identified by FEP/H-REMD led to a quantitative analysis of physical/chemical determinants governing DMH1 selectivity. The current work illustrates that small changes in the binding site residue type (e.g. pre-hinge region in ALK2 vs. ALK5) or side chain orientation (e.g. Tyr219 in caALK2 vs. wtALK2), as well as a subtle structural modification on the ligand (e.g. DMH1 vs. LDN193189) will cause distinct binding profiles and selectivity among BMP inhibitors. Therefore, the current computational approach represents a new way of investigating BMP inhibitors. Our results provide critical information for designing exclusively selective BMP inhibitors for the development of effective pharmacotherapy for diseases caused by aberrant BMP signaling. PMID:26133550

  10. A model for plant lighting system selection

    NASA Technical Reports Server (NTRS)

    Ciolkosz, D. E.; Albright, L. D.; Sager, J. C.; Langhans, R. W.

    2002-01-01

    A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

  11. Observability in strategic models of viability selection.

    PubMed

    Gámez, M; Carreño, R; Kósa, A; Varga, Z

    2003-10-01

    Strategic models of frequency-dependent viability selection, in terms of mathematical systems theory, are considered as a dynamic observation system. Using a general sufficient condition for observability of nonlinear systems with invariant manifold, it is studied whether, observing certain phenotypic characteristics of the population, the development of its genetic state can be recovered, at least near equilibrium.

  12. Structural Basis for Binding and Selectivity of Antimalarial and Anticancer Ethylenediamine Inhibitors to Protein Farnesyltransferase

    SciTech Connect

    Hast, Michael A.; Fletcher, Steven; Cummings, Christopher G.; Pusateri, Erin E.; Blaskovich, Michelle A.; Rivas, Kasey; Gelb, Michael H.; Voorhis, Wesley C.Van; Sebti, Said M.; Hamilton, Andrew D.; Beese, Lorena S. ); ); ); )

    2009-03-20

    Protein farnesyltransferase (FTase) catalyzes an essential posttranslational lipid modification of more than 60 proteins involved in intracellular signal transduction networks. FTase inhibitors have emerged as a significant target for development of anticancer therapeutics and, more recently, for the treatment of parasitic diseases caused by protozoan pathogens, including malaria (Plasmodium falciparum). We present the X-ray crystallographic structures of complexes of mammalian FTase with five inhibitors based on an ethylenediamine scaffold, two of which exhibit over 1000-fold selective inhibition of P. falciparum FTase. These structures reveal the dominant determinants in both the inhibitor and enzyme that control binding and selectivity. Comparison to a homology model constructed for the P. falciparum FTase suggests opportunities for further improving selectivity of a new generation of antimalarial inhibitors.

  13. Inference of Episodic Changes in Natural Selection Acting on Protein Coding Sequences via CODEML.

    PubMed

    Bielawski, Joseph P; Baker, Jennifer L; Mingrone, Joseph

    2016-01-01

    This unit provides protocols for using the CODEML program from the PAML package to make inferences about episodic natural selection in protein-coding sequences. The protocols cover inference tasks such as maximum likelihood estimation of selection intensity, testing the hypothesis of episodic positive selection, and identifying sites with a history of episodic evolution. We provide protocols for using the rich set of models implemented in CODEML to assess robustness, and for using bootstrapping to assess if the requirements for reliable statistical inference have been met. An example dataset is used to illustrate how the protocols are used with real protein-coding sequences. The workflow of this design, through automation, is readily extendable to a larger-scale evolutionary survey. © 2016 by John Wiley & Sons, Inc. PMID:27322407

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

    PubMed

    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/.

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

    PubMed Central

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

    2014-01-01

    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/. PMID:24782522

  16. Predicting protein-RNA interaction amino acids using random forest based on submodularity subset selection.

    PubMed

    Pan, Xiaoyong; Zhu, Lin; Fan, Yong-Xian; Yan, Junchi

    2014-11-13

    Protein-RNA interaction plays a very crucial role in many biological processes, such as protein synthesis, transcription and post-transcription of gene expression and pathogenesis of disease. Especially RNAs always function through binding to proteins. Identification of binding interface region is especially useful for cellular pathways analysis and drug design. In this study, we proposed a novel approach for binding sites identification in proteins, which not only integrates local features and global features from protein sequence directly, but also constructed a balanced training dataset using sub-sampling based on submodularity subset selection. Firstly we extracted local features and global features from protein sequence, such as evolution information and molecule weight. Secondly, the number of non-interaction sites is much more than interaction sites, which leads to a sample imbalance problem, and hence biased machine learning model with preference to non-interaction sites. To better resolve this problem, instead of previous randomly sub-sampling over-represented non-interaction sites, a novel sampling approach based on submodularity subset selection was employed, which can select more representative data subset. Finally random forest were trained on optimally selected training subsets to predict interaction sites. Our result showed that our proposed method is very promising for predicting protein-RNA interaction residues, it achieved an accuracy of 0.863, which is better than other state-of-the-art methods. Furthermore, it also indicated the extracted global features have very strong discriminate ability for identifying interaction residues from random forest feature importance analysis.

  17. Quantile hydrologic model selection and uncertainty assessment

    NASA Astrophysics Data System (ADS)

    Pande, S.; Keyzer, M. A.; Savenije, H.; Gosain, A. K.

    2010-12-01

    Inapplicability of state of the art hydrological models due to scarce data motivates the need for a modeling approach that can be well constrained to available data and still model dominant processes. Such an approach requires embedded model relationships to be simple and parsimonious in parameters for robust model selection. Simplicity in functional relationship is also important from water management point of view if these models are to be coupled with economic system models for meaningful policy assessment. We propose a semi-distributed approach wherein we model already known dominant processes in dryland areas of Western India (evaporation, Hortonian overland flows, transmission loses and subsurface flows) in a simple but constrained manner through mathematical programming of relevant equations and constraints. Diverse data sources such as GRACE, MERRA reanalysis data, FAO soil texture map and even Indian Agricultural Census data are used. Such a modeling approach allows uncertainty quantification through quantile parameter estimation, which we present in this talk. Quantile estimation transfers uncertainty due to hydrologic model misspecification or data uncertainty, based on quantiles of residuals, onto parameters of the hydrologic model with a fixed structure. An adaptation of quantile regression to parsimonious hydrologic model estimation, this frequentist approach seeks to complement existing Bayesian approaches to model parameter and prediction uncertainty.

  18. Influence of the protein status of piglets on their ability to select and prefer protein sources.

    PubMed

    Guzmán-Pino, Sergio A; Solà-Oriol, David; Figueroa, Jaime; Pérez, José F

    2014-04-22

    Pigs may have retained the capacity to choose feeds based on their nutritional requirements, even after decades in which they are not allowed to select their diet composition due to the common feeding systems of the intensive pig industry. We used 480 early-weaned piglets in two experiments to assess their ability to select and prefer protein-related sources, depending on their protein status. Piglets were fed after weaning with two isoenergetic diets formulated to contain an optimal or sub-optimal crude-protein (CP) content, a high-protein (HP, 204g CP/kg as-fed) or a low-protein diet (LP, 142g CP/kg), respectively. In Experiment 1, the preference of piglets was assessed by using a choice test between protein (porcine digestible peptides [PDP] 40g/L) and carbohydrate (sucrose 40g/L) water-based solutions for a period of 3min. Piglets showed higher intake and preference for the sucrose 40g/L than for the PDP 40g/L solution, independently of the dietary CP content (9.8mL/kg body weight [BW] vs. 3.7mL/kg BW and 10.4mL/kg BW vs. 4.3mL/kg BW in HP and LP pigs, respectively). In Experiment 2, piglets were given eight training sessions in which two equally preferred flavors were mixed with protein (porcine animal plasma 60g/L, CSp) or carbohydrate (maltodextrin 60g/L, CSc) solutions. In the subsequent choice test, piglets fed the HP diet showed a tendency to a higher intake of CSc than of CSp (6.5mL/kg BW vs. 5.4mL/kg BW). On the other hand, piglets fed the LP diet showed a higher intake and preference for CSp than for CSc (15.5mL/kg BW vs. 10.2mL/kg BW), differences being higher for medium and low BW piglets than for heavy ones. The results show that piglets are unable to express a specific appetite for protein to correct previous underfeeding with it; however, they may show an appropriate dietary selection pattern in order to overcome protein deficiency through associative learning.

  19. Selective molecular transport through the protein shell of a bacterial microcompartment organelle.

    PubMed

    Chowdhury, Chiranjit; Chun, Sunny; Pang, Allan; Sawaya, Michael R; Sinha, Sharmistha; Yeates, Todd O; Bobik, Thomas A

    2015-03-10

    Bacterial microcompartments are widespread prokaryotic organelles that have important and diverse roles ranging from carbon fixation to enteric pathogenesis. Current models for microcompartment function propose that their outer protein shell is selectively permeable to small molecules, but whether a protein shell can mediate selective permeability and how this occurs are unresolved questions. Here, biochemical and physiological studies of structure-guided mutants are used to show that the hexameric PduA shell protein of the 1,2-propanediol utilization (Pdu) microcompartment forms a selectively permeable pore tailored for the influx of 1,2-propanediol (the substrate of the Pdu microcompartment) while restricting the efflux of propionaldehyde, a toxic intermediate of 1,2-propanediol catabolism. Crystal structures of various PduA mutants provide a foundation for interpreting the observed biochemical and phenotypic data in terms of molecular diffusion across the shell. Overall, these studies provide a basis for understanding a class of selectively permeable channels formed by nonmembrane proteins. PMID:25713376

  20. Information-driven structural modelling of protein-protein interactions.

    PubMed

    Rodrigues, João P G L M; Karaca, Ezgi; Bonvin, Alexandre M J J

    2015-01-01

    Protein-protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called "information-driven" approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a "classical" protein-protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes. PMID:25330973

  1. Recursive protein modeling: a divide and conquer strategy for Protein Structure Prediction and its case study in CASP9.

    PubMed

    Cheng, Jianlin; Eickholt, Jesse; Wang, Zheng; Deng, Xin

    2012-06-01

    After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques--template-based modeling and template-free modeling--have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can significantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction. PMID:22809379

  2. A soft and transparent handleable protein model.

    PubMed

    Kawakami, Masaru

    2012-08-01

    The field of structural biology currently relies on computer-generated graphical representations of three-dimensional (3D) structures to conceptualize biomolecules. As the size and complexity of the molecular structure increases, model generation and peer discussions become more difficult. It is even more problematic when discussing protein-protein interactions wherein large surface area contact is considered. This report demonstrates the viability of a new handleable protein molecular model with a soft and transparent silicone body similar to the molecule's surface. A full-color printed main chain structure embedded in the silicone body enables users to simultaneously feel the molecular surface, view through the main chain structure, and manually simulate molecular docking. The interactive, hands-on experience deepens the user's intuitive understanding of the complicated 3D protein structure and elucidates ligand binding and protein-protein interactions. This model would be an effective discussion tool for the classroom or laboratory that stimulates inspired learning in this study field.

  3. A soft and transparent handleable protein model

    NASA Astrophysics Data System (ADS)

    Kawakami, Masaru

    2012-08-01

    The field of structural biology currently relies on computer-generated graphical representations of three-dimensional (3D) structures to conceptualize biomolecules. As the size and complexity of the molecular structure increases, model generation and peer discussions become more difficult. It is even more problematic when discussing protein-protein interactions wherein large surface area contact is considered. This report demonstrates the viability of a new handleable protein molecular model with a soft and transparent silicone body similar to the molecule's surface. A full-color printed main chain structure embedded in the silicone body enables users to simultaneously feel the molecular surface, view through the main chain structure, and manually simulate molecular docking. The interactive, hands-on experience deepens the user's intuitive understanding of the complicated 3D protein structure and elucidates ligand binding and protein-protein interactions. This model would be an effective discussion tool for the classroom or laboratory that stimulates inspired learning in this study field.

  4. Design of protein-interaction specificity affords selective bZIP-binding peptides

    PubMed Central

    Grigoryan, Gevorg; Reinke, Aaron W.; Keating, Amy E.

    2009-01-01

    Interaction specificity is a required feature of biological networks and a necessary characteristic of protein or small-molecule reagents and therapeutics. The ability to alter or inhibit protein interactions selectively would advance basic and applied molecular science. Assessing or modelling interaction specificity requires treating multiple competing complexes, which presents computational and experimental challenges. Here we present a computational framework for designing protein interaction specificity and use it to identify specific peptide partners for human bZIP transcription factors. Protein microarrays were used to characterize designed, synthetic ligands for all but one of 20 bZIP families. The bZIP proteins share strong sequence and structural similarities and thus are challenging targets to bind specifically. Yet many of the designs, including examples that bind the oncoproteins cJun, cFos and cMaf, were selective for their targets over all 19 other families. Collectively, the designs exhibit a wide range of novel interaction profiles, demonstrating that human bZIPs have only sparsely sampled the possible interaction space accessible to them. Our computational method provides a way to systematically analyze tradeoffs between stability and specificity and is suitable for use with many types of structure-scoring functions; thus it may prove broadly useful as a tool for protein design. PMID:19370028

  5. Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)

    PubMed Central

    Holman, Stephen W.; Hammond, Dean E.; Simpson, Deborah M.; Waters, John; Hurst, Jane L.

    2016-01-01

    Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644981

  6. Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS).

    PubMed

    Holman, Stephen W; Hammond, Dean E; Simpson, Deborah M; Waters, John; Hurst, Jane L; Beynon, Robert J

    2016-10-28

    Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways.This article is part of the themed issue 'Quantitative mass spectrometry'. PMID:27644981

  7. Review and selection of unsaturated flow models

    SciTech Connect

    1993-09-10

    Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer ground-water flow models; to conduct performance assessments; and to develop performance assessment models, where necessary. In the area of scientific modeling, the M&O CRWMS has the following responsibilities: To provide overall management and integration of modeling activities. To provide a framework for focusing modeling and model development. To identify areas that require increased or decreased emphasis. To ensure that the tools necessary to conduct performance assessment are available. These responsibilities are being initiated through a three-step process. It consists of a thorough review of existing models, testing of models which best fit the established requirements, and making recommendations for future development that should be conducted. Future model enhancement will then focus on the models selected during this activity. Furthermore, in order to manage future model development, particularly in those areas requiring substantial enhancement, the three-step process will be updated and reported periodically in the future.

  8. ModelOMatic: fast and automated model selection between RY, nucleotide, amino acid, and codon substitution models.

    PubMed

    Whelan, Simon; Allen, James E; Blackburne, Benjamin P; Talavera, David

    2015-01-01

    Molecular phylogenetics is a powerful tool for inferring both the process and pattern of evolution from genomic sequence data. Statistical approaches, such as maximum likelihood and Bayesian inference, are now established as the preferred methods of inference. The choice of models that a researcher uses for inference is of critical importance, and there are established methods for model selection conditioned on a particular type of data, such as nucleotides, amino acids, or codons. A major limitation of existing model selection approaches is that they can only compare models acting upon a single type of data. Here, we extend model selection to allow comparisons between models describing different types of data by introducing the idea of adapter functions, which project aggregated models onto the originally observed sequence data. These projections are implemented in the program ModelOMatic and used to perform model selection on 3722 families from the PANDIT database, 68 genes from an arthropod phylogenomic data set, and 248 genes from a vertebrate phylogenomic data set. For the PANDIT and arthropod data, we find that amino acid models are selected for the overwhelming majority of alignments; with progressively smaller numbers of alignments selecting codon and nucleotide models, and no families selecting RY-based models. In contrast, nearly all alignments from the vertebrate data set select codon-based models. The sequence divergence, the number of sequences, and the degree of selection acting upon the protein sequences may contribute to explaining this variation in model selection. Our ModelOMatic program is fast, with most families from PANDIT taking fewer than 150 s to complete, and should therefore be easily incorporated into existing phylogenetic pipelines. ModelOMatic is available at https://code.google.com/p/modelomatic/.

  9. FTMAP: extended protein mapping with user-selected probe molecules

    PubMed Central

    Ngan, Chi Ho; Bohnuud, Tanggis; Mottarella, Scott E.; Beglov, Dmitri; Villar, Elizabeth A.; Hall, David R.; Kozakov, Dima; Vajda, Sandor

    2012-01-01

    Binding hot spots, protein sites with high-binding affinity, can be identified using X-ray crystallography or NMR by screening libraries of small organic molecules that tend to cluster at such regions. FTMAP, a direct computational analog of the experimental screening approaches, globally samples the surface of a target protein using small organic molecules as probes, finds favorable positions, clusters the conformations and ranks the clusters on the basis of the average energy. The regions that bind several probe clusters predict the binding hot spots, in good agreement with experimental results. Small molecules discovered by fragment-based approaches to drug design also bind at the hot spot regions. To identify such molecules and their most likely bound positions, we extend the functionality of FTMAP (http://ftmap.bu.edu/param) to accept any small molecule as an additional probe. In its updated form, FTMAP identifies the hot spots based on a standard set of probes, and for each additional probe shows representative structures of nearby low energy clusters. This approach helps to predict bound poses of the user-selected molecules, detects if a compound is not likely to bind in the hot spot region, and provides input for the design of larger ligands. PMID:22589414

  10. Preventing fibril formation of a protein by selective mutation

    PubMed Central

    Maisuradze, Gia G.; Medina, Jordi; Kachlishvili, Khatuna; Krupa, Pawel; Mozolewska, Magdalena A.; Martin-Malpartida, Pau; Maisuradze, Luka; Macias, Maria J.; Scheraga, Harold A.

    2015-01-01

    The origins of formation of an intermediate state involved in amyloid formation and ways to prevent it are illustrated with the example of the Formin binding protein 28 (FBP28) WW domain, which folds with biphasic kinetics. Molecular dynamics of protein folding trajectories are used to examine local and global motions and the time dependence of formation of contacts between Cαs and Cβs of selected pairs of residues. Focus is placed on the WT FBP28 WW domain and its six mutants (L26D, L26E, L26W, E27Y, T29D, and T29Y), which have structures that are determined by high-resolution NMR spectroscopy. The origins of formation of an intermediate state are elucidated, viz. as formation of hairpin 1 by a hydrophobic collapse mechanism causing significant delay of formation of both hairpins, especially hairpin 2, which facilitates the emergence of an intermediate state. It seems that three-state folding is a major folding scenario for all six mutants and WT. Additionally, two-state and downhill folding scenarios were identified in ∼15% of the folding trajectories for L26D and L26W, in which both hairpins are formed by the Matheson–Scheraga mechanism much faster than in three-state folding. These results indicate that formation of hairpins connecting two antiparallel β-strands determines overall folding. The correlations between the local and global motions identified for all folding trajectories lead to the identification of the residues making the main contributions in the formation of the intermediate state. The presented findings may provide an understanding of protein folding intermediates in general and lead to a procedure for their prevention. PMID:26483482

  11. Tracking Models for Optioned Portfolio Selection

    NASA Astrophysics Data System (ADS)

    Liang, Jianfeng

    In this paper we study a target tracking problem for the portfolio selection involving options. In particular, the portfolio in question contains a stock index and some European style options on the index. A refined tracking-error-variance methodology is adopted to formulate this problem as a multi-stage optimization model. We derive the optimal solutions based on stochastic programming and optimality conditions. Attention is paid to the structure of the optimal payoff function, which is shown to possess rich properties.

  12. Models of globular proteins in aqueous solutions

    NASA Astrophysics Data System (ADS)

    Wentzel, Nathaniel James

    Protein crystallization is a continuing area of research. Currently, there is no universal theory for the conditions required to crystallize proteins. A better understanding of protein crystallization will be helpful in determining protein structure and preventing and treating certain diseases. In this thesis, we will extend the understanding of globular proteins in aqueous solutions by analyzing various models for protein interactions. Experiments have shown that the liquid-liquid phase separation curves for lysozyme in solution with salt depend on salt type and salt concentration. We analyze a simple square well model for this system whose well depth depends on salt type and salt concentration, to determine the phase coexistence surfaces from experimental data. The surfaces, calculated from a single Monte Carlo simulation and a simple scaling argument, are shown as a function of temperature, salt concentration and protein concentration for two typical salts. Urate Oxidase from Asperigillus flavus is a protein used for studying the effects of polymers on the crystallization of large proteins. Experiments have determined some aspects of the phase diagram. We use Monte Carlo techniques and perturbation theory to predict the phase diagram for a model of urate oxidase in solution with PEG. The model used includes an electrostatic interaction, van der Waals attraction, and a polymerinduced depletion interaction. The results agree quantitatively with experiments. Anisotropy plays a role in globular protein interactions, including the formation of hemoglobin fibers in sickle cell disease. Also, the solvent conditions have been shown to play a strong role in the phase behavior of some aqueous protein solutions. Each has previously been treated separately in theoretical studies. Here we propose and analyze a simple, combined model that treats both anisotropy and solvent effects. We find that this model qualitatively explains some phase behavior, including the existence of

  13. Information criteria and selection of vibration models.

    PubMed

    Ruzek, Michal; Guyader, Jean-Louis; Pézerat, Charles

    2014-12-01

    This paper presents a method of determining an appropriate equation of motion of two-dimensional plane structures like membranes and plates from vibration response measurements. The local steady-state vibration field is used as input for the inverse problem that approximately determines the dispersion curve of the structure. This dispersion curve is then statistically treated with Akaike information criterion (AIC), which compares the experimentally measured curve to several candidate models (equations of motion). The model with the lowest AIC value is then chosen, and the utility of other models can also be assessed. This method is applied to three experimental case studies: A red cedar wood plate for musical instruments, a thick paper subjected to unknown membrane tension, and a thick composite sandwich panel. These three cases give three different situations of a model selection.

  14. Image Discrimination Models With Stochastic Channel Selection

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

    1995-01-01

    Many models of human image processing feature a large fixed number of channels representing cortical units varying in spatial position (visual field direction and eccentricity) and spatial frequency (radial frequency and orientation). The values of these parameters are usually sampled at fixed values selected to ensure adequate overlap considering the bandwidth and/or spread parameters, which are usually fixed. Even high levels of overlap does not always ensure that the performance of the model will vary smoothly with image translation or scale changes. Physiological measurements of bandwidth and/or spread parameters result in a broad distribution of estimated parameter values and the prediction of some psychophysical results are facilitated by the assumption that these parameters also take on a range of values. Selecting a sample of channels from a continuum of channels rather than using a fixed set can make model performance vary smoothly with changes in image position, scale, and orientation. It also facilitates the addition of spatial inhomogeneity, nonlinear feature channels, and focus of attention to channel models.

  15. Model selection for radiochromic film dosimetry

    NASA Astrophysics Data System (ADS)

    Méndez, I.

    2015-05-01

    The purpose of this study was to find the most accurate model for radiochromic film dosimetry by comparing different channel independent perturbation models. A model selection approach based on (algorithmic) information theory was followed, and the results were validated using gamma-index analysis on a set of benchmark test cases. Several questions were addressed: (a) whether incorporating the information of the non-irradiated film, by scanning prior to irradiation, improves the results; (b) whether lateral corrections are necessary when using multichannel models; (c) whether multichannel dosimetry produces better results than single-channel dosimetry; (d) which multichannel perturbation model provides more accurate film doses. It was found that scanning prior to irradiation and applying lateral corrections improved the accuracy of the results. For some perturbation models, increasing the number of color channels did not result in more accurate film doses. Employing Truncated Normal perturbations was found to provide better results than using Micke-Mayer perturbation models. Among the models being compared, the triple-channel model with Truncated Normal perturbations, net optical density as the response and subject to the application of lateral corrections was found to be the most accurate model. The scope of this study was circumscribed by the limits under which the models were tested. In this study, the films were irradiated with megavoltage radiotherapy beams, with doses from about 20-600 cGy, entire (8 inch  × 10 inch) films were scanned, the functional form of the sensitometric curves was a polynomial and the different lots were calibrated using the plane-based method.

  16. DNA Aptamers Selectively Target Leishmania infantum H2A Protein

    PubMed Central

    Martín, M. Elena; García-Hernández, Marta; García-Recio, Eva M.; Gómez-Chacón, Gerónimo F.; Sánchez-López, Marta; González, Víctor M.

    2013-01-01

    Parasites of the genus Leishmania produce leishmaniasis which affects millions people around the world. Understanding the molecular characteristics of the parasite can increase the knowledge about the mechanisms underlying disease development and progression. Thus, the study of the molecular features of histones has been considered of particular interest because Leishmania does not condense the chromatin during mitosis and, consequently, a different role for these proteins in the biology of the parasite can be expected. Furthermore, the sequence divergences in the amino and in the carboxy-terminal domains of the kinetoplastid core histones convert them in potential diagnostic and/or therapeutics targets. Aptamers are oligonucleotide ligands that are selected in vitro by their affinity and specificity for the target as a consequence of the particular tertiary structure that they are able to acquire depending on their sequence. Development of high-affinity molecules with the ability to recognize specifically Leishmania histones is essential for the progress of this kind of study. Two aptamers which specifically recognize Leishmania infantum H2A histone were cloned from a previously obtained ssDNA enriched population. These aptamers were sequenced and subjected to an in silico analysis. ELONA, slot blot and Western blot were performed to establish aptamer affinity and specificity for LiH2A histone and ELONA assays using peptides corresponding to overlapped sequences of LiH2A were made mapping the aptamers:LiH2A interaction. As “proofs of concept”, aptamers were used to determine the number of parasites in an ELONA platform and to purify LiH2A from complex mixtures. The aptamers showed different secondary structures among them; however, both of them were able to recognize the same peptides located in a side of the protein. In addition, we demonstrate that these aptamers are useful for LiH2A identification and also may be of potential application as diagnostic

  17. Advances in Homology Protein Structure Modeling

    PubMed Central

    Xiang, Zhexin

    2007-01-01

    Homology modeling plays a central role in determining protein structure in the structural genomics project. The importance of homology modeling has been steadily increasing because of the large gap that exists between the overwhelming number of available protein sequences and experimentally solved protein structures, and also, more importantly, because of the increasing reliability and accuracy of the method. In fact, a protein sequence with over 30% identity to a known structure can often be predicted with an accuracy equivalent to a low-resolution X-ray structure. The recent advances in homology modeling, especially in detecting distant homologues, aligning sequences with template structures, modeling of loops and side chains, as well as detecting errors in a model, have contributed to reliable prediction of protein structure, which was not possible even several years ago. The ongoing efforts in solving protein structures, which can be time-consuming and often difficult, will continue to spur the development of a host of new computational methods that can fill in the gap and further contribute to understanding the relationship between protein structure and function. PMID:16787261

  18. Selection and estimation for mixed graphical models

    PubMed Central

    Chen, Shizhe; Witten, Daniela M.; shojaie, Ali

    2016-01-01

    Summary We consider the problem of estimating the parameters in a pairwise graphical model in which the distribution of each node, conditioned on the others, may have a different exponential family form. We identify restrictions on the parameter space required for the existence of a well-defined joint density, and establish the consistency of the neighbourhood selection approach for graph reconstruction in high dimensions when the true underlying graph is sparse. Motivated by our theoretical results, we investigate the selection of edges between nodes whose conditional distributions take different parametric forms, and show that efficiency can be gained if edge estimates obtained from the regressions of particular nodes are used to reconstruct the graph. These results are illustrated with examples of Gaussian, Bernoulli, Poisson and exponential distributions. Our theoretical findings are corroborated by evidence from simulation studies.

  19. Selection and estimation for mixed graphical models

    PubMed Central

    Chen, Shizhe; Witten, Daniela M.; shojaie, Ali

    2016-01-01

    Summary We consider the problem of estimating the parameters in a pairwise graphical model in which the distribution of each node, conditioned on the others, may have a different exponential family form. We identify restrictions on the parameter space required for the existence of a well-defined joint density, and establish the consistency of the neighbourhood selection approach for graph reconstruction in high dimensions when the true underlying graph is sparse. Motivated by our theoretical results, we investigate the selection of edges between nodes whose conditional distributions take different parametric forms, and show that efficiency can be gained if edge estimates obtained from the regressions of particular nodes are used to reconstruct the graph. These results are illustrated with examples of Gaussian, Bernoulli, Poisson and exponential distributions. Our theoretical findings are corroborated by evidence from simulation studies. PMID:27625437

  20. Disulfide bridge regulates ligand-binding site selectivity in liver bile acid-binding proteins.

    PubMed

    Cogliati, Clelia; Tomaselli, Simona; Assfalg, Michael; Pedò, Massimo; Ferranti, Pasquale; Zetta, Lucia; Molinari, Henriette; Ragona, Laura

    2009-10-01

    Bile acid-binding proteins (BABPs) are cytosolic lipid chaperones that play central roles in driving bile flow, as well as in the adaptation to various pathological conditions, contributing to the maintenance of bile acid homeostasis and functional distribution within the cell. Understanding the mode of binding of bile acids with their cytoplasmic transporters is a key issue in providing a model for the mechanism of their transfer from the cytoplasm to the nucleus, for delivery to nuclear receptors. A number of factors have been shown to modulate bile salt selectivity, stoichiometry, and affinity of binding to BABPs, e.g. chemistry of the ligand, protein plasticity and, possibly, the formation of disulfide bridges. Here, the effects of the presence of a naturally occurring disulfide bridge on liver BABP ligand-binding properties and backbone dynamics have been investigated by NMR. Interestingly, the disulfide bridge does not modify the protein-binding stoichiometry, but has a key role in modulating recognition at both sites, inducing site selectivity for glycocholic and glycochenodeoxycholic acid. Protein conformational changes following the introduction of a disulfide bridge are small and located around the inner binding site, whereas significant changes in backbone motions are observed for several residues distributed over the entire protein, both in the apo form and in the holo form. Site selectivity appears, therefore, to be dependent on protein mobility rather than being governed by steric factors. The detected properties further establish a parallelism with the behaviour of human ileal BABP, substantiating the proposal that BABPs have parallel functions in hepatocytes and enterocytes. PMID:19754879

  1. Disulfide bridge regulates ligand-binding site selectivity in liver bile acid-binding proteins.

    PubMed

    Cogliati, Clelia; Tomaselli, Simona; Assfalg, Michael; Pedò, Massimo; Ferranti, Pasquale; Zetta, Lucia; Molinari, Henriette; Ragona, Laura

    2009-10-01

    Bile acid-binding proteins (BABPs) are cytosolic lipid chaperones that play central roles in driving bile flow, as well as in the adaptation to various pathological conditions, contributing to the maintenance of bile acid homeostasis and functional distribution within the cell. Understanding the mode of binding of bile acids with their cytoplasmic transporters is a key issue in providing a model for the mechanism of their transfer from the cytoplasm to the nucleus, for delivery to nuclear receptors. A number of factors have been shown to modulate bile salt selectivity, stoichiometry, and affinity of binding to BABPs, e.g. chemistry of the ligand, protein plasticity and, possibly, the formation of disulfide bridges. Here, the effects of the presence of a naturally occurring disulfide bridge on liver BABP ligand-binding properties and backbone dynamics have been investigated by NMR. Interestingly, the disulfide bridge does not modify the protein-binding stoichiometry, but has a key role in modulating recognition at both sites, inducing site selectivity for glycocholic and glycochenodeoxycholic acid. Protein conformational changes following the introduction of a disulfide bridge are small and located around the inner binding site, whereas significant changes in backbone motions are observed for several residues distributed over the entire protein, both in the apo form and in the holo form. Site selectivity appears, therefore, to be dependent on protein mobility rather than being governed by steric factors. The detected properties further establish a parallelism with the behaviour of human ileal BABP, substantiating the proposal that BABPs have parallel functions in hepatocytes and enterocytes.

  2. Model selection versus model averaging in dose finding studies.

    PubMed

    Schorning, Kirsten; Bornkamp, Björn; Bretz, Frank; Dette, Holger

    2016-09-30

    A key objective of Phase II dose finding studies in clinical drug development is to adequately characterize the dose response relationship of a new drug. An important decision is then on the choice of a suitable dose response function to support dose selection for the subsequent Phase III studies. In this paper, we compare different approaches for model selection and model averaging using mathematical properties as well as simulations. We review and illustrate asymptotic properties of model selection criteria and investigate their behavior when changing the sample size but keeping the effect size constant. In a simulation study, we investigate how the various approaches perform in realistically chosen settings. Finally, the different methods are illustrated with a recently conducted Phase II dose finding study in patients with chronic obstructive pulmonary disease. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27226147

  3. Topical liposome targeting of dyes, melanins, genes, and proteins selectively to hair follicles.

    PubMed

    Hoffman, R M

    1998-01-01

    For therapeutic and cosmetic modification of hair, we have developed a hair-follicle-selective macromolecule and small molecule targeting system with topical application of phosphatidylcholine-based liposomes. Liposome-entrapped melanins, proteins, genes, and small-molecules have been selectively targeted to the hair follicle and hair shafts of mice. Liposomal delivery of these molecules is time dependent. Negligible amounts of delivered molecules enter the dermis, epidermis, or bloodstream thereby demonstrating selective follicle delivery. Naked molecules are trapped in the stratum corneum and are unable to enter the follicle. The potential of the hair-follicle liposome delivery system for therapeutic use for hair disease as well as for cosmesis has been demonstrated in 3-dimensional histoculture of hair-growing skin and mouse in vivo models. Topical liposome selective delivery to hair follicles has demonstrated the ability to color hair with melanin, the delivery of the active lac-Z gene to hair matrix cells and delivery of proteins as well. Liposome-targeting of molecules to hair follicles has also been achieved in human scalp in histoculture. Liposomes thus have high potential in selective hair follicle targeting of large and small molecules, including genes, opening the field of gene therapy and other molecular therapy of the hair process to restore hair growth, physiologically restore or alter hair pigment, and to prevent or accelerate hair loss.

  4. Active surfaces engineered by immobilizing protein-polymer nanoreactors for selectively detecting sugar alcohols.

    PubMed

    Zhang, Xiaoyan; Lomora, Mihai; Einfalt, Tomaz; Meier, Wolfgang; Klein, Noreen; Schneider, Dirk; Palivan, Cornelia G

    2016-05-01

    We introduce active surfaces generated by immobilizing protein-polymer nanoreactors on a solid support for sensitive sugar alcohols detection. First, such selective nanoreactors were engineered in solution by simultaneous encapsulation of specific enzymes in copolymer polymersomes, and insertion of membrane proteins for selective conduct of sugar alcohols. Despite the artificial surroundings, and the thickness of the copolymer membrane, functionality of reconstituted Escherichia coli glycerol facilitator (GlpF) was preserved, and allowed selective diffusion of sugar alcohols to the inner cavity of the polymersome, where encapsulated ribitol dehydrogenase (RDH) enzymes served as biosensing entities. Ribitol, selected as a model sugar alcohol, was detected quantitatively by the RDH-nanoreactors with GlpF-mediated permeability in a concentration range of 1.5-9 mM. To obtain "active surfaces" for detecting sugar alcohols, the nanoreactors optimized in solution were then immobilized on a solid support: aldehyde groups exposed at the compartment external surface reacted via an aldehyde-amino reaction with glass surfaces chemically modified with amino groups. The nanoreactors preserved their architecture and activity after immobilization on the glass surface, and represent active biosensing surfaces for selective detection of sugar alcohols, with high sensitivity.

  5. Nonlinear Models for Protein Folding and Function

    NASA Astrophysics Data System (ADS)

    Cruzeiro, L.

    Earlier a specific kinetic process for reproducible protein folding was proposed according to which the nascent chain is helical and the first step in in vivo protein folding is the bending of the initial helix at specific amino acid sites. Here the theoretical feasibility of this kinetic process is tested. To that end, two proteins, one belonging to the mainly α class and the other belonging to the α/β class, are selected and targeted molecular dynamics is applied to generate folding pathways for those two proteins, starting from two well defined initial conformations: a fully extended and a α-helical conformation. Not only are the native states closer to an initial helical structure for both proteins but also the pathways from the α-helical initial conformation to the native state have lower potential energy than the pathways that start from the fully extended conformation. For the α/β protein, 30% (40%) of the pathways from an initial α-helix (fully extended) structure lead to unentangled native folds, a success rate that can be increased to 85% by the introduction of a putative intermediate structure. These results lend support to the kinetic process proposed and open up a new direction in which to look for a solution to the protein folding problem. The chapter ends with a section that emphasizes the formal similarities between the dynamics quantum vibrational excited states in proteins and electrons in nonlinear lattices.

  6. Targeting prion-like protein doppel selectively suppresses tumor angiogenesis

    PubMed Central

    Al-Hilal, Taslim A.; Chung, Seung Woo; Choi, Jeong Uk; Kim, Seong Who; Kim, Sang Yoon; Ahsan, Fakhrul; Kim, In-San

    2016-01-01

    Controlled and site-specific regulation of growth factor signaling remains a major challenge for current antiangiogenic therapies, as these antiangiogenic agents target normal vasculature as well tumor vasculature. In this article, we identified the prion-like protein doppel as a potential therapeutic target for tumor angiogenesis. We investigated the interactions between doppel and VEGFR2 and evaluated whether blocking the doppel/VEGFR2 axis suppresses the process of angiogenesis. We discovered that tumor endothelial cells (TECs), but not normal ECs, express doppel; tumors from patients and mouse xenografts expressed doppel in their vasculatures. Induced doppel overexpression in ECs enhanced vascularization, whereas doppel constitutively colocalized and complexed with VEGFR2 in TECs. Doppel inhibition depleted VEGFR2 from the cell membrane, subsequently inducing the internalization and degradation of VEGFR2 and thereby attenuating VEGFR2 signaling. We also synthesized an orally active glycosaminoglycan (LHbisD4) that specifically binds with doppel. We determined that LHbisD4 concentrates over the tumor site and that genetic loss of doppel in TECs decreases LHbisD4 binding and targeting both in vitro and in vivo. Moreover, LHbisD4 eliminated VEGFR2 from the cell membrane, prevented VEGF binding in TECs, and suppressed tumor growth. Together, our results demonstrate that blocking doppel can control VEGF signaling in TECs and selectively inhibit tumor angiogenesis. PMID:26950422

  7. Targeting prion-like protein doppel selectively suppresses tumor angiogenesis.

    PubMed

    Al-Hilal, Taslim A; Chung, Seung Woo; Choi, Jeong Uk; Alam, Farzana; Park, Jooho; Kim, Seong Who; Kim, Sang Yoon; Ahsan, Fakhrul; Kim, In-San; Byun, Youngro

    2016-04-01

    Controlled and site-specific regulation of growth factor signaling remains a major challenge for current antiangiogenic therapies, as these antiangiogenic agents target normal vasculature as well tumor vasculature. In this article, we identified the prion-like protein doppel as a potential therapeutic target for tumor angiogenesis. We investigated the interactions between doppel and VEGFR2 and evaluated whether blocking the doppel/VEGFR2 axis suppresses the process of angiogenesis. We discovered that tumor endothelial cells (TECs), but not normal ECs, express doppel; tumors from patients and mouse xenografts expressed doppel in their vasculatures. Induced doppel overexpression in ECs enhanced vascularization, whereas doppel constitutively colocalized and complexed with VEGFR2 in TECs. Doppel inhibition depleted VEGFR2 from the cell membrane, subsequently inducing the internalization and degradation of VEGFR2 and thereby attenuating VEGFR2 signaling. We also synthesized an orally active glycosaminoglycan (LHbisD4) that specifically binds with doppel. We determined that LHbisD4 concentrates over the tumor site and that genetic loss of doppel in TECs decreases LHbisD4 binding and targeting both in vitro and in vivo. Moreover, LHbisD4 eliminated VEGFR2 from the cell membrane, prevented VEGF binding in TECs, and suppressed tumor growth. Together, our results demonstrate that blocking doppel can control VEGF signaling in TECs and selectively inhibit tumor angiogenesis. PMID:26950422

  8. COARSE-GRAINED MODELING OF PROTEIN UNFOLDING DYNAMICS*

    PubMed Central

    DENG, MINGGE

    2014-01-01

    We present a new dynamic elastic network model (DENM) that describes the unfolding process of a force-loaded protein. The protein interaction network and its potentials are constructed based on information of its native-state structure obtained from the Protein Data Bank, with network nodes positioned at the Cα coordinates of the protein backbone. Specifically, to mimic the unfolding process, i.e., to simulate the process of overcoming the local energy barrier on the free energy landscape with force loading, the noncovalent protein network bonds (i.e., hydrogen bonds, salt bridges, hydrophobic contacts, etc.) are broken one-by-one with a certain probability, while the strong covalent bonds along the backbone (i.e., peptide bonds, disulfide bonds, etc.) are kept intact. The jumping event from local energy minima (bonds breaking rate) are chosen according to Kramer’s theory and the Bell model. Moreover, we exploit the self-similar structure of proteins at different scales to design an effective coarse-graining procedure for DENM with optimal parameter selection. The robustness of DENM is validated by coarse-grained molecular dynamics (MD) simulation against atomistic MD simulation of force-extension processes of the Fibrinogen and Titin Immunoglobulin proteins. We observe that the native structure of the proteins determines the total unfolding dynamics (including large deviations) and not just the fluctuations around the native state. PMID:25400515

  9. Autocrine selection of a GLP-1R G-protein biased agonist with potent antidiabetic effects

    PubMed Central

    Zhang, Hongkai; Sturchler, Emmanuel; Zhu, Jiang; Nieto, Ainhoa; Cistrone, Philip A.; Xie, Jia; He, LinLing; Yea, Kyungmoo; Jones, Teresa; Turn, Rachel; Di Stefano, Peter S.; Griffin, Patrick R.; Dawson, Philip E.; McDonald, Patricia H.; Lerner, Richard A.

    2015-01-01

    Glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) agonists have emerged as treatment options for type 2 diabetes mellitus (T2DM). GLP-1R signals through G-protein-dependent, and G-protein-independent pathways by engaging the scaffold protein β-arrestin; preferential signalling of ligands through one or the other of these branches is known as ‘ligand bias'. Here we report the discovery of the potent and selective GLP-1R G-protein-biased agonist, P5. We identified P5 in a high-throughput autocrine-based screening of large combinatorial peptide libraries, and show that P5 promotes G-protein signalling comparable to GLP-1 and Exendin-4, but exhibited a significantly reduced β-arrestin response. Preclinical studies using different mouse models of T2DM demonstrate that P5 is a weak insulin secretagogue. Nevertheless, chronic treatment of diabetic mice with P5 increased adipogenesis, reduced adipose tissue inflammation as well as hepatic steatosis and was more effective at correcting hyperglycaemia and lowering haemoglobin A1c levels than Exendin-4, suggesting that GLP-1R G-protein-biased agonists may provide a novel therapeutic approach to T2DM. PMID:26621478

  10. Thermodynamically important contacts in folding of model proteins.

    PubMed

    Scala, A; Dokholyan, N V; Buldyrev, S V; Stanley, H E

    2001-03-01

    We introduce a quantity, the entropic susceptibility, that measures the thermodynamic importance-for the folding transition-of the contacts between amino acids in model proteins. Using this quantity, we find that only one equilibrium run of a computer simulation of a model protein is sufficient to select a subset of contacts that give rise to the peak in the specific heat observed at the folding transition. To illustrate the method, we identify thermodynamically important contacts in a model 46-mer. We show that only about 50% of all contacts present in the protein native state are responsible for the sharp peak in the specific heat at the folding transition temperature, while the remaining 50% of contacts do not affect the specific heat.

  11. Improved modeling of GPS selective availability

    NASA Technical Reports Server (NTRS)

    Braasch, Michael S.; Fink, Annmarie; Duffus, Keith

    1994-01-01

    Selective Availability (SA) represents the dominant error source for stand-alone users of the Global Positioning System (GPS). Even for DGPS, SA mandates the update rate required for a desired level of accuracy in realtime applications. As was witnessed in the recent literature, the ability to model this error source is crucial to the proper evaluation of GPS-based systems. A variety of SA models were proposed to date; however, each has its own shortcomings. Most of these models were based on limited data sets or data which were corrupted by additional error sources. A comprehensive treatment of the problem is presented. The phenomenon of SA is discussed and a technique is presented whereby both clock and orbit components of SA are identifiable. Extensive SA data sets collected from Block 2 satellites are presented. System Identification theory then is used to derive a robust model of SA from the data. This theory also allows for the statistical analysis of SA. The stationarity of SA over time and across different satellites is analyzed and its impact on the modeling problem is discussed.

  12. A Theoretical Lower Bound for Selection on the Expression Levels of Proteins

    PubMed Central

    Price, Morgan N.; Arkin, Adam P.

    2016-01-01

    We use simple models of the costs and benefits of microbial gene expression to show that changing a protein’s expression away from its optimum by 2-fold should reduce fitness by at least 0.2·P, where P is the fraction the cell’s protein that the gene accounts for. As microbial genes are usually expressed at above 5 parts per million, and effective population sizes are likely to be above 106, this implies that 2-fold changes to gene expression levels are under strong selection, as Ne·s≫1, where Ne is the effective population size and s is the selection coefficient. Thus, most gene duplications should be selected against. On the other hand, we predict that for most genes, small changes in the expression will be effectively neutral. PMID:27289091

  13. Automated hydrophobic interaction chromatography column selection for use in protein purification.

    PubMed

    Murphy, Patrick J M; Stone, Orrin J; Anderson, Michelle E

    2011-01-01

    which HIC media should be employed for future, more exhaustive optimization experiments and protein purification runs (4). The specific protein being purified here is recombinant green fluorescent protein (GFP); however, the approach may be adapted for purifying other proteins with one or more hydrophobic surface regions. GFP serves as a useful model protein, due to its stability, unique light absorbance peak at 397 nm, and fluorescence when exposed to UV light (5). Bacterial lysate containing wild type GFP was prepared in a high-salt buffer, loaded into a Bio-Rad DuoFlow medium pressure liquid chromatography system, and adsorbed to HiTrap HIC columns containing different HIC media. The protein was eluted from the columns and analyzed by in-line and post-run detection methods. Buffer blending, dynamic sample loop injection, sequential column selection, multi-wavelength analysis, and split fraction eluate collection increased the functionality of the system and reproducibility of the experimental approach. PMID:21968976

  14. Modeling protein synthesis from a physicist's perspective: A toy model

    NASA Astrophysics Data System (ADS)

    Basu, Aakash; Chowdhury, Debashish

    2007-10-01

    Proteins are polymers of amino acids. These macromolecules are synthesized by intracellular machines called ribosomes. Although the experimental investigation of protein synthesis has been a traditional area of research in molecular cell biology, important quantitative models of protein synthesis have been reported in research journals devoted to statistical physics and related interdisciplinary topics. From the perspective of a physicist, protein synthesis is the classical transport of interacting ribosomes on a messenger RNA (mRNA) template that dictates the sequence of the amino acids on the protein. We discuss appropriate simplification of the models and methods. In particular, we develop and analyze a simple toy model using some elementary techniques of nonequilibrium statistical mechanics and predict the average rate of protein synthesis and the spatial organization of the ribosomes in the steady state.

  15. A novel inducible protein production system and neomycin resistance as selection marker for Methanosarcina mazei.

    PubMed

    Mondorf, Sebastian; Deppenmeier, Uwe; Welte, Cornelia

    2012-01-01

    Methanosarcina mazei is one of the model organisms for the methanogenic order Methanosarcinales whose metabolism has been studied in detail. However, the genetic toolbox is still limited. This study was aimed at widening the scope of utilizable methods in this group of organisms. (i) Proteins specific to methanogens are oftentimes difficult to produce in E. coli. However, a protein production system is not available for methanogens. Here we present an inducible system to produce Strep-tagged proteins in Ms. mazei. The promoter p1687, which directs the transcription of methyl transferases that demethylate methylamines, was cloned into plasmid pWM321 and its activity was determined by monitoring β-glucuronidase production. The promoter was inactive during growth on methanol but was rapidly activated when trimethylamine was added to the medium. The gene encoding the β-glucuronidase from E. coli was fused to a Strep-tag and was cloned downstream of the p1687 promoter. The protein was overproduced in Ms. mazei and was purified in an active form by affinity chromatography. (ii) Puromycin is currently the only antibiotic used as a selectable marker in Ms. mazei and its relatives. We established neomycin resistance as a second selectable marker by designing a plasmid that confers neomycin resistance in Ms. mazei.

  16. Modeling the "glass" transition in proteins.

    PubMed

    Sitnitsky, A E

    2002-02-01

    A model of a protein as a disordered system of identical spherical particles (which imitate protein side chains) interacting with each other via a repulsive soft sphere potential U(r) infinity r(-beta) is constructed. The particles undergo the conformational motion (CM) within their own harmonic conformational potentials around some mean equilibrium positions ascribed by the tertiary structure of the protein. A first principles calculation of the positional correlation functions for the CM is carried out. The general analysis is exemplified by the case in which the mean equilibrium positions of the particles form a cubic tightly-packed (face- centered) lattice (each particle has 12 nearest neighbors) with the step b(hydr) =6.6 A (the average distance between the centers of mass of hydrated protein subunits). The model yields dramatic slowing down of the relaxation with the decrease of temperature followed by a sharp glass transition at some crossover temperature T(c) < 200 K. At the transition the liquid-like dynamic behavior (the correlation functions tend to zero with time) is altered by the glass-like one (the correlation functions tend with time to some non-zero limit). In the liquid-like region above the crossover temperature the relaxation exhibits distinct alpha-process following the beta-one. The glass transition results from the interaction of the particles. Thus the model suggests that namely direct interactions of the fragments of protein structure rather than protein-solvent interactions are the origin of the phenomenon of the glass transition. The known increase of T(c) up to 300 K at dehydration of the protein is attributed to the known concomitant compression of the globule upon drying by about 4-6% so that positions of individual atoms displace by about 0.6 A (modeled by the decrease of the step of the lattice b by 0.6 A so that b(dehydr)=6 A). The model suggests that the solvent influences the phenomenon of the glass transition indirectly

  17. An Enzyme Cascade for Selective Modification of Tyrosine Residues in Structurally Diverse Peptides and Proteins.

    PubMed

    Struck, Anna-Winona; Bennett, Matthew R; Shepherd, Sarah A; Law, Brian J C; Zhuo, Ying; Wong, Lu Shin; Micklefield, Jason

    2016-03-01

    Bioorthogonal chemistry enables a specific moiety in a complex biomolecule to be selectively modified in the presence of many reactive functional groups and other cellular entities. Such selectivity has become indispensable in biology, enabling biomolecules to be derivatized, conjugated, labeled, or immobilized for imaging, biochemical assays, or therapeutic applications. Methyltransferase enzymes (MTase) that accept analogues of the cofactor S-adenosyl methionine have been widely deployed for alkyl-diversification and bioorthogonal labeling. However, MTases typically possess tight substrate specificity. Here we introduce a more flexible methodology for selective derivatization of phenolic moieties in complex biomolecules. Our approach relies on the tandem enzymatic reaction of a fungal tyrosinase and the mammalian catechol-O-methyltransferase (COMT), which can effect the sequential hydroxylation of the phenolic group to give an intermediate catechol moiety that is subsequently O-alkylated. When used in this combination, the alkoxylation is highly selective for tyrosine residues in peptides and proteins, yet remarkably tolerant to changes in the peptide sequence. Tyrosinase-COMT are shown to provide highly versatile and regioselective modification of a diverse range of substrates including peptide antitumor agents, hormones, cyclic peptide antibiotics, and model proteins. PMID:26867114

  18. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  19. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    PubMed Central

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-01-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases. PMID:26608097

  20. Selective, rapid and optically switchable regulation of protein function in live mammalian cells

    NASA Astrophysics Data System (ADS)

    Tsai, Yu-Hsuan; Essig, Sebastian; James, John R.; Lang, Kathrin; Chin, Jason W.

    2015-07-01

    The rapid and selective regulation of a target protein within living cells that contain closely related family members is an outstanding challenge. Here we introduce genetically directed bioorthogonal ligand tethering (BOLT) and demonstrate selective inhibition (iBOLT) of protein function. In iBOLT, inhibitor-conjugate/target protein pairs are created where the target protein contains a genetically encoded unnatural amino acid with bioorthogonal reactivity and the inhibitor conjugate contains a complementary bioorthogonal group. iBOLT enables the first rapid and specific inhibition of MEK isozymes, and introducing photoisomerizable linkers in the inhibitor conjugate enables reversible, optical regulation of protein activity (photo-BOLT) in live mammalian cells. We demonstrate that a pan kinase inhibitor conjugate allows selective and rapid inhibition of the lymphocyte specific kinase, indicating the modularity and scalability of BOLT. We anticipate that BOLT will enable the rapid and selective regulation of diverse proteins for which no selective small-molecule ligands exist.

  1. Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins

    PubMed Central

    2013-01-01

    Background Current immunological bioinformatic approaches focus on the prediction of allele-specific epitopes capable of triggering immunogenic activity. The prediction of major histocompatibility complex (MHC) class I epitopes is well studied, and various software solutions exist for this purpose. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection. Results We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic organisms. We evaluated our computational approach by using the Mycobacterium tuberculosis (Mtb) H37Rv exoproteome as a gold standard model. A literature search was carried out on 60 out of 553 Mtb's predicted exoproteins, looking for previous experimental evidence concerning their possible antigenicity. Half of the 60 proteins were classified as highest scored by the MED statistic, while the other half were classified as lowest scored. Among the lowest scored proteins, ~13% were confirmed as not related to antigenicity or not contributing to the bacterial pathogenicity, and 70% of the highest scored proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online at http://med.mmci.uni-saarland.de/. Conclusions The software presented here offers a practical and accurate method to identify potential vaccine and diagnosis candidates against

  2. Solubilization and electrophoretic characterization of select edible nut seed proteins.

    PubMed

    Sathe, Shridhar K; Venkatachalam, Mahesh; Sharma, Girdhari M; Kshirsagar, Harshal H; Teuber, Suzanne S; Roux, Kenneth H

    2009-09-01

    The solubility of almond, Brazil nut, cashew nut, hazelnut, macadamia, pecan, pine nut, pistachio, walnut, and peanut proteins in several aqueous solvents was qualitatively and quantitatively assessed. In addition, the effects of extraction time and ionic strength on protein solubility were also investigated. Electrophoresis and protein determination (Lowry, Bradford, and micro-Kjeldahl) methods were used for qualitative and quantitative assessment of proteins, respectively. Depending on the seed, buffer type and ionic strength significantly affected protein solubility. The results suggest that buffered sodium borate (BSB; 0.1 M H(3)BO(3), 0.025 M Na(2)B(4)O(7), 0.075 M NaCl, pH 8.45) optimally solubilizes nut seed proteins. Qualitative differences in seed protein electrophoretic profiles were revealed. For a specific seed type, these differences were dependent on the solvent(s) used to solubilize the seed proteins. SDS-PAGE results suggest the polypeptide molecular mass range for the tree nut seed proteins to be 3-100 kDa. The results of native IEF suggested that the proteins were mainly acidic, with a pI range from >4.5 to <7.0. Western immunoblotting experiments indicated that rabbit polyclonal antibodies recognized substantially the same polypeptides as those recognized by the corresponding pooled patient sera IgE.

  3. Solubilization and electrophoretic characterization of select edible nut seed proteins.

    PubMed

    Sathe, Shridhar K; Venkatachalam, Mahesh; Sharma, Girdhari M; Kshirsagar, Harshal H; Teuber, Suzanne S; Roux, Kenneth H

    2009-09-01

    The solubility of almond, Brazil nut, cashew nut, hazelnut, macadamia, pecan, pine nut, pistachio, walnut, and peanut proteins in several aqueous solvents was qualitatively and quantitatively assessed. In addition, the effects of extraction time and ionic strength on protein solubility were also investigated. Electrophoresis and protein determination (Lowry, Bradford, and micro-Kjeldahl) methods were used for qualitative and quantitative assessment of proteins, respectively. Depending on the seed, buffer type and ionic strength significantly affected protein solubility. The results suggest that buffered sodium borate (BSB; 0.1 M H(3)BO(3), 0.025 M Na(2)B(4)O(7), 0.075 M NaCl, pH 8.45) optimally solubilizes nut seed proteins. Qualitative differences in seed protein electrophoretic profiles were revealed. For a specific seed type, these differences were dependent on the solvent(s) used to solubilize the seed proteins. SDS-PAGE results suggest the polypeptide molecular mass range for the tree nut seed proteins to be 3-100 kDa. The results of native IEF suggested that the proteins were mainly acidic, with a pI range from >4.5 to <7.0. Western immunoblotting experiments indicated that rabbit polyclonal antibodies recognized substantially the same polypeptides as those recognized by the corresponding pooled patient sera IgE. PMID:19655801

  4. Modeling of protein misfolding in disease.

    PubMed

    Małolepsza, Edyta B

    2008-01-01

    A short review of the results of molecular modeling of prion disease is presented in this chapter. According to the "one-protein theory" proposed by Prusiner, prion proteins are misfolded naturally occurring proteins, which, on interaction with correctly folded proteins may induce misfolding and propagate the disease, resulting in insoluble amyloid aggregates in cells of affected specimens. Because of experimental difficulties in measurements of origin and growth of insoluble amyloid aggregations in cells, theoretical modeling is often the only one source of information regarding the molecular mechanism of the disease. Replica exchange Monte Carlo simulations presented in this chapter indicate that proteins in the native state, N, on interaction with an energetically higher structure, R, can change their conformation into R and form a dimer, R(2). The addition of another protein in the N state to R(2) may lead to spontaneous formation of a trimer, R(3). These results reveal the molecular basis for a model of prion disease propagation or conformational diseases in general. PMID:18446294

  5. Bayesian model selection analysis of WMAP3

    SciTech Connect

    Parkinson, David; Mukherjee, Pia; Liddle, Andrew R.

    2006-06-15

    We present a Bayesian model selection analysis of WMAP3 data using our code CosmoNest. We focus on the density perturbation spectral index n{sub S} and the tensor-to-scalar ratio r, which define the plane of slow-roll inflationary models. We find that while the Bayesian evidence supports the conclusion that n{sub S}{ne}1, the data are not yet powerful enough to do so at a strong or decisive level. If tensors are assumed absent, the current odds are approximately 8 to 1 in favor of n{sub S}{ne}1 under our assumptions, when WMAP3 data is used together with external data sets. WMAP3 data on its own is unable to distinguish between the two models. Further, inclusion of r as a parameter weakens the conclusion against the Harrison-Zel'dovich case (n{sub S}=1, r=0), albeit in a prior-dependent way. In appendices we describe the CosmoNest code in detail, noting its ability to supply posterior samples as well as to accurately compute the Bayesian evidence. We make a first public release of CosmoNest, now available at www.cosmonest.org.

  6. Correcting for selection using frailty models.

    PubMed

    Olesen, Anne Vingaard; Parner, Erik Thorlund

    2006-05-30

    Chronic diseases are roughly speaking lifelong transitions between the states: relapse and recovery. The long-term pattern of recurrent times-to-relapse can be investigated with routine register data on hospital admissions. The relapses become readmissions to hospital, and the time spent in hospital are gaps between subsequent times-at-risk. However, problems of selection and dependent censoring arise because the calendar period of observation is limited and the study population likely to be heterogeneous. We will theoretically verify that an assumption of conditional independence of all times-at-risk and gaps, given the latent individual frailty level, allows for consistent inference in the shared frailty model. Using simulation studies, we also investigate cases where gaps (and/or staggered entry) are informative for the individual frailty. We found that the use of the shared frailty model can be extended to situations, where gaps are dependent on the frailty, but short compared to the distribution of the times-to-relapse. Our motivating example deals with the course of schizophrenia. We analysed routine register data on readmissions in almost 9000 persons with the disorder. Marginal survival curves of time-to-first-readmission, time-to-second-readmission, etc. were estimated in the shared frailty model. Based on the schizophrenia literature, the conclusion of our analysis was rather surprising: one of a stable course of disorder. PMID:16252271

  7. Modeling selective local interactions with memory

    PubMed Central

    Galante, Amanda; Levy, Doron

    2012-01-01

    Recently we developed a stochastic particle system describing local interactions between cyanobacteria. We focused on the common freshwater cyanobacteria Synechocystis sp., which are coccoidal bacteria that utilize group dynamics to move toward a light source, a motion referred to as phototaxis. We were particularly interested in the local interactions between cells that were located in low to medium density areas away from the front. The simulations of our stochastic particle system in 2D replicated many experimentally observed phenomena, such as the formation of aggregations and the quasi-random motion of cells. In this paper, we seek to develop a better understanding of group dynamics produced by this model. To facilitate this study, we replace the stochastic model with a system of ordinary differential equations describing the evolution of particles in 1D. Unlike many other models, our emphasis is on particles that selectively choose one of their neighbors as the preferred direction of motion. Furthermore, we incorporate memory by allowing persistence in the motion. We conduct numerical simulations which allow us to efficiently explore the space of parameters, in order to study the stability, size, and merging of aggregations. PMID:24244060

  8. Entropic Priors and Bayesian Model Selection

    NASA Astrophysics Data System (ADS)

    Brewer, Brendon J.; Francis, Matthew J.

    2009-12-01

    We demonstrate that the principle of maximum relative entropy (ME), used judiciously, can ease the specification of priors in model selection problems. The resulting effect is that models that make sharp predictions are disfavoured, weakening the usual Bayesian ``Occam's Razor.'' This is illustrated with a simple example involving what Jaynes called a ``sure thing'' hypothesis. Jaynes' resolution of the situation involved introducing a large number of alternative ``sure thing'' hypotheses that were possible before we observed the data. However, in more complex situations, it may not be possible to explicitly enumerate large numbers of alternatives. The entropic priors formalism produces the desired result without modifying the hypothesis space or requiring explicit enumeration of alternatives; all that is required is a good model for the prior predictive distribution for the data. This idea is illustrated with a simple rigged-lottery example, and we outline how this idea may help to resolve a recent debate amongst cosmologists: is dark energy a cosmological constant, or has it evolved with time in some way? And how shall we decide, when the data are in?

  9. Selecting a model of supersymmetry breaking mediation

    SciTech Connect

    AbdusSalam, S. S.; Allanach, B. C.; Dolan, M. J.; Feroz, F.; Hobson, M. P.

    2009-08-01

    We study the problem of selecting between different mechanisms of supersymmetry breaking in the minimal supersymmetric standard model using current data. We evaluate the Bayesian evidence of four supersymmetry breaking scenarios: mSUGRA, mGMSB, mAMSB, and moduli mediation. The results show a strong dependence on the dark matter assumption. Using the inferred cosmological relic density as an upper bound, minimal anomaly mediation is at least moderately favored over the CMSSM. Our fits also indicate that evidence for a positive sign of the {mu} parameter is moderate at best. We present constraints on the anomaly and gauge mediated parameter spaces and some previously unexplored aspects of the dark matter phenomenology of the moduli mediation scenario. We use sparticle searches, indirect observables and dark matter observables in the global fit and quantify robustness with respect to prior choice. We quantify how much information is contained within each constraint.

  10. Selective quantitative bioanalysis of proteins in biological fluids by on-line immunoaffinity chromatography-protein digestion-liquid chromatography-mass spectrometry.

    PubMed

    Hoos, Johannes S; Sudergat, Hilke; Hoelck, Jens-Peter; Stahl, Mark; de Vlieger, Jon S B; Niessen, Wilfried M A; Lingeman, Henk; Irth, Hubertus

    2006-01-18

    A quantitative method for the determination of proteins in complex biological matrices has been developed based on the selectivity of antibodies for sample purification followed by proteolytic digestion and quantitative mass spectrometry. An immunosorbent of polyclonal anti-bovine serum albumin (BSA) antibodies immobilized on CNBR agarose is used in the on-line mode for selective sample pretreatment. Next, the purified sample is trypsin digested to obtain protein specific peptide markers. Subsequent analysis of the peptide mixture using a desalination procedure and a separation step coupled, on-line to an ion-trap mass spectrometer, reveals that this method enables selective determination of proteins in biological matrices like diluted human plasma. This approach enhances substantially the selectivity compared to common quantitative analysis executed with immunoassays and colorimetry, fluorimetry or luminescence detection. Hyphenation of the immunoaffinity chromatography with on-line digestion and chromatography-mass spectrometry is performed and a completely on-line quantification of the model protein BSA in bovine and human urine was established. A detection limit of 170 nmol/l and a quantification limit of 280 nmol/l is obtained using 50 microl of either standard or spiked biological matrix. The model system allows fully automated absolute quantitative mass spectrometric analysis of intact proteins in biological matrices without time-consuming labeling procedures.

  11. Newton, Einstein, Jeffreys and Bayesian model selection

    NASA Astrophysics Data System (ADS)

    Chettri, Samir; Batchelor, David; Campbell, William; Balakrishnan, Karthik

    2005-11-01

    In Jefferys and Berger apply Bayesian model selection to the problem of choosing between rival theories, in particular between Einstein's theory of general relativity (GR) and Newtonian gravity (NG). [1] presents a debate between Harold Jeffreys and Charles Poor regarding the observed 43''/century anomalous perhelion precession of Mercury. GR made a precise prediction of 42.98''/century while proponents of NG suggested several physical mechanisms that were eventually refuted, with the exception of a modified inverse square law. Using Bayes Factors (BF) and data available in 1921, shows that GR is preferable to NG by a factor of about 25 to 1. A scale for BF used by Jeffreys, suggests that this is positive to strong evidence for GR over modified NG but it is not very strong or even overwhelming. In this work we calculate the BF from the period 1921 till 1993. By 1960 we see that the BF, due to better data gathering techniques and advances in technology, had reached a factor of greater than 100 to 1, making GR strongly preferable to NG and by 1990 the BF reached 1000:1. Ironically while BF had reached a state of near certainty even in 1960 rival theories of gravitation were on the rise - notably the Brans-Dicke (BD) scalar-tensor theory of gravity. The BD theory is postulated in such a way that for small positive values of a scalar parameter ω, the BF would favor GR while the BF would approach unity with certainty as ω grows larger, at which point either theory would be prefered, i.e., it is a theory that cannot lose. Does this mean Bayesian model selection needs to be overthrown? This points to the need for cogent prior information guided by physics and physical experiment.

  12. Duplication, selection and gene conversion in a Drosophila mojavensis female reproductive protein family.

    PubMed

    Kelleher, Erin S; Markow, Therese A

    2009-04-01

    Protein components of the Drosophila male ejaculate, several of which evolve rapidly, are critical modulators of reproductive success. Recent studies of female reproductive tract proteins indicate they also are extremely divergent between species, suggesting that reproductive molecules may coevolve between the sexes. Our current understanding of intersexual coevolution, however, is severely limited by the paucity of genetic and evolutionary studies on the female molecules involved. Physiological evidence of ejaculate-female coadaptation, paired with a promiscuous mating system, makes Drosophila mojavensis an exciting model system in which to study the evolution of reproductive proteins. Here we explore the evolutionary dynamics of a five-paralog gene family of female reproductive proteases within populations of D. mojavensis and throughout the repleta species group. We show that the proteins have experienced ongoing gene duplication and adaptive evolution and further exhibit dynamic patterns of pseudogenation, copy number variation, gene conversion, and selection within geographically isolated populations of D. mojavensis. The integration of these patterns in a single gene family has never before been documented in a reproductive protein.

  13. Duplication, Selection and Gene Conversion in a Drosophila mojavensis Female Reproductive Protein Family

    PubMed Central

    Kelleher, Erin S.; Markow, Therese A.

    2009-01-01

    Protein components of the Drosophila male ejaculate, several of which evolve rapidly, are critical modulators of reproductive success. Recent studies of female reproductive tract proteins indicate they also are extremely divergent between species, suggesting that reproductive molecules may coevolve between the sexes. Our current understanding of intersexual coevolution, however, is severely limited by the paucity of genetic and evolutionary studies on the female molecules involved. Physiological evidence of ejaculate–female coadaptation, paired with a promiscuous mating system, makes Drosophila mojavensis an exciting model system in which to study the evolution of reproductive proteins. Here we explore the evolutionary dynamics of a five-paralog gene family of female reproductive proteases within populations of D. mojavensis and throughout the repleta species group. We show that the proteins have experienced ongoing gene duplication and adaptive evolution and further exhibit dynamic patterns of pseudogenation, copy number variation, gene conversion, and selection within geographically isolated populations of D. mojavensis. The integration of these patterns in a single gene family has never before been documented in a reproductive protein. PMID:19204376

  14. Structural modeling of snow flea antifreeze protein.

    PubMed

    Lin, Feng-Hsu; Graham, Laurie A; Campbell, Robert L; Davies, Peter L

    2007-03-01

    The glycine-rich antifreeze protein recently discovered in snow fleas exhibits strong freezing point depression activity without significantly changing the melting point of its solution (thermal hysteresis). BLAST searches did not detect any protein with significant similarity in current databases. Based on its circular dichroism spectrum, discontinuities in its tripeptide repeat pattern, and intramolecular disulfide bonding, a detailed theoretical model is proposed for the 6.5-kDa isoform. In the model, the 81-residue protein is organized into a bundle of six short polyproline type II helices connected (with one exception) by proline-containing turns. This structure forms two sheets of three parallel helices, oriented antiparallel to each other. The central helices are particularly rich in glycines that facilitate backbone carbonyl-amide hydrogen bonding to four neighboring helices. The modeled structure has similarities to polyglycine II proposed by Crick and Rich in 1955 and is a close match to the polyproline type II antiparallel sheet structure determined by Traub in 1969 for (Pro-Gly-Gly)(n). Whereas the latter two structures are formed by intermolecular interactions, the snow flea antifreeze is stabilized by intramolecular interactions between the helices facilitated by the regularly spaced turns and disulfide bonds. Like several other antifreeze proteins, this modeled protein is amphipathic with a putative hydrophobic ice-binding face. PMID:17158562

  15. Structural modeling of snow flea antifreeze protein.

    PubMed

    Lin, Feng-Hsu; Graham, Laurie A; Campbell, Robert L; Davies, Peter L

    2007-03-01

    The glycine-rich antifreeze protein recently discovered in snow fleas exhibits strong freezing point depression activity without significantly changing the melting point of its solution (thermal hysteresis). BLAST searches did not detect any protein with significant similarity in current databases. Based on its circular dichroism spectrum, discontinuities in its tripeptide repeat pattern, and intramolecular disulfide bonding, a detailed theoretical model is proposed for the 6.5-kDa isoform. In the model, the 81-residue protein is organized into a bundle of six short polyproline type II helices connected (with one exception) by proline-containing turns. This structure forms two sheets of three parallel helices, oriented antiparallel to each other. The central helices are particularly rich in glycines that facilitate backbone carbonyl-amide hydrogen bonding to four neighboring helices. The modeled structure has similarities to polyglycine II proposed by Crick and Rich in 1955 and is a close match to the polyproline type II antiparallel sheet structure determined by Traub in 1969 for (Pro-Gly-Gly)(n). Whereas the latter two structures are formed by intermolecular interactions, the snow flea antifreeze is stabilized by intramolecular interactions between the helices facilitated by the regularly spaced turns and disulfide bonds. Like several other antifreeze proteins, this modeled protein is amphipathic with a putative hydrophobic ice-binding face.

  16. Modelling of DNA-protein recognition

    NASA Technical Reports Server (NTRS)

    Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.

    1980-01-01

    Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.

  17. Target selection by natural and redesigned PUF proteins

    PubMed Central

    Porter, Douglas F.; Koh, Yvonne Y.; VanVeller, Brett; Raines, Ronald T.; Wickens, Marvin

    2015-01-01

    Pumilio/fem-3 mRNA binding factor (PUF) proteins bind RNA with sequence specificity and modularity, and have become exemplary scaffolds in the reengineering of new RNA specificities. Here, we report the in vivo RNA binding sites of wild-type (WT) and reengineered forms of the PUF protein Saccharomyces cerevisiae Puf2p across the transcriptome. Puf2p defines an ancient protein family present throughout fungi, with divergent and distinctive PUF RNA binding domains, RNA-recognition motifs (RRMs), and prion regions. We identify sites in RNA bound to Puf2p in vivo by using two forms of UV cross-linking followed by immunopurification. The protein specifically binds more than 1,000 mRNAs, which contain multiple iterations of UAAU-binding elements. Regions outside the PUF domain, including the RRM, enhance discrimination among targets. Compensatory mutants reveal that one Puf2p molecule binds one UAAU sequence, and align the protein with the RNA site. Based on this architecture, we redesign Puf2p to bind UAAG and identify the targets of this reengineered PUF in vivo. The mutant protein finds its target site in 1,800 RNAs and yields a novel RNA network with a dramatic redistribution of binding elements. The mutant protein exhibits even greater RNA specificity than wild type. The redesigned protein decreases the abundance of RNAs in its redesigned network. These results suggest that reengineering using the PUF scaffold redirects and can even enhance specificity in vivo. PMID:26668354

  18. Target selection by natural and redesigned PUF proteins.

    PubMed

    Porter, Douglas F; Koh, Yvonne Y; VanVeller, Brett; Raines, Ronald T; Wickens, Marvin

    2015-12-29

    Pumilio/fem-3 mRNA binding factor (PUF) proteins bind RNA with sequence specificity and modularity, and have become exemplary scaffolds in the reengineering of new RNA specificities. Here, we report the in vivo RNA binding sites of wild-type (WT) and reengineered forms of the PUF protein Saccharomyces cerevisiae Puf2p across the transcriptome. Puf2p defines an ancient protein family present throughout fungi, with divergent and distinctive PUF RNA binding domains, RNA-recognition motifs (RRMs), and prion regions. We identify sites in RNA bound to Puf2p in vivo by using two forms of UV cross-linking followed by immunopurification. The protein specifically binds more than 1,000 mRNAs, which contain multiple iterations of UAAU-binding elements. Regions outside the PUF domain, including the RRM, enhance discrimination among targets. Compensatory mutants reveal that one Puf2p molecule binds one UAAU sequence, and align the protein with the RNA site. Based on this architecture, we redesign Puf2p to bind UAAG and identify the targets of this reengineered PUF in vivo. The mutant protein finds its target site in 1,800 RNAs and yields a novel RNA network with a dramatic redistribution of binding elements. The mutant protein exhibits even greater RNA specificity than wild type. The redesigned protein decreases the abundance of RNAs in its redesigned network. These results suggest that reengineering using the PUF scaffold redirects and can even enhance specificity in vivo. PMID:26668354

  19. Computational protein design is a challenge for implicit solvation models.

    PubMed

    Jaramillo, Alfonso; Wodak, Shoshana J

    2005-01-01

    Increasingly complex schemes for representing solvent effects in an implicit fashion are being used in computational analyses of biological macromolecules. These schemes speed up the calculations by orders of magnitude and are assumed to compromise little on essential features of the solvation phenomenon. In this work we examine this assumption. Five implicit solvation models, a surface area-based empirical model, two models that approximate the generalized Born treatment and a finite difference Poisson-Boltzmann method are challenged in situations differing from those where these models were calibrated. These situations are encountered in automatic protein design procedures, whose job is to select sequences, which stabilize a given protein 3D structure, from a large number of alternatives. To this end we evaluate the energetic cost of burying amino acids in thousands of environments with different solvent exposures belonging, respectively, to decoys built with random sequences and to native protein crystal structures. In addition we perform actual sequence design calculations. Except for the crudest surface area-based procedure, all the tested models tend to favor the burial of polar amino acids in the protein interior over nonpolar ones, a behavior that leads to poor performance in protein design calculations. We show, on the other hand, that three of the examined models are nonetheless capable of discriminating between the native fold and many nonnative alternatives, a test commonly used to validate force fields. It is concluded that protein design is a particularly challenging test for implicit solvation models because it requires accurate estimates of the solvation contribution of individual residues. This contrasts with native recognition, which depends less on solvation and more on other nonbonded contributions.

  20. MOPED: Model Organism Protein Expression Database.

    PubMed

    Kolker, Eugene; Higdon, Roger; Haynes, Winston; Welch, Dean; Broomall, William; Lancet, Doron; Stanberry, Larissa; Kolker, Natali

    2012-01-01

    Large numbers of mass spectrometry proteomics studies are being conducted to understand all types of biological processes. The size and complexity of proteomics data hinders efforts to easily share, integrate, query and compare the studies. The Model Organism Protein Expression Database (MOPED, htttp://moped.proteinspire.org) is a new and expanding proteomics resource that enables rapid browsing of protein expression information from publicly available studies on humans and model organisms. MOPED is designed to simplify the comparison and sharing of proteomics data for the greater research community. MOPED uniquely provides protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis. Data can be queried for specific proteins, browsed based on organism, tissue, localization and condition and sorted by false discovery rate and expression. MOPED empowers users to visualize their own expression data and compare it with existing studies. Further, MOPED links to various protein and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED contains over 43,000 proteins with at least one spectral match and more than 11 million high certainty spectra.

  1. Fast loop modeling for protein structures

    NASA Astrophysics Data System (ADS)

    Zhang, Jiong; Nguyen, Son; Shang, Yi; Xu, Dong; Kosztin, Ioan

    2015-03-01

    X-ray crystallography is the main method for determining 3D protein structures. In many cases, however, flexible loop regions of proteins cannot be resolved by this approach. This leads to incomplete structures in the protein data bank, preventing further computational study and analysis of these proteins. For instance, all-atom molecular dynamics (MD) simulation studies of structure-function relationship require complete protein structures. To address this shortcoming, we have developed and implemented an efficient computational method for building missing protein loops. The method is database driven and uses deep learning and multi-dimensional scaling algorithms. We have implemented the method as a simple stand-alone program, which can also be used as a plugin in existing molecular modeling software, e.g., VMD. The quality and stability of the generated structures are assessed and tested via energy scoring functions and by equilibrium MD simulations. The proposed method can also be used in template-based protein structure prediction. Work supported by the National Institutes of Health [R01 GM100701]. Computer time was provided by the University of Missouri Bioinformatics Consortium.

  2. Food Protein Functionality--A New Model.

    PubMed

    Foegeding, E Allen

    2015-12-01

    Proteins in foods serve dual roles as nutrients and structural building blocks. The concept of protein functionality has historically been restricted to nonnutritive functions--such as creating emulsions, foams, and gels--but this places sole emphasis on food quality considerations and potentially overlooks modifications that may also alter nutritional quality or allergenicity. A new model is proposed that addresses the function of proteins in foods based on the length scale(s) responsible for the function. Properties such as flavor binding, color, allergenicity, and digestibility are explained based on the structure of individual molecules; placing this functionality at the nano/molecular scale. At the next higher scale, applications in foods involving gelation, emulsification, and foam formation are based on how proteins form secondary structures that are seen at the nano and microlength scales, collectively called the mesoscale. The macroscale structure represents the arrangements of molecules and mesoscale structures in a food. Macroscale properties determine overall product appearance, stability, and texture. The historical approach of comparing among proteins based on forming and stabilizing specific mesoscale structures remains valid but emphasis should be on a common means for structure formation to allow for comparisons across investigations. For applications in food products, protein functionality should start with identification of functional needs across scales. Those needs are then evaluated relative to how processing and other ingredients could alter desired molecular scale properties, or proper formation of mesoscale structures. This allows for a comprehensive approach to achieving the desired function of proteins in foods.

  3. Identification of novel peptide substrates for protein farnesyltransferase reveals two substrate classes with distinct sequence selectivities

    PubMed Central

    Hougland, James L.; Hicks, Katherine A.; Hartman, Heather L.; Kelly, Rebekah A.; Watt, Terry J.; Fierke, Carol A.

    2010-01-01

    Prenylation is a post-translational modification essential for the proper localization and function of many proteins. Farnesylation, the attachment of a 15-carbon farnesyl group near the C-terminus of protein substrates, is catalyzed by protein farnesyltransferase (FTase). Farnesylation has received significant interest as a target for pharmaceutical development and farnesyltransferase inhibitors (FTIs) are in clinical trials as cancer therapeutics. However, as the total complement of prenylated proteins is unknown, the FTase substrates responsible for FTI efficacy are not yet understood. Identifying novel prenylated proteins within the human proteome constitutes an important step towards understanding prenylation-dependent cellular processes. Based on sequence preferences for FTase derived from analysis of known farnesylated proteins, we selected and screened a library of small peptides representing the C-termini of 213 human proteins for activity with FTase. We identified 77 novel FTase substrates that exhibit multiple-turnover reactivity within this library; our library also contained 85 peptides that can be farnesylated by FTase only under single-turnover conditions. Based on these results, a second library was designed that yielded an additional 29 novel multiple-turnover FTase substrates and 45 single-turnover substrates. The two classes of substrates exhibit different specificity requirements. Efficient multiple-turnover reactivity correlates with the presence of a nonpolar amino acid at the a2 position and a Phe, Met, or Gln at the terminal X residue, consistent with the proposed Ca1a2X sequence model. In contrast, the sequences of the single-turnover substrates vary significantly more at both the a2 and X residues and are not well-described by current farnesylation algorithms. These results improve the definition of prenyltransferase substrate specificity, test the efficacy of substrate algorithms, and provide valuable information about therapeutic targets

  4. Modeling protein assemblies in the proteome.

    PubMed

    Kuzu, Guray; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

    2014-03-01

    Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high- and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations.

  5. Molecular Mechanism of Selectivity among G Protein-Coupled Receptor Kinase 2 Inhibitors

    SciTech Connect

    Thal, David M.; Yeow, Raymond Y.; Schoenau, Christian; Huber, Jochen; Tesmer, John J.G.

    2012-07-11

    G protein-coupled receptors (GPCRs) are key regulators of cell physiology and control processes ranging from glucose homeostasis to contractility of the heart. A major mechanism for the desensitization of activated GPCRs is their phosphorylation by GPCR kinases (GRKs). Overexpression of GRK2 is strongly linked to heart failure, and GRK2 has long been considered a pharmaceutical target for the treatment of cardiovascular disease. Several lead compounds developed by Takeda Pharmaceuticals show high selectivity for GRK2 and therapeutic potential for the treatment of heart failure. To understand how these drugs achieve their selectivity, we determined crystal structures of the bovine GRK2-G{beta}{gamma} complex in the presence of two of these inhibitors. Comparison with the apoGRK2-G{beta}{gamma} structure demonstrates that the compounds bind in the kinase active site in a manner similar to that of the AGC kinase inhibitor balanol. Both balanol and the Takeda compounds induce a slight closure of the kinase domain, the degree of which correlates with the potencies of the inhibitors. Based on our crystal structures and homology modeling, we identified five amino acids surrounding the inhibitor binding site that we hypothesized could contribute to inhibitor selectivity. However, our results indicate that these residues are not major determinants of selectivity among GRK subfamilies. Rather, selectivity is achieved by the stabilization of a unique inactive conformation of the GRK2 kinase domain.

  6. Strategies for Selection from Protein Libraries Composed of de Novo Designed Secondary Structure Modules

    NASA Astrophysics Data System (ADS)

    Matsuura, Tomoaki; Plückthun, Andreas

    2004-02-01

    As more and more protein structures are determined, it has become clear that there is only a limited number of protein folds in nature. To explore whether the protein folds found in nature are the only solutions to the protein folding problem, or that a lack of evolutionary pressure causes the paucity of different protein folds found, we set out to construct protein libraries without any restriction on topology. We generated different libraries (all α-helix, all β-strand and α-helix plus β-strand) with an average length of 100 amino acid residues, composed of designed secondary structure modules (α-helix, β-strand and β-turn) in various proportions, based primarily on the patterning of polar and non-polar residues. From the analysis of proteins chosen randomly from the libraries, we found that a substantial portion of pure α-helical proteins show properties similar to native proteins. Using these libraries as a starting point, we aim to establish a selection system which allows us to enrich proteins with favorable folding properties (non-aggregating, compactly folded) from the libraries. We have developed such a method based on ribosome display. This selection is based on two concepts: (1) misfolded proteins are more sensitive to proteolysis, (2) misfolded and/or aggregated proteins are more hydrophobic. We show that by applying each of these selection criteria proteins that are compactly folded and soluble can be enriched over insoluble and random coil proteins.

  7. Beta-galactosidase and selective neutrality. [amino acid composition of proteins

    NASA Technical Reports Server (NTRS)

    Holmquist, R.

    1979-01-01

    Three hypotheses to explain the amino acid composition of proteins are inconsistent (about 10 to the minus 9th) with the experimental data for beta-galactosidase from Escherichia coli. The exceptional length of this protein, 1021 residues, permits rigorous tests of these hypotheses without complication from statistical artifacts. Either this protein is not at compositional equilibrium, which is unlikely from knowledge about other proteins, or the evolution of this protein and its coding gene have not been selectively neutral. However, the composition of approximately 60% of the molecule is consistent with either a selectively neutral or nonneutral evolutionary process.

  8. Identification of an Allosteric Small Molecule Inhibitor Selective for Inducible Form of Heat Shock Protein 70

    PubMed Central

    Howe, Matthew K.; Bodoor, Khaldon; Carlson, David A.; Hughes, Philip F.; Alwarawrah, Yazan; Loiselle, David R.; Jaeger, Alex M.; Darr, David B.; Jordan, Jamie L.; Hunter, Lucas M.; Molzberger, Eileen T.; Gobillot, Theodore A.; Thiele, Dennis J.; Brodsky, Jeffrey L.; Spector, Neil L.; Haystead, Timothy A. J.

    2014-01-01

    Summary Inducible Hsp70 (Hsp70i) is overexpressed in a wide spectrum of human tumors and its expression correlates with metastasis, poor outcomes, and resistance to chemotherapy in patients. Identification of small molecule inhibitors selective for Hsp70i could provide new therapeutic tools for cancer treatment. In this work, we used fluorescence-linked enzyme chemoproteomic strategy (FLECS) to identify HS-72, an allosteric inhibitor selective for Hsp70i. HS-72 displays the hallmarks of Hsp70 inhibition in cells, promoting substrate protein degradation and growth inhibition. Importantly, HS-72 is selective for Hsp70i over the closely related constitutively active Hsc70. Studies with purified protein show HS-72 acts as an allosteric inhibitor, reducing ATP affinity. In vivo HS-72 is well-tolerated, showing bioavailability and efficacy, inhibiting tumor growth and promoting survival in a HER2+ model of breast cancer. The HS-72 scaffold is amenable to resynthesis and iteration, suggesting an ideal starting point for a new generation of anticancer therapeutics targeting Hsp70i. PMID:25500222

  9. Protein scaffolds for selective enrichment of metal ions

    DOEpatents

    He, Chuan; Zhou, Lu; Bosscher, Michael

    2016-02-09

    Polypeptides comprising high affinity for the uranyl ion are provided. Methods for binding uranyl using such proteins are likewise provided and can be used, for example, in methods for uranium purification or removal.

  10. Fold assessment for comparative protein structure modeling.

    PubMed

    Melo, Francisco; Sali, Andrej

    2007-11-01

    Accurate and automated assessment of both geometrical errors and incompleteness of comparative protein structure models is necessary for an adequate use of the models. Here, we describe a composite score for discriminating between models with the correct and incorrect fold. To find an accurate composite score, we designed and applied a genetic algorithm method that searched for a most informative subset of 21 input model features as well as their optimized nonlinear transformation into the composite score. The 21 input features included various statistical potential scores, stereochemistry quality descriptors, sequence alignment scores, geometrical descriptors, and measures of protein packing. The optimized composite score was found to depend on (1) a statistical potential z-score for residue accessibilities and distances, (2) model compactness, and (3) percentage sequence identity of the alignment used to build the model. The accuracy of the composite score was compared with the accuracy of assessment by single and combined features as well as by other commonly used assessment methods. The testing set was representative of models produced by automated comparative modeling on a genomic scale. The composite score performed better than any other tested score in terms of the maximum correct classification rate (i.e., 3.3% false positives and 2.5% false negatives) as well as the sensitivity and specificity across the whole range of thresholds. The composite score was implemented in our program MODELLER-8 and was used to assess models in the MODBASE database that contains comparative models for domains in approximately 1.3 million protein sequences.

  11. Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach.

    PubMed

    Stern, Adi; Doron-Faigenboim, Adi; Erez, Elana; Martz, Eric; Bacharach, Eran; Pupko, Tal

    2007-07-01

    Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K(s)) and non-synonymous (K(a)) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton.bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K(a) and K(s) (omega) at each site of the protein. This ratio is graphically displayed on each site using a color-coding scheme, indicating either positive selection, purifying selection or lack of selection. Selecton implements an assembly of different evolutionary models, which allow for statistical testing of the hypothesis that a protein has undergone positive selection. Specifically, the recently developed mechanistic-empirical model is introduced, which takes into account the physicochemical properties of amino acids. Advanced options were introduced to allow maximal fine tuning of the server to the user's specific needs, including calculation of statistical support of the omega values, an advanced graphic display of the protein's 3-dimensional structure, use of different genetic codes and inputting of a pre-built phylogenetic tree. Selecton version 2.2 is an effective, user-friendly and freely available web server which implements up-to-date methods for computing site-specific selection forces, and the visualization of these forces on the protein's sequence and structure.

  12. The Protein Model Portal—a comprehensive resource for protein structure and model information

    PubMed Central

    Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

    2013-01-01

    The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org PMID:23624946

  13. Protein Synthesis with Ribosomes Selected for the Incorporation of β-Amino Acids.

    PubMed

    Maini, Rumit; Chowdhury, Sandipan Roy; Dedkova, Larisa M; Roy, Basab; Daskalova, Sasha M; Paul, Rakesh; Chen, Shengxi; Hecht, Sidney M

    2015-06-16

    In an earlier study, β³-puromycin was used for the selection of modified ribosomes, which were utilized for the incorporation of five different β-amino acids into Escherichia coli dihydrofolate reductase (DHFR). The selected ribosomes were able to incorporate structurally disparate β-amino acids into DHFR, in spite of the use of a single puromycin for the selection of the individual clones. In this study, we examine the extent to which the structure of the β³-puromycin employed for ribosome selection influences the regio- and stereochemical preferences of the modified ribosomes during protein synthesis; the mechanistic probe was a single suppressor tRNA(CUA) activated with each of four methyl-β-alanine isomers (1-4). The modified ribosomes were found to incorporate each of the four isomeric methyl-β-alanines into DHFR but exhibited a preference for incorporation of 3(S)-methyl-β-alanine (β-mAla; 4), i.e., the isomer having the same regio- and stereochemistry as the O-methylated β-tyrosine moiety of β³-puromycin. Also conducted were a selection of clones that are responsive to β²-puromycin and a demonstration of reversal of the regio- and stereochemical preferences of these clones during protein synthesis. These results were incorporated into a structural model of the modified regions of 23S rRNA, which included in silico prediction of a H-bonding network. Finally, it was demonstrated that incorporation of 3(S)-methyl-β-alanine (β-mAla; 4) into a short α-helical region of the nucleic acid binding domain of hnRNP LL significantly stabilized the helix without affecting its DNA binding properties.

  14. Phytomonas: A non-pathogenic trypanosomatid model for functional expression of proteins.

    PubMed

    Miranda, Mariana R; Sayé, Melisa; Reigada, Chantal; Carrillo, Carolina; Pereira, Claudio A

    2015-10-01

    Phytomonas are protozoan parasites from the Trypanosomatidae family which infect a wide variety of plants. Herein, Phytomonas Jma was tested as a model for functional expression of heterologous proteins. Green fluorescent protein expression was evaluated in Phytomonas and compared with Trypanosoma cruzi, the etiological agent of Chagas' disease. Phytomonas was able to express GFP at levels similar to T. cruzi although the transgenic selection time was higher. It was possible to establish an efficient transfection and selection protocol for protein expression. These results demonstrate that Phytomonas can be a good model for functional expression of proteins from other trypanosomatids, presenting the advantage of being completely safe for humans. PMID:26142019

  15. Phytomonas: A non-pathogenic trypanosomatid model for functional expression of proteins.

    PubMed

    Miranda, Mariana R; Sayé, Melisa; Reigada, Chantal; Carrillo, Carolina; Pereira, Claudio A

    2015-10-01

    Phytomonas are protozoan parasites from the Trypanosomatidae family which infect a wide variety of plants. Herein, Phytomonas Jma was tested as a model for functional expression of heterologous proteins. Green fluorescent protein expression was evaluated in Phytomonas and compared with Trypanosoma cruzi, the etiological agent of Chagas' disease. Phytomonas was able to express GFP at levels similar to T. cruzi although the transgenic selection time was higher. It was possible to establish an efficient transfection and selection protocol for protein expression. These results demonstrate that Phytomonas can be a good model for functional expression of proteins from other trypanosomatids, presenting the advantage of being completely safe for humans.

  16. Kinetic Analysis of Protein Folding Lattice Models

    NASA Astrophysics Data System (ADS)

    Chen, Hu; Zhou, Xin; Liaw, Chih Young; Koh, Chan Ghee

    Based on two-dimensional square lattice models of proteins, the relation between folding time and temperature is studied by Monte Carlo simulation. The results can be represented by a kinetic model with three states — random coil, molten globule, and native state. The folding process is composed of nonspecific collapse and final searching for the native state. At high temperature, it is easy to escape from local traps in the folding process. With decreasing temperature, because of the trapping in local traps, the final searching speed decreases. Then the folding shows chevron rollover. Through the analysis of the fitted parameters of the kinetic model, it is found that the main difference between the energy landscapes of the HP model and the Go model is that the number of local minima of the Go model is less than that of the HP model.

  17. Differential Evolutionary Selection and Natural Evolvability Observed in ALT Proteins of Human Filarial Parasites.

    PubMed

    Devoe, Neil C; Corbett, Ian J; Barker, Linsey; Chang, Robert; Gudis, Polyxeni; Mullen, Nathan; Perez, Kailey; Raposo, Hugo; Scholz, John; May, Meghan

    2016-01-01

    The abundant larval transcript (ALT-2) protein is present in all members of the Filarioidea, and has been reported as a potential candidate antigen for a subunit vaccine against lymphatic filariasis. To assess the potential for vaccine escape or heterologous protection, we examined the evolutionary selection acting on ALT-2. The ratios of nonsynonymous (K(a)) to synonymous (K(s)) mutation frequencies (ω) were calculated for the alt-2 genes of the lymphatic filariasis agents Brugia malayi and Wuchereria bancrofti and the agents of river blindness and African eyeworm disease Onchocerca volvulus and Loa loa. Two distinct Bayesian models of sequence evolution showed that ALT-2 of W. bancrofti and L. loa were under significant (P<0.05; P < 0.001) diversifying selection, while ALT-2 of B. malayi and O. volvulus were under neutral to stabilizing selection. Diversifying selection as measured by ω values was notably strongest on the region of ALT-2 encoding the signal peptide of L. loa and was elevated in the variable acidic domain of L. loa and W. bancrofti. Phylogenetic analysis indicated that the ALT-2 consensus sequences formed three clades: the first consisting of B. malayi, the second consisting of W. bancrofti, and the third containing both O. volvulus and L. loa. ALT-2 selection was therefore not predictable by phylogeny or pathology, as the two species parasitizing the eye were selected differently, as were the two species parasitizing the lymphatic system. The most immunogenic regions of L. loa and W. bancrofti ALT-2 sequence as modeled by antigenicity prediction analysis did not correspond with elevated levels of diversifying selection, and were not selected differently than predicted antigenic epitopes in B. malayi and O. volvulus. Measurements of ALT-2 evolvability made by χ2 analysis between alleles that were stable (O. volvulus and B. malayi) and those that were under diversifying selection (W. bancrofti and L. loa) indicated significant (P<0

  18. Differential Evolutionary Selection and Natural Evolvability Observed in ALT Proteins of Human Filarial Parasites.

    PubMed

    Devoe, Neil C; Corbett, Ian J; Barker, Linsey; Chang, Robert; Gudis, Polyxeni; Mullen, Nathan; Perez, Kailey; Raposo, Hugo; Scholz, John; May, Meghan

    2016-01-01

    The abundant larval transcript (ALT-2) protein is present in all members of the Filarioidea, and has been reported as a potential candidate antigen for a subunit vaccine against lymphatic filariasis. To assess the potential for vaccine escape or heterologous protection, we examined the evolutionary selection acting on ALT-2. The ratios of nonsynonymous (K(a)) to synonymous (K(s)) mutation frequencies (ω) were calculated for the alt-2 genes of the lymphatic filariasis agents Brugia malayi and Wuchereria bancrofti and the agents of river blindness and African eyeworm disease Onchocerca volvulus and Loa loa. Two distinct Bayesian models of sequence evolution showed that ALT-2 of W. bancrofti and L. loa were under significant (P<0.05; P < 0.001) diversifying selection, while ALT-2 of B. malayi and O. volvulus were under neutral to stabilizing selection. Diversifying selection as measured by ω values was notably strongest on the region of ALT-2 encoding the signal peptide of L. loa and was elevated in the variable acidic domain of L. loa and W. bancrofti. Phylogenetic analysis indicated that the ALT-2 consensus sequences formed three clades: the first consisting of B. malayi, the second consisting of W. bancrofti, and the third containing both O. volvulus and L. loa. ALT-2 selection was therefore not predictable by phylogeny or pathology, as the two species parasitizing the eye were selected differently, as were the two species parasitizing the lymphatic system. The most immunogenic regions of L. loa and W. bancrofti ALT-2 sequence as modeled by antigenicity prediction analysis did not correspond with elevated levels of diversifying selection, and were not selected differently than predicted antigenic epitopes in B. malayi and O. volvulus. Measurements of ALT-2 evolvability made by χ2 analysis between alleles that were stable (O. volvulus and B. malayi) and those that were under diversifying selection (W. bancrofti and L. loa) indicated significant (P<0

  19. Differential Evolutionary Selection and Natural Evolvability Observed in ALT Proteins of Human Filarial Parasites

    PubMed Central

    Devoe, Neil C.; Corbett, Ian J.; Barker, Linsey; Chang, Robert; Gudis, Polyxeni; Mullen, Nathan; Perez, Kailey; Raposo, Hugo; Scholz, John; May, Meghan

    2016-01-01

    The abundant larval transcript (ALT-2) protein is present in all members of the Filarioidea, and has been reported as a potential candidate antigen for a subunit vaccine against lymphatic filariasis. To assess the potential for vaccine escape or heterologous protection, we examined the evolutionary selection acting on ALT-2. The ratios of nonsynonymous (K(a)) to synonymous (K(s)) mutation frequencies (ω) were calculated for the alt-2 genes of the lymphatic filariasis agents Brugia malayi and Wuchereria bancrofti and the agents of river blindness and African eyeworm disease Onchocerca volvulus and Loa loa. Two distinct Bayesian models of sequence evolution showed that ALT-2 of W. bancrofti and L. loa were under significant (P<0.05; P < 0.001) diversifying selection, while ALT-2 of B. malayi and O. volvulus were under neutral to stabilizing selection. Diversifying selection as measured by ω values was notably strongest on the region of ALT-2 encoding the signal peptide of L. loa and was elevated in the variable acidic domain of L. loa and W. bancrofti. Phylogenetic analysis indicated that the ALT-2 consensus sequences formed three clades: the first consisting of B. malayi, the second consisting of W. bancrofti, and the third containing both O. volvulus and L. loa. ALT-2 selection was therefore not predictable by phylogeny or pathology, as the two species parasitizing the eye were selected differently, as were the two species parasitizing the lymphatic system. The most immunogenic regions of L. loa and W. bancrofti ALT-2 sequence as modeled by antigenicity prediction analysis did not correspond with elevated levels of diversifying selection, and were not selected differently than predicted antigenic epitopes in B. malayi and O. volvulus. Measurements of ALT-2 evolvability made by χ2 analysis between alleles that were stable (O. volvulus and B. malayi) and those that were under diversifying selection (W. bancrofti and L. loa) indicated significant (P<0

  20. dockYard--a repository to assist modeling of protein-protein docking.

    PubMed

    Mitra, Pralay; Pal, Debnath

    2011-03-01

    In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard ( http://pallab.serc.iisc.ernet.in/dockYard ), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with ≥ 90% or ≥ 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

  1. The first evidence of positive selection in peptidoglycan recognition protein (PGRP) genes of Crassostrea gigas.

    PubMed

    Zhang, Yang; Yu, Ziniu

    2013-05-01

    The oyster Crassostrea gigas is thought to have developed effective immunity to potentially harmful pathogens while under continuous exposure to marine microorganisms; however, the evolutionary mechanisms by which such immunity developed has not been understood. To understand the evolution of immunity, we characterized the family of peptidoglycan recognition proteins in the oyster (CgPGRPs). These proteins are crucial pattern recognition receptors for peptidoglycans (PGNs) and thereby, for activating the innate immune response of host. Herein, we identify seven new CgPGRP genes. Phylogenetic analysis of the seven new and five previously reported CgPRGP genes reveals that the CgPRGP gene family can be clustered into two groups, CgPRGPS and CgPRGPL. Moreover, the CgPRGPS group can be further divided into five subgroups. A codon-substitution model and three likelihood ratio tests (LRTs) suggest that seven sites in the CgPGRP family of genes have been subjected to strong positive selection (ω = 3.035-4.143), Three dimensional modeling revealed that these sites are found primarily at the periphery of coils and α-helices rather than in β-strands, perhaps allowing PGRP to adapt to, and recognize, variability of PGN structure. In conclusion, our studies provide the first evidence of positive Darwinian selection in the CgPGRP family, contributing to a better understanding of the adaptive mechanism of host-pathogens interaction in marine mollusks.

  2. Membrane Compartmentalization Reducing the Mobility of Lipids and Proteins within a Model Plasma Membrane.

    PubMed

    Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P

    2016-09-01

    The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.

  3. Hydration dynamics near a model protein surface

    SciTech Connect

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-09-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces.

  4. A versatile selection system for folding competent proteins using genetic complementation in a eukaryotic host

    PubMed Central

    Lyngsø, Christina; Kjaerulff, Søren; Müller, Sven; Bratt, Tomas; Mortensen, Uffe H; Dal Degan, Florence

    2010-01-01

    Recombinant expression of native or modified eukaryotic proteins is pivotal for structural and functional studies and for industrial and pharmaceutical production of proteins. However, it is often impeded by the lack of proper folding. Here, we present a stringent and broadly applicable eukaryotic in vivo selection system for folded proteins. It is based on genetic complementation of the Schizosaccharomyces pombe growth marker gene invertase fused C-terminally to a protein library. The fusion proteins are directed to the secretion system, utilizing the ability of the eukaryotic protein quality-control systems to retain misfolded proteins in the ER and redirect them for cytosolic degradation, thereby only allowing folded proteins to reach the cell surface. Accordingly, the folding potential of the tested protein determines the ability of autotrophic colony growth. This system was successfully demonstrated using a complex insertion mutant library of TNF-α, from which different folding competent mutant proteins were uncovered. PMID:20082307

  5. Novel proteins associated with human dilated cardiomyopathy: selective reduction in α(1A)-adrenergic receptors and increased desensitization proteins.

    PubMed

    Shi, Ting; Moravec, Christine S; Perez, Dianne M

    2013-04-01

    Abstract Therapeutics to treat human heart failure (HF) and the identification of proteins associated with HF are still limited. We analyzed α(1)-adrenergic receptor (AR) subtypes in human HF and performed proteomic analysis on more uniform samples to identify novel proteins associated with human HF. Six failing hearts with end-stage dilated cardiomyopathy (DCM) and four non-failing heart controls were subjected to proteomic analysis. Out of 48 identified proteins, 26 proteins were redundant between samples. Ten of these 26 proteins were previously reported to be associated with HF. Of the newly identified proteins, we found several muscle proteins and mitochondrial/electron transport proteins, while novel were functionally similar to previous reports. However, we also found novel proteins involved in functional classes such as β-oxidation and G-protein coupled receptor signaling and desensitization not previously associated with HF. We also performed radioligand-binding studies on the heart samples and not only confirmed a large loss of β(1)-ARs in end-stage DCM, but also found a selective decrease in the α(1A)-AR subtype not previously reported. We have identified new proteins and functional categories associated with end-stage DCM. We also report that similar to the previously characterized loss of β(1)-AR in HF, there is also a concomitant loss of α(1A)-ARs, which are considered cardioprotective proteins.

  6. Selective dansylation of M protein within intact influenza virions

    SciTech Connect

    Robertson, B.H.; Bennett, J.C.; Compans, R.W.

    1982-12-01

    Exposure of purified influenza virions to (/sup 14/C)dansyl chloride resulted in the covalent attachment of the dansyl chromophore to the virion. Gel electrophoresis revealed that the dansyl chromophore was specifically coupled to the internal membrane (M) protein. Purification of the M protein by gel filtration followed by cyanogen bromide cleavage and peptide fractionation revealed that four of six peptide peaks contained dansyl label. Acid hydrolysis of the separated peptide peaks followed by thin-layer chromatography revealed that dansyl label was coupled to lysine residues present in these peptides. The results of these investigations have demonstrated that the M protein molecule is the major viral polypeptide labeled when intact virions are exposed to dansyl chloride.

  7. Domains in folding of model proteins.

    PubMed Central

    Abkevich, V. I.; Gutin, A. M.; Shakhnovich, E. I.

    1995-01-01

    By means of Monte Carlo simulation, we investigated the equilibrium between folded and unfolded states of lattice model proteins. The amino acid sequences were designed to have pronounced energy minimum target conformations of different length and shape. For short fully compact (36-mer) proteins, the all-or-none transition from the unfolded state to the native state was observed. This was not always the case for longer proteins. Among 12 designed sequences with the native structure of a fully compact 48-mer, a simple all-or-none transition was observed in only three cases. For the other nine sequences, three states of behavior-the native, denatured, and intermediate states-were found. The contiguous part of the native structure (domain) was conserved in the intermediate state, whereas the remaining part was completely unfolded and structureless. These parts melted separately from each other. PMID:7549881

  8. Model-building codes for membrane proteins.

    SciTech Connect

    Shirley, David Noyes; Hunt, Thomas W.; Brown, W. Michael; Schoeniger, Joseph S.; Slepoy, Alexander; Sale, Kenneth L.; Young, Malin M.; Faulon, Jean-Loup Michel; Gray, Genetha Anne

    2005-01-01

    We have developed a novel approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only a sparse set of distance constraints, such as those derived from MS3-D, dipolar-EPR and FRET experiments. Algorithms have been written for searching the conformational space of membrane protein folds matching the set of distance constraints, which provides initial structures for local conformational searches. Local conformation search is achieved by optimizing these candidates against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. This results in refined helical bundles to which the interhelical loops and amino acid side-chains are added. Using a set of only 27 distance constraints extracted from the literature, our methods successfully recover the structure of dark-adapted rhodopsin to within 3.2 {angstrom} of the crystal structure.

  9. Genetic selection system for improving recombinant membrane protein expression in E. coli

    PubMed Central

    Massey-Gendel, Elizabeth; Zhao, Anni; Boulting, Gabriella; Kim, Hye-Yeon; Balamotis, Michael A; Seligman, Len M; Nakamoto, Robert K; Bowie, James U

    2009-01-01

    A major barrier to the physical characterization and structure determination of membrane proteins is low yield in recombinant expression. To address this problem, we have designed a selection strategy to isolate mutant strains of Escherichia coli that improve the expression of a targeted membrane protein. In this method, the coding sequence of the membrane protein of interest is fused to a C-terminal selectable marker, so that the production of the selectable marker and survival on selective media is linked to expression of the targeted membrane protein. Thus, mutant strains with improved expression properties can be directly selected. We also introduce a rapid method for curing isolated strains of the plasmids used during the selection process, in which the plasmids are removed by in vivo digestion with the homing endonuclease I-CreI. We tested this selection system on a rhomboid family protein from Mycobacterium tuberculosis (Rv1337) and were able to isolate mutants, which we call EXP strains, with up to 75-fold increased expression. The EXP strains also improve the expression of other membrane proteins that were not the target of selection, in one case roughly 90-fold. PMID:19165721

  10. Methionine Ligand Interaction in a Blue Copper Protein Characterized by Site-Selective Infrared Spectroscopy.

    PubMed

    Le Sueur, Amanda L; Schaugaard, Richard N; Baik, Mu-Hyun; Thielges, Megan C

    2016-06-01

    The reactivity of metal sites in proteins is tuned by protein-based ligands. For example, in blue copper proteins such as plastocyanin (Pc), the structure imparts a highly elongated bond between the Cu and a methionine (Met) axial ligand to modulate its redox properties. Despite extensive study, a complete understanding of the contribution of the protein to redox activity is challenged by experimentally accessing both redox states of metalloproteins. Using infrared (IR) spectroscopy in combination with site-selective labeling with carbon-deuterium (C-D) vibrational probes, we characterized the localized changes at the Cu ligand Met97 in the oxidized and reduced states, as well as the Zn(II) or Co(II)-substituted, the pH-induced low-coordinate, the apoprotein, and the unfolded states. The IR absorptions of (d3-methyl)Met97 are highly sensitive to interaction of the sulfur-based orbitals with the metal center and are demonstrated to be useful reporters of its modulation in the different states. Unrestricted Kohn-Sham density functional theory calculations performed on a model of the Cu site of Pc confirm the observed dependence. IR spectroscopy was then applied to characterize the impact of binding to the physiological redox partner cytochrome (cyt) f. The spectral changes suggest a slightly stronger Cu-S(Met97) interaction in the complex with cyt f that has potential to modulate the electron transfer properties. Besides providing direct, molecular-level comparison of the oxidized and reduced states of Pc from the perspective of the axial Met ligand and evidence for perturbation of the Cu site properties by redox partner binding, this study demonstrates the localized spatial information afforded by IR spectroscopy of selectively incorporated C-D probes. PMID:27164303

  11. Selective Immobilization of Proteins onto Solid Supports Through Split-Intein Mediated Protein Trans-Splicing

    SciTech Connect

    Kwon, Y; Coleman, M A; Camarero, J A

    2005-08-23

    Protein microarrays have emerged as important tools for screening protein-protein interactions and hold great potential for various applications including proteomics research, drug discovery, and diagnostics. This work describes a novel method for the traceless immobilization of proteins to a solid support through split-intein mediated protein trans-splicing. This method has been successfully used for the immobilization of biologically active proteins from very diluted samples ({approx}1{micro}M) and it does not require the purification of the protein to be attached. This makes possible the direct immobilization of proteins from complex mixtures such as cellular lysates and it can also be easily interfaced with cell-free expression systems for high-throughput production of protein microarrays.

  12. Molecular modeling of protein-glycosaminoglycan interactions.

    PubMed

    Cardin, A D; Weintraub, H J

    1989-01-01

    Forty-nine regions in 21 proteins were identified as potential heparin-binding sites based on the sequence organizations of their basic and nonbasic residues. Twelve known heparin-binding sequences in vitronectin, apolipoproteins E and B-100, and platelet factor 4 were used to formulate two search strings for identifying potential heparin-binding regions in other proteins. Consensus sequences for glycosaminoglycan recognition were determined as [-X-B-B-X-B-X-] and [-X-B-B-B-X-X-B-X-] where B is the probability of a basic residue and X is a hydropathic residue. Predictions were then made as to the heparin-binding domains in endothelial cell growth factor, purpurin, and antithrombin-III. Many of the natural sequences conforming to these consensus motifs show prominent amphipathic periodicities having both alpha-helical and beta-strand conformations as determined by predictive algorithms and circular dichroism studies. The heparin-binding domain of vitronectin was modeled and formed a hydrophilic pocket that wrapped around and folded over a heparin octasaccharide, yielding a complementary structure. We suggest that these consensus sequence elements form potential nucleation sites for the recognition of polyanions in proteins and may provide a useful guide in identifying heparin-binding regions in other proteins. The possible relevance of protein-glycosaminoglycans interactions in atherosclerosis is discussed. PMID:2463827

  13. Increasing selection response by Bayesian modeling of heterogeneous environmental variances

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

  14. Gγ recruitment systems specifically select PPI and affinity-enhanced candidate proteins that interact with membrane protein targets.

    PubMed

    Kaishima, Misato; Ishii, Jun; Fukuda, Nobuo; Kondo, Akihiko

    2015-11-19

    Protein-protein interactions (PPIs) are crucial for the vast majority of biological processes. We previously constructed a Gγ recruitment system to screen PPI candidate proteins and desirable affinity-altered (affinity-enhanced and affinity-attenuated) protein variants. The methods utilized a target protein fused to a mutated G-protein γ subunit (Gγcyto) lacking the ability to localize to the inner leaflet of the plasma membrane. However, the previous systems were adapted to use only soluble cytosolic proteins as targets. Recently, membrane proteins have been found to form the principal nodes of signaling involved in diseases and have attracted a great deal of interest as primary drug targets. Here, we describe new protocols for the Gγ recruitment systems that are specifically designed to use membrane proteins as targets to overcome previous limitations. These systems represent an attractive approach to exploring novel interacting candidates and affinity-altered protein variants and their interactions with proteins on the inner side of the plasma membrane, with high specificity and selectivity.

  15. Gγ recruitment systems specifically select PPI and affinity-enhanced candidate proteins that interact with membrane protein targets

    PubMed Central

    Kaishima, Misato; Ishii, Jun; Fukuda, Nobuo; Kondo, Akihiko

    2015-01-01

    Protein-protein interactions (PPIs) are crucial for the vast majority of biological processes. We previously constructed a Gγ recruitment system to screen PPI candidate proteins and desirable affinity-altered (affinity-enhanced and affinity-attenuated) protein variants. The methods utilized a target protein fused to a mutated G-protein γ subunit (Gγcyto) lacking the ability to localize to the inner leaflet of the plasma membrane. However, the previous systems were adapted to use only soluble cytosolic proteins as targets. Recently, membrane proteins have been found to form the principal nodes of signaling involved in diseases and have attracted a great deal of interest as primary drug targets. Here, we describe new protocols for the Gγ recruitment systems that are specifically designed to use membrane proteins as targets to overcome previous limitations. These systems represent an attractive approach to exploring novel interacting candidates and affinity-altered protein variants and their interactions with proteins on the inner side of the plasma membrane, with high specificity and selectivity. PMID:26581329

  16. The Use of Experimental Structures to Model Protein Dynamics

    PubMed Central

    Katebi, Ataur R.; Sankar, Kannan; Jia, Kejue; Jernigan, Robert L.

    2014-01-01

    Summary The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high – for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, this chapter focuses on two methods – Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein. We have described, step by step, how to select a set of protein structures, how to extract the needed information from the PDB files for PCA, how to extract the dynamics information using PCA, how to calculate ENM modes, how to measure the congruency between the dynamics computed from the principal components (PCs) and the ENM modes, and how to compute entropies using the PCs. We provide the computer programs or references to software tools to

  17. The use of experimental structures to model protein dynamics.

    PubMed

    Katebi, Ataur R; Sankar, Kannan; Jia, Kejue; Jernigan, Robert L

    2015-01-01

    The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high-for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, this chapter focuses on two methods-Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein. We have described, step by step, how to select a set of protein structures, how to extract the needed information from the PDB files for PCA, how to extract the dynamics information using PCA, how to calculate ENM modes, how to measure the congruency between the dynamics computed from the principal components (PCs) and the ENM modes, and how to compute entropies using the PCs. We provide the computer programs or references to software tools to accomplish each step

  18. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    USGS Publications Warehouse

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

  19. Changes in Binding of [(123)I]CLINDE, a High-Affinity Translocator Protein 18 kDa (TSPO) Selective Radioligand in a Rat Model of Traumatic Brain Injury.

    PubMed

    Donat, Cornelius K; Gaber, Khaled; Meixensberger, Jürgen; Brust, Peter; Pinborg, Lars H; Hansen, Henrik H; Mikkelsen, Jens D

    2016-06-01

    After traumatic brain injury (TBI), secondary injuries develop, including neuroinflammatory processes that contribute to long-lasting impairments. These secondary injuries represent potential targets for treatment and diagnostics. The translocator protein 18 kDa (TSPO) is expressed in activated microglia cells and upregulated in response to brain injury and therefore a potential biomarker of the neuroinflammatory processes. Second-generation radioligands of TSPO, such as [(123)I]CLINDE, have a higher signal-to-noise ratio as the prototype ligand PK11195. [(123)I]CLINDE has been employed in human studies using single-photon emission computed tomography to image the neuroinflammatory response after stroke. In this study, we used the same tracer in a rat model of TBI to determine changes in TSPO expression. Adult Sprague-Dawley rats were subjected to moderate controlled cortical impact injury and sacrificed at 6, 24, 72 h and 28 days post surgery. TSPO expression was assessed in brain sections employing [(123)I]CLINDE in vitro autoradiography. From 24 h to 28 days post surgery, injured animals exhibited a marked and time-dependent increase in [(123)I]CLINDE binding in the ipsilateral motor, somatosensory and parietal cortex, as well as in the hippocampus and thalamus. Interestingly, binding was also significantly elevated in the contralateral M1 motor cortex following TBI. Craniotomy without TBI caused a less marked increase in [(123)I]CLINDE binding, restricted to the ipsilateral hemisphere. Radioligand binding was consistent with an increase in TSPO mRNA expression and CD11b immunoreactivity at the contusion site. This study demonstrates the applicability of [(123)I]CLINDE for detailed regional and quantitative assessment of glial activity in experimental models of TBI.

  20. Hypothetical proteins present during recovery phase of radiation resistant bacterium Deinococcus radiodurans are under purifying selection.

    PubMed

    Das, Anubrata D; Misra, Hari S

    2013-08-01

    Deinococcus radiodurans has an unusual capacity to recover from intense doses of ionizing radiation. The DNA repair proteins of this organism play an important role in repairing the heavily damaged DNA by employing a novel mechanism of DNA double-strand break repair. An earlier report stated that genes of many of these repair proteins are under positive selection implying that these genes have a tendency to mutate, which in turn provides selective advantage to this bacterium. Several "hypothetical proteins" are also present during the recovery phase and some of them have also been shown for their roles in radiation resistance. Therefore, we tested the selection pressure on the genes encoding these poorly characterized proteins. Our results show that a number of "hypothetical proteins" present during the repair phase have structural adaptations compared to their orthologs and the genes encoding them as well as those for the DNA repair proteins present during this phase are under purifying selection. Evidence of purifying selection in these hypothetical proteins suggests that certain novel characteristics among these proteins are conserved and seem to be under functional constraints to perform important functions during recovery process after gamma radiation damage.

  1. Symmetry-adapted digital modeling I. Axial symmetric proteins.

    PubMed

    Janner, A

    2016-05-01

    Considered are axial symmetric proteins exemplified by the octameric mitochondrial creatine kinase, the Pyr RNA-binding attenuation protein, the D-aminopeptidase and the cyclophilin A-cyclosporin complex, with tetragonal (422), trigonal (32), pentagonal (52) and pentagonal (52) point-group symmetry, respectively. One starts from the protein enclosing form, which is characterized by vertices at points of a lattice (the form lattice) whose dimension depends on the point group. This allows the indexing of Cα's at extreme radial positions. The indexing is extended to additional residues on the basis of a finer lattice, the digital modeling lattice Λ, which includes the form lattice as a sublattice. This leads to a coarse-grained description of the protein. In the crystallographic point-group case, the planar indices are obtained from a projection of atomic positions along the rotation axis, taken as the z axis. The planar indices of a Cα are then those of the nearest projected lattice point. In the non-crystallographic case, low indices are an additional requirement. The coarse-grained bead follows from the condition imposed on the residues selected to have a z coordinate within a band of value δ above and below the height of lattice points. The choice of δ permits a variation of the coarse-grained bead model. For example, the value δ = 0.5 leads to a fine-grained indexing of the full set of residues, whereas with δ = 0.25 one gets a coarse-grained model which includes only about half of these residues. Within this procedure, the indexing of the Cα only depends on the choice of the digital modeling lattice and not on the value of δ. The characteristics which distinguish the present approach from other coarse-grained models of proteins on lattices are summarized at the end. PMID:27126107

  2. Modelling Transcapillary Transport of Fluid and Proteins in Hemodialysis Patients

    PubMed Central

    Pietribiasi, Mauro; Waniewski, Jacek; Załuska, Alicja; Załuska, Wojciech; Lindholm, Bengt

    2016-01-01

    Background The kinetics of protein transport to and from the vascular compartment play a major role in the determination of fluid balance and plasma refilling during hemodialysis (HD) sessions. In this study we propose a whole-body mathematical model describing water and protein shifts across the capillary membrane during HD and compare its output to clinical data while evaluating the impact of choosing specific values for selected parameters. Methods The model follows a two-compartment structure (vascular and interstitial space) and is based on balance equations of protein mass and water volume in each compartment. The capillary membrane was described according to the three-pore theory. Two transport parameters, the fractional contribution of large pores (αLP) and the total hydraulic conductivity (LpS) of the capillary membrane, were estimated from patient data. Changes in the intensity and direction of individual fluid and solute flows through each part of the transport system were analyzed in relation to the choice of different values of small pores radius and fractional conductivity, lymphatic sensitivity to hydraulic pressure, and steady-state interstitial-to-plasma protein concentration ratio. Results The estimated values of LpS and αLP were respectively 10.0 ± 8.4 mL/min/mmHg (mean ± standard deviation) and 0.062 ± 0.041. The model was able to predict with good accuracy the profiles of plasma volume and serum total protein concentration in most of the patients (average root-mean-square deviation < 2% of the measured value). Conclusions The applied model provides a mechanistic interpretation of fluid transport processes induced by ultrafiltration during HD, using a minimum of tuned parameters and assumptions. The simulated values of individual flows through each kind of pore and lymphatic absorption rate yielded by the model may suggest answers to unsolved questions on the relative impact of these not-measurable quantities on total vascular refilling and

  3. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 3 2012-10-01 2012-10-01 false Selection of risk model. 425.600 Section 425.600... Selection of risk model. (a) For its initial agreement period, an ACO may elect to operate under one of the following tracks: (1) Track 1. Under Track 1, the ACO operates under the one-sided model (as described...

  4. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 3 2013-10-01 2013-10-01 false Selection of risk model. 425.600 Section 425.600... Selection of risk model. (a) For its initial agreement period, an ACO may elect to operate under one of the following tracks: (1) Track 1. Under Track 1, the ACO operates under the one-sided model (as described...

  5. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 3 2014-10-01 2014-10-01 false Selection of risk model. 425.600 Section 425.600... Selection of risk model. (a) For its initial agreement period, an ACO may elect to operate under one of the following tracks: (1) Track 1. Under Track 1, the ACO operates under the one-sided model (as described...

  6. Rhes, a striatal-selective protein implicated in Huntington disease, binds beclin-1 and activates autophagy.

    PubMed

    Mealer, Robert G; Murray, Alexandra J; Shahani, Neelam; Subramaniam, Srinivasa; Snyder, Solomon H

    2014-02-01

    The protein mutated in Huntington disease (HD), mutant huntingtin (mHtt), is expressed throughout the brain and body. However, the pathology of HD is characterized by early and dramatic destruction selectively of the striatum. We previously reported that the striatal-specific protein Rhes binds mHtt and enhances its cytotoxicity. Moreover, Rhes-deleted mice are dramatically protected from neurodegeneration and motor dysfunction in mouse models of HD. We now report a function of Rhes in autophagy, a lysosomal degradation pathway implicated in aging and HD neurodegeneration. In PC12 cells, deletion of endogenous Rhes decreases autophagy, whereas Rhes overexpression activates autophagy. These effects are independent of mTOR and opposite in the direction predicted by the known activation of mTOR by Rhes. Rhes robustly binds the autophagy regulator Beclin-1, decreasing its inhibitory interaction with Bcl-2 independent of JNK-1 signaling. Finally, co-expression of mHtt blocks Rhes-induced autophagy activation. Thus, the isolated pathology and delayed onset of HD may reflect the striatal-selective expression and changes in autophagic activity of Rhes.

  7. Selective sorting and destruction of mitochondrial membrane proteins in aged yeast

    PubMed Central

    Hughes, Adam L; Hughes, Casey E; Henderson, Kiersten A; Yazvenko, Nina; Gottschling, Daniel E

    2016-01-01

    Mitochondrial dysfunction is a hallmark of aging, and underlies the development of many diseases. Cells maintain mitochondrial homeostasis through a number of pathways that remodel the mitochondrial proteome or alter mitochondrial content during times of stress or metabolic adaptation. Here, using yeast as a model system, we identify a new mitochondrial degradation system that remodels the mitochondrial proteome of aged cells. Unlike many common mitochondrial degradation pathways, this system selectively removes a subset of membrane proteins from the mitochondrial inner and outer membranes, while leaving the remainder of the organelle intact. Selective removal of preexisting proteins is achieved by sorting into a mitochondrial-derived compartment, or MDC, followed by release through mitochondrial fission and elimination by autophagy. Formation of MDCs requires the import receptors Tom70/71, and failure to form these structures exacerbates preexisting mitochondrial dysfunction, suggesting that the MDC pathway provides protection to mitochondria in times of stress. DOI: http://dx.doi.org/10.7554/eLife.13943.001 PMID:27097106

  8. Validation subset selections for extrapolation oriented QSPAR models.

    PubMed

    Szántai-Kis, Csaba; Kövesdi, István; Kéri, György; Orfi, László

    2003-01-01

    One of the most important features of QSPAR models is their predictive ability. The predictive ability of QSPAR models should be checked by external validation. In this work we examined three different types of external validation set selection methods for their usefulness in in-silico screening. The usefulness of the selection methods was studied in such a way that: 1) We generated thousands of QSPR models and stored them in 'model banks'. 2) We selected a final top model from the model banks based on three different validation set selection methods. 3) We predicted large data sets, which we called 'chemical universe sets', and calculated the corresponding SEPs. The models were generated from small fractions of the available water solubility data during a GA Variable Subset Selection procedure. The external validation sets were constructed by random selections, uniformly distributed selections or by perimeter-oriented selections. We found that the best performing models on the perimeter-oriented external validation sets usually gave the best validation results when the remaining part of the available data was overwhelmingly large, i.e., when the model had to make a lot of extrapolations. We also compared the top final models obtained from external validation set selection methods in three independent and different sizes of 'chemical universe sets'.

  9. Heterostructured magnetite-titanate nanosheets for prompt charge selective binding and magnetic separation of mixed proteins.

    PubMed

    Zhou, Qinhua; Lu, Zhufeng; Cao, Xuebo

    2014-02-01

    We reported the prompt charge selective binding and magnetic separation of mixed proteins by utilizing heterostructured Fe3O4-Na2Ti3O7 nanosheets. Fe3O4-Na2Ti3O7 nanosheets are found to combine a variety of structure and property merits, such as the increased interlayer galleries, exposed exchange sites, flexible framework, and magnetic manipulability. Probing the dissociation dynamics of Na(+) inside the nanosheets reveals that they possess remarkably enhanced Na(+) dissociation capability and the dissociation rate of Na(+) reaches 7.9×10(-)(6)mol g(-)(1)s(-)(1), much superior to titanate nanotubes. In model protein separation experiments, we utilize mixed proteins containing albumin and hemoglobin to assess Fe3O4-Na2Ti3O7 nanosheets. It is found that, by controlling the pH of the sample at 6, positively charged hemoglobin and negatively charged albumin are immediately separated (∼5s) by the nanosheets and the saturated loading capacity of hemoglobin on the nanosheets reaches 4.7±0.61g g(-)(1). Furthermore, hemoglobin bound to the nanosheets can be readily released after buffer wash and is not damaged, while the nanosheets are recyclable and maintain their high efficiency. The outstanding performance of Fe3O4-Na2Ti3O7 nanosheets in separating mixed proteins is attributed to the ultrafast Na(+) dissociation rate, flexible titanate framework, open geometry, and aqueous-like environment to stabilize proteins. These merits, together with the recyclability and cost effectiveness, should make Fe3O4-Na2Ti3O7 nanosheets ideal candidates for biological recognition, isolation, and purification under technologically useful conditions.

  10. Mutation-selection models of coding sequence evolution with site-heterogeneous amino acid fitness profiles.

    PubMed

    Rodrigue, Nicolas; Philippe, Hervé; Lartillot, Nicolas

    2010-03-01

    Modeling the interplay between mutation and selection at the molecular level is key to evolutionary studies. To this end, codon-based evolutionary models have been proposed as pertinent means of studying long-range evolutionary patterns and are widely used. However, these approaches have not yet consolidated results from amino acid level phylogenetic studies showing that selection acting on proteins displays strong site-specific effects, which translate into heterogeneous amino acid propensities across the columns of alignments; related codon-level studies have instead focused on either modeling a single selective context for all codon columns, or a separate selective context for each codon column, with the former strategy deemed too simplistic and the latter deemed overparameterized. Here, we integrate recent developments in nonparametric statistical approaches to propose a probabilistic model that accounts for the heterogeneity of amino acid fitness profiles across the coding positions of a gene. We apply the model to a dozen real protein-coding gene alignments and find it to produce biologically plausible inferences, for instance, as pertaining to site-specific amino acid constraints, as well as distributions of scaled selection coefficients. In their account of mutational features as well as the heterogeneous regimes of selection at the amino acid level, the modeling approaches studied here can form a backdrop for several extensions, accounting for other selective features, for variable population size, or for subtleties of mutational features, all with parameterizations couched within population-genetic theory. PMID:20176949

  11. Macromolecular composition dictates receptor and G protein selectivity of regulator of G protein signaling (RGS) 7 and 9-2 protein complexes in living cells.

    PubMed

    Masuho, Ikuo; Xie, Keqiang; Martemyanov, Kirill A

    2013-08-30

    Regulator of G protein signaling (RGS) proteins play essential roles in the regulation of signaling via G protein-coupled receptors (GPCRs). With hundreds of GPCRs and dozens of G proteins, it is important to understand how RGS regulates selective GPCR-G protein signaling. In neurons of the striatum, two RGS proteins, RGS7 and RGS9-2, regulate signaling by μ-opioid receptor (MOR) and dopamine D2 receptor (D2R) and are implicated in drug addiction, movement disorders, and nociception. Both proteins form trimeric complexes with the atypical G protein β subunit Gβ5 and a membrane anchor, R7BP. In this study, we examined GTPase-accelerating protein (GAP) activity as well as Gα and GPCR selectivity of RGS7 and RGS9-2 complexes in live cells using a bioluminescence resonance energy transfer-based assay that monitors dissociation of G protein subunits. We showed that RGS9-2/Gβ5 regulated both Gi and Go with a bias toward Go, but RGS7/Gβ5 could serve as a GAP only for Go. Interestingly, R7BP enhanced GAP activity of RGS7 and RGS9-2 toward Go and Gi and enabled RGS7 to regulate Gi signaling. Neither RGS7 nor RGS9-2 had any activity toward Gz, Gs, or Gq in the absence or presence of R7BP. We also observed no effect of GPCRs (MOR and D2R) on the G protein bias of R7 RGS proteins. However, the GAP activity of RGS9-2 showed a strong receptor preference for D2R over MOR. Finally, RGS7 displayed an four times greater GAP activity relative to RGS9-2. These findings illustrate the principles involved in establishing G protein and GPCR selectivity of striatal RGS proteins.

  12. Protease-resistant prions selectively decrease Shadoo protein.

    PubMed

    Watts, Joel C; Stöhr, Jan; Bhardwaj, Sumita; Wille, Holger; Oehler, Abby; Dearmond, Stephen J; Giles, Kurt; Prusiner, Stanley B

    2011-11-01

    The central event in prion diseases is the conformational conversion of the cellular prion protein (PrP(C)) into PrP(Sc), a partially protease-resistant and infectious conformer. However, the mechanism by which PrP(Sc) causes neuronal dysfunction remains poorly understood. Levels of Shadoo (Sho), a protein that resembles the flexibly disordered N-terminal domain of PrP(C), were found to be reduced in the brains of mice infected with the RML strain of prions [1], implying that Sho levels may reflect the presence of PrP(Sc) in the brain. To test this hypothesis, we examined levels of Sho during prion infection using a variety of experimental systems. Sho protein levels were decreased in the brains of mice, hamsters, voles, and sheep infected with different natural and experimental prion strains. Furthermore, Sho levels were decreased in the brains of prion-infected, transgenic mice overexpressing Sho and in infected neuroblastoma cells. Time-course experiments revealed that Sho levels were inversely proportional to levels of protease-resistant PrP(Sc). Membrane anchoring and the N-terminal domain of PrP both influenced the inverse relationship between Sho and PrP(Sc). Although increased Sho levels had no discernible effect on prion replication in mice, we conclude that Sho is the first non-PrP marker specific for prion disease. Additional studies using this paradigm may provide insight into the cellular pathways and systems subverted by PrP(Sc) during prion disease. PMID:22163178

  13. Large-Scale Identification of Putative Exported Proteins in Candida albicans by Genetic Selection

    PubMed Central

    Monteoliva, L.; López Matas, M.; Gil, C.; Nombela, C.; Pla, J.

    2002-01-01

    In all living organisms, secreted proteins play essential roles in different processes. Of special interest is the construction of the fungal cell wall, since this structure is absent from mammalian cells. The identification of the proteins involved in its biogenesis is therefore a primary goal in antifungal research. To perform a systematic identification of such proteins in Candida albicans, we carried out a genetic screening in which in-frame fusions with an intracellular allele of invertase gene SUC2 of Saccharomyces cerevisiae can be used to select and identify putatively exported proteins in the heterologous host S. cerevisiae. Eighty-three clones were selected, including 11 previously identified genes from C. albicans as well as 41 C. albicans genes that encode proteins homologous to already described proteins from related organisms. They include enzymes involved in cell wall synthesis and protein secretion. We also found membrane receptors and transporters presumably related to the interaction of C. albicans with the environment as well as extracellular enzymes and proteins involved in different morphological transitions. In addition, 11 C. albicans open reading frames (ORFs) identified in this screening encode proteins homologous to unknown or putative proteins, while 5 ORFs encode novel secreted proteins without known homologues in other organisms. This screening procedure therefore not only identifies a set of targets of interest in antifungal research but also provides new clues for understanding the topological locations of many proteins involved in processes relevant to the pathogenicity of this microorganism. PMID:12456000

  14. Protein Folding Activity of Ribosomal RNA Is a Selective Target of Two Unrelated Antiprion Drugs

    PubMed Central

    Tribouillard-Tanvier, Déborah; Dos Reis, Suzana; Gug, Fabienne; Voisset, Cécile; Béringue, Vincent; Sabate, Raimon; Kikovska, Ema; Talarek, Nicolas; Bach, Stéphane; Huang, Chenhui; Desban, Nathalie; Saupe, Sven J.; Supattapone, Surachai; Thuret, Jean-Yves; Chédin, Stéphane; Vilette, Didier; Galons, Hervé; Sanyal, Suparna; Blondel, Marc

    2008-01-01

    Background 6-Aminophenanthridine (6AP) and Guanabenz (GA, a drug currently in use for the treatment of hypertension) were isolated as antiprion drugs using a yeast-based assay. These structurally unrelated molecules are also active against mammalian prion in several cell-based assays and in vivo in a mouse model for prion-based diseases. Methodology/Principal Findings Here we report the identification of cellular targets of these drugs. Using affinity chromatography matrices for both drugs, we demonstrate an RNA-dependent interaction of 6AP and GA with the ribosome. These specific interactions have no effect on the peptidyl transferase activity of the ribosome or on global translation. In contrast, 6AP and GA specifically inhibit the ribosomal RNA-mediated protein folding activity of the ribosome. Conclusion/Significance 6AP and GA are therefore the first compounds to selectively inhibit the protein folding activity of the ribosome. They thus constitute precious tools to study the yet largely unexplored biological role of this protein folding activity. PMID:18478094

  15. Selecting Improved Peptidyl Motifs for Cytosolic Delivery of Disparate Protein and Nanoparticle Materials

    PubMed Central

    Boeneman, Kelly; Delehanty, James B.; Blanco-Canosa, Juan B.; Susumu, Kimihiro; Stewart, Michael H.; Oh, Eunkeu; Huston, Alan L.; Dawson, Glyn; Ingale, Sampat; Walters, Ryan; Domowicz, Miriam; Deschamps, Jeffrey R.; Algar, W. Russ; DiMaggio, Stassi; Manono, Janet; Spillmann, Christopher M.; Thompson, Darren; Jennings, Travis L.; Dawson, Philip E.; Medintz, Igor L.

    2013-01-01

    Cell penetrating peptides facilitate efficient intracellular uptake of diverse materials ranging from small contrast agents to larger proteins and nanoparticles. However, a significant impediment remains in the subsequent compartmentalization/endosomal sequestration of most of these cargoes. Previous functional screening suggested that a modular peptide originally designed to deliver palmitoyl-protein thioesterase inhibitors to neurons could mediate endosomal escape in cultured cells. Here, we detail properties relevant to this peptide’s ability to mediate cytosolic delivery of quantum dots (QDs) to a wide range of cell-types, brain tissue culture and a developing chick embryo in a remarkably non-toxic manner. The peptide further facilitated efficient endosomal escape of large proteins, dendrimers and other nanoparticle materials. We undertook an iterative structure-activity relationship analysis of the peptide by discretely modifying key components including length, charge, fatty acid content and their order using a comparative, semi-quantitative assay. This approach allowed us to define the key motifs required for endosomal escape, to select more efficient escape sequences, along with unexpectedly identifying a sequence modified by one methylene group that specifically targeted QDs to cellular membranes. We interpret our results within a model of peptide function and highlight implications for in vivo labeling and nanoparticle-mediated drug delivery by using different peptides to co-deliver cargoes to cells and engage in multifunctional labeling. PMID:23710591

  16. Quorum-sensing Salmonella selectively trigger protein expression within tumors

    PubMed Central

    Swofford, Charles A.; Van Dessel, Nele; Forbes, Neil S.

    2015-01-01

    Salmonella that secrete anticancer proteins have the potential to eliminate tumors, but nonspecific expression causes damage to healthy tissue. We hypothesize that Salmonella, integrated with a density-dependent switch, would only express proteins in tightly packed colonies within tumors. To test this hypothesis, we cloned the lux quorum-sensing (QS) system and a GFP reporter into nonpathogenic Salmonella. Fluorescence and bacterial density were measured in culture and in a tumor-on-a-chip device to determine the critical density necessary to initiate expression. QS Salmonella were injected into 4T1 tumor-bearing mice to quantify GFP expression in vivo using immunofluorescence. At densities below 0.6 × 1010 cfu/g in tumors, less than 3% of QS Salmonella expressed GFP. Above densities of 4.2 × 1010 cfu/g, QS Salmonella had similar expression levels to constitutive controls. GFP expression by QS colonies was dependent upon the distance to neighboring bacteria. No colonies expressed GFP when the average distance to neighbors was greater than 155 µm. Calculations of autoinducer concentrations showed that expression was sigmoidally dependent on density and inversely dependent on average radial distance. Based on bacterial counts from excised tissue, the liver density (0.0079 × 1010 cfu/g) was less than the critical density (0.11 × 1010 cfu/g) necessary to initiate expression. QS Salmonella are a promising tool for cancer treatment that will target drugs to tumors while preventing damage to healthy tissue. PMID:25737556

  17. Interacting Boson Model: selected recent developments

    SciTech Connect

    Balantekin, A.B.

    1986-01-01

    The Interacting Boson Model is briefly reviewed. Recent applications of this model to the low-lying collective magnetic-dipole excitations and to the spectra of /sup 195/Ir are described. 13 refs., 3 figs.

  18. HABITAT MODELING APPROACHES FOR RESTORATION SITE SELECTION

    EPA Science Inventory

    Numerous modeling approaches have been used to develop predictive models of species-environment and species-habitat relationships. These models have been used in conservation biology and habitat or species management, but their application to restoration efforts has been minimal...

  19. In vivo selection of basic region-leucine zipper proteins with altered DNA-binding specificities

    SciTech Connect

    Sera, T.; Schultz, P.G.

    1996-04-02

    A transcription interference assay was used to generate mutant basic region-leucine zipper proteins with altered DNA-binding specificities. A library of mutants of a CCAAT/enhancer binding protein was constructed by randomizing five DNA-contacting amino acids in the basic region Asn{sup {minus}18}, Ala{sup {minus}15}, Val{sup {minus}14}, Ser{sup {minus}11}, And Arg{sup {minus}10}. These mutants were then selected for their ability to bind mutant recognition sequences containing substitutions at the 2 and 3 positions of the wild-type sequence 5{prime}-A{sup 5}T{sup 4}T{sup 3}G{sup 2}C{sup 1}G{sup 1{prime}}C{sup 2{prime}}A{sup 3}A{sup 4{prime}}T{sup 5{prime}}-3{prime}. Mutants containing the sequence Leu{sup {minus}18}Tyr{sup {minus}15}Xaa{sup {minus}14}-Tyr{sup {minus}11}Arg{sup {minus}10}, in which four of the five contact residues are altered, were identified that recognize the palindromic sequence 5{prime}-ACTCYCGY{prime}GAT-3{prime} (Xaa=asparagine when Y = G; Xaa = methionine when Y = A). Moreover, in a selection against the sequence 5{prime}-ATTACGTAAT-3{prime}, mutants were obtained containing substitutions not only in the basic region but also in the hinge region between the basic and leucine zipper regions. The mutant proteins showed high specificity in a functional transcription interference assay. A model for the interaction of these mutants with the target DNA sequences is discussed. 28 refs., 1 fig., 4 tabs.

  20. Protein-resistant NTA-functionalized polymer brushes for selective and stable immobilization of histidine-tagged proteins.

    PubMed

    Gautrot, Julien E; Huck, Wilhelm T S; Welch, Martin; Ramstedt, Madeleine

    2010-01-01

    Protein-resistant polymeric coatings that allow highly selective immobilization of specific biomolecules are essential for biomedical applications such as microarrays, biosensing, heterogeneous catalysis, and bioengineering. Polymer brushes are particularly interesting for this purpose because their chemical structure and physical properties can easily be tailored to meet specific needs. This article explores the functionalization of two protein-resistant polymer brushes, poly(oligoethylene glycol methacrylate) (POEGMA) and poly(hydroxyethyl methacrylate) (PHEMA), with nitrilotriacetic acid (NTA) moieties that can complex histidine-tagged (His-tagged) proteins selectively and reversibly. Using fluorescence microscopy, IR spectroscopy, X-ray photoelectron spectroscopy, surface plasmon resonanace, and ellipsometry, we demonstrate that His-tagged green fluorescent protein can be immobilized on NTA brushes with high stability and loading. The loading saturation reached for NTA-POEGMA is higher than that for NTA-PHEMA because of increased swelling of the former brush. Despite this higher loading capacity, NTA-POEGMA remained highly protein-resistant, which shows its potential for "clean" and specific protein immobilization. Finally, we showed that the preserved protein resistance of NTA-POEGMA brushes can be used to generate well-defined binary biofunctional patterns via a simple protocol of incubations and washes. These patterns may find applications in cell arraying and screening. PMID:20356235

  1. Cognitive Niches: An Ecological Model of Strategy Selection

    ERIC Educational Resources Information Center

    Marewski, Julian N.; Schooler, Lael J.

    2011-01-01

    How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each…

  2. Targeted reengineering of protein geranylgeranyltransferase type I selectivity functionally implicates active-site residues in protein-substrate recognition.

    PubMed

    Gangopadhyay, Soumyashree A; Losito, Erica L; Hougland, James L

    2014-01-21

    Posttranslational modifications are vital for the function of many proteins. Prenylation is one such modification, wherein protein geranylgeranyltransferase type I (GGTase-I) or protein farnesyltransferase (FTase) modify proteins by attaching a 20- or 15-carbon isoprenoid group, respectively, to a cysteine residue near the C-terminus of a target protein. These enzymes require a C-terminal Ca1a2X sequence on their substrates, with the a1, a2, and X residues serving as substrate-recognition elements for FTase and/or GGTase-I. While crystallographic structures of rat GGTase-I show a tightly packed and hydrophobic a2 residue binding pocket, consistent with a preference for moderately sized a2 residues in GGTase-I substrates, the functional impact of enzyme-substrate contacts within this active site remains to be determined. Using site-directed mutagenesis and peptide substrate structure-activity studies, we have identified specific active-site residues within rat GGTase-I involved in substrate recognition and developed novel GGTase-I variants with expanded/altered substrate selectivity. The ability to drastically alter GGTase-I selectivity mirrors similar behavior observed in FTase but employs mutation of a distinct set of structurally homologous active-site residues. Our work demonstrates that tunable selectivity may be a general phenomenon among multispecific enzymes involved in posttranslational modification and raises the possibility of variable substrate selectivity among GGTase-I orthologues from different organisms. Furthermore, the GGTase-I variants developed herein can serve as tools for studying GGTase-I substrate selectivity and the effects of prenylation pathway modifications on specific proteins. PMID:24344934

  3. A multilayer evaluation approach for protein structure prediction and model quality assessment.

    PubMed

    Zhang, Jingfen; Wang, Qingguo; Vantasin, Kittinun; Zhang, Jiong; He, Zhiquan; Kosztin, Ioan; Shang, Yi; Xu, Dong

    2011-01-01

    Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy. PMID:21997706

  4. A multilayer evaluation approach for protein structure prediction and model quality assessment.

    PubMed

    Zhang, Jingfen; Wang, Qingguo; Vantasin, Kittinun; Zhang, Jiong; He, Zhiquan; Kosztin, Ioan; Shang, Yi; Xu, Dong

    2011-01-01

    Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy.

  5. Quorum-sensing Salmonella selectively trigger protein expression within tumors.

    PubMed

    Swofford, Charles A; Van Dessel, Nele; Forbes, Neil S

    2015-03-17

    Salmonella that secrete anticancer proteins have the potential to eliminate tumors, but nonspecific expression causes damage to healthy tissue. We hypothesize that Salmonella, integrated with a density-dependent switch, would only express proteins in tightly packed colonies within tumors. To test this hypothesis, we cloned the lux quorum-sensing (QS) system and a GFP reporter into nonpathogenic Salmonella. Fluorescence and bacterial density were measured in culture and in a tumor-on-a-chip device to determine the critical density necessary to initiate expression. QS Salmonella were injected into 4T1 tumor-bearing mice to quantify GFP expression in vivo using immunofluorescence. At densities below 0.6 × 10(10) cfu/g in tumors, less than 3% of QS Salmonella expressed GFP. Above densities of 4.2 × 10(10) cfu/g, QS Salmonella had similar expression levels to constitutive controls. GFP expression by QS colonies was dependent upon the distance to neighboring bacteria. No colonies expressed GFP when the average distance to neighbors was greater than 155 µm. Calculations of autoinducer concentrations showed that expression was sigmoidally dependent on density and inversely dependent on average radial distance. Based on bacterial counts from excised tissue, the liver density (0.0079 × 10(10) cfu/g) was less than the critical density (0.11 × 10(10) cfu/g) necessary to initiate expression. QS Salmonella are a promising tool for cancer treatment that will target drugs to tumors while preventing damage to healthy tissue.

  6. Patterns of neutral diversity under general models of selective sweeps.

    PubMed

    Coop, Graham; Ralph, Peter

    2012-09-01

    Two major sources of stochasticity in the dynamics of neutral alleles result from resampling of finite populations (genetic drift) and the random genetic background of nearby selected alleles on which the neutral alleles are found (linked selection). There is now good evidence that linked selection plays an important role in shaping polymorphism levels in a number of species. One of the best-investigated models of linked selection is the recurrent full-sweep model, in which newly arisen selected alleles fix rapidly. However, the bulk of selected alleles that sweep into the population may not be destined for rapid fixation. Here we develop a general model of recurrent selective sweeps in a coalescent framework, one that generalizes the recurrent full-sweep model to the case where selected alleles do not sweep to fixation. We show that in a large population, only the initial rapid increase of a selected allele affects the genealogy at partially linked sites, which under fairly general assumptions are unaffected by the subsequent fate of the selected allele. We also apply the theory to a simple model to investigate the impact of recurrent partial sweeps on levels of neutral diversity and find that for a given reduction in diversity, the impact of recurrent partial sweeps on the frequency spectrum at neutral sites is determined primarily by the frequencies rapidly achieved by the selected alleles. Consequently, recurrent sweeps of selected alleles to low frequencies can have a profound effect on levels of diversity but can leave the frequency spectrum relatively unperturbed. In fact, the limiting coalescent model under a high rate of sweeps to low frequency is identical to the standard neutral model. The general model of selective sweeps we describe goes some way toward providing a more flexible framework to describe genomic patterns of diversity than is currently available. PMID:22714413

  7. Structural requirements to obtain highly potent and selective 18 kDa Translocator Protein (TSPO) Ligands.

    PubMed

    Taliani, Sabrina; Pugliesi, Isabella; Da Settimo, Federico

    2011-01-01

    The (18 kDa) Translocator Protein (TSPO), was initially identified in 1977 as peripheral binding site for the benzodiazepine diazepam and named "Peripheral-type benzodiazepine receptor (PBR)". It is an evolutionarily well-conserved protein particularly located at the outer/inner mitochondrial membrane contact sites, in closely association with the 32 kDa voltage-dependent anion channel (VDAC) and the 30 kDa adenine nucleotide translocase (ANT), thus forming the mitochondrial permeability transition pore (MPTP). TSPO is ubiquitary expressed in peripheral tissues (steroid producing tissues, liver, heart, kidney, lung, immune system) and in lower levels in the central nervous system, where it is mainly located in glial cells, and in neurons. TSPO is involved in a variety of biological processes such as cholesterol transport, steroidogenesis, calcium homeostasis, lipid metabolism, mitochondrial oxidation, cell growth and differentiation, apoptosis induction, and regulation of immune functions. In the last decade, many studies have reported that TSPO basal expression is altered in a number of human pathologies, such as cancer and neurodegenerative disorders (Huntington's and Alzheimer's diseases), as well as in various forms of brain injury and inflammation and anxiety. Consequently, TSPO has not only been suggested as a promising drug target for a number of therapeutic applications (anticonvulsant, anxiolytic, immunomodulating, etc.), but also as valid diagnostic marker for related-disease state and progression, prompting the development of specific labelled ligands as powerful tools for imaging techniques. A number of structurally different classes of ligands have been reported, showing high affinity and selectivity towards TSPO. Indeed, most of these ligands have been designed starting from selective CBR ligands which were structurally modified in order to shift their affinity towards TSPO. Extensive structure-activity relationship studies were performed allowing to

  8. Reactibodies generated by kinetic selection couple chemical reactivity with favorable protein dynamics.

    PubMed

    Smirnov, Ivan; Carletti, Eugénie; Kurkova, Inna; Nachon, Florian; Nicolet, Yvain; Mitkevich, Vladimir A; Débat, Hélène; Avalle, Bérangère; Belogurov, Alexey A; Kuznetsov, Nikita; Reshetnyak, Andrey; Masson, Patrick; Tonevitsky, Alexander G; Ponomarenko, Natalia; Makarov, Alexander A; Friboulet, Alain; Tramontano, Alfonso; Gabibov, Alexander

    2011-09-20

    Igs offer a versatile template for combinatorial and rational design approaches to the de novo creation of catalytically active proteins. We have used a covalent capture selection strategy to identify biocatalysts from within a human semisynthetic antibody variable fragment library that uses a nucleophilic mechanism. Specific phosphonylation at a single tyrosine within the variable light-chain framework was confirmed in a recombinant IgG construct. High-resolution crystallographic structures of unmodified and phosphonylated Fabs display a 15-Å-deep two-chamber cavity at the interface of variable light (V(L)) and variable heavy (V(H)) fragments having a nucleophilic tyrosine at the base of the site. The depth and structure of the pocket are atypical of antibodies in general but can be compared qualitatively with the catalytic site of cholinesterases. A structurally disordered heavy chain complementary determining region 3 loop, constituting a wall of the cleft, is stabilized after covalent modification by hydrogen bonding to the phosphonate tropinol moiety. These features and presteady state kinetics analysis indicate that an induced fit mechanism operates in this reaction. Mutations of residues located in this stabilized loop do not interfere with direct contacts to the organophosphate ligand but can interrogate second shell interactions, because the H3 loop has a conformation adjusted for binding. Kinetic and thermodynamic parameters along with computational docking support the active site model, including plasticity and simple catalytic components. Although relatively uncomplicated, this catalytic machinery displays both stereo- and chemical selectivity. The organophosphate pesticide paraoxon is hydrolyzed by covalent catalysis with rate-limiting dephosphorylation. This reactibody is, therefore, a kinetically selected protein template that has enzyme-like catalytic attributes. PMID:21896761

  9. Amyloid precursor protein selective gamma-secretase inhibitors for treatment of Alzheimer's disease

    PubMed Central

    2010-01-01

    Introduction Inhibition of gamma-secretase presents a direct target for lowering Aβ production in the brain as a therapy for Alzheimer's disease (AD). However, gamma-secretase is known to process multiple substrates in addition to amyloid precursor protein (APP), most notably Notch, which has limited clinical development of inhibitors targeting this enzyme. It has been postulated that APP substrate selective inhibitors of gamma-secretase would be preferable to non-selective inhibitors from a safety perspective for AD therapy. Methods In vitro assays monitoring inhibitor potencies at APP γ-site cleavage (equivalent to Aβ40), and Notch ε-site cleavage, in conjunction with a single cell assay to simultaneously monitor selectivity for inhibition of Aβ production vs. Notch signaling were developed to discover APP selective gamma-secretase inhibitors. In vivo efficacy for acute reduction of brain Aβ was determined in the PDAPP transgene model of AD, as well as in wild-type FVB strain mice. In vivo selectivity was determined following seven days x twice per day (b.i.d.) treatment with 15 mg/kg/dose to 1,000 mg/kg/dose ELN475516, and monitoring brain Aβ reduction vs. Notch signaling endpoints in periphery. Results The APP selective gamma-secretase inhibitors ELN318463 and ELN475516 reported here behave as classic gamma-secretase inhibitors, demonstrate 75- to 120-fold selectivity for inhibiting Aβ production compared with Notch signaling in cells, and displace an active site directed inhibitor at very high concentrations only in the presence of substrate. ELN318463 demonstrated discordant efficacy for reduction of brain Aβ in the PDAPP compared with wild-type FVB, not observed with ELN475516. Improved in vivo safety of ELN475516 was demonstrated in the 7d repeat dose study in wild-type mice, where a 33% reduction of brain Aβ was observed in mice terminated three hours post last dose at the lowest dose of inhibitor tested. No overt in-life or post

  10. Selection of Temporal Lags When Modeling Economic and Financial Processes.

    PubMed

    Matilla-Garcia, Mariano; Ojeda, Rina B; Marin, Manuel Ruiz

    2016-10-01

    This paper suggests new nonparametric statistical tools and procedures for modeling linear and nonlinear univariate economic and financial processes. In particular, the tools presented help in selecting relevant lags in the model description of a general linear or nonlinear time series; that is, nonlinear models are not a restriction. The tests seem to be robust to the selection of free parameters. We also show that the test can be used as a diagnostic tool for well-defined models. PMID:27550703

  11. Model Selection for Monitoring CO2 Plume during Sequestration

    2014-12-31

    The model selection method developed as part of this project mainly includes four steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models, (2) model clustering using multidimensional scaling coupled with k-mean clustering, (3) model selection using the Bayes' rule in the reduced model space, (4) model expansion using iterative resampling of the posterior models. The fourth step expresses one of the advantages of the method: it provides a built-in means ofmore » quantifying the uncertainty in predictions made with the selected models. In our application to plume monitoring, by expanding the posterior space of models, the final ensemble of representations of geological model can be used to assess the uncertainty in predicting the future displacement of the CO2 plume. The software implementation of this approach is attached here.« less

  12. The Multilingual Lexicon: Modelling Selection and Control

    ERIC Educational Resources Information Center

    de Bot, Kees

    2004-01-01

    In this paper an overview of research on the multilingual lexicon is presented as the basis for a model for processing multiple languages. With respect to specific issues relating to the processing of more than two languages, it is suggested that there is no need to develop a specific model for such multilingual processing, but at the same time we…

  13. A Split-Ubiquitin Based Strategy Selecting for Protein Complex-Interfering Mutations.

    PubMed

    Gronemeyer, Thomas; Chollet, Julian; Werner, Stefan; Glomb, Oliver; Bäuerle, Anne; Johnsson, Nils

    2016-01-01

    Understanding the topologies and functions of protein interaction networks requires the selective removal of single interactions. We introduce a selection strategy that enriches among a random library of alleles for mutations that impair the binding to a given partner protein. The selection makes use of a split-ubiquitin based protein interaction assay. This assay provides yeast cells that carry protein complex disturbing mutations with the advantage of being able to survive on uracil-lacking media. Applied to the exemplary interaction between the PB domains of the yeast proteins Bem1 and Cdc24, we performed two independent selections. The selections were either analyzed by Sanger sequencing of isolated clones or by next generation sequencing (NGS) of pools of clones. Both screens enriched for the same mutation in position 833 of Cdc24. Biochemical analysis confirmed that this mutation disturbs the interaction with Bem1 but not the fold of the protein. The larger dataset obtained by NGS achieved a more complete representation of the bipartite interaction interface of Cdc24.

  14. A Split-Ubiquitin Based Strategy Selecting for Protein Complex-Interfering Mutations

    PubMed Central

    Gronemeyer, Thomas; Chollet, Julian; Werner, Stefan; Glomb, Oliver; Bäuerle, Anne; Johnsson, Nils

    2016-01-01

    Understanding the topologies and functions of protein interaction networks requires the selective removal of single interactions. We introduce a selection strategy that enriches among a random library of alleles for mutations that impair the binding to a given partner protein. The selection makes use of a split-ubiquitin based protein interaction assay. This assay provides yeast cells that carry protein complex disturbing mutations with the advantage of being able to survive on uracil-lacking media. Applied to the exemplary interaction between the PB domains of the yeast proteins Bem1 and Cdc24, we performed two independent selections. The selections were either analyzed by Sanger sequencing of isolated clones or by next generation sequencing (NGS) of pools of clones. Both screens enriched for the same mutation in position 833 of Cdc24. Biochemical analysis confirmed that this mutation disturbs the interaction with Bem1 but not the fold of the protein. The larger dataset obtained by NGS achieved a more complete representation of the bipartite interaction interface of Cdc24. PMID:27402358

  15. Nonstructural Proteins Are Preferential Positive Selection Targets in Zika Virus and Related Flaviviruses.

    PubMed

    Sironi, Manuela; Forni, Diego; Clerici, Mario; Cagliani, Rachele

    2016-09-01

    The Flavivirus genus comprises several human pathogens such as dengue virus (DENV), Japanese encephalitis virus (JEV), and Zika virus (ZIKV). Although ZIKV usually causes mild symptoms, growing evidence is linking it to congenital birth defects and to increased risk of Guillain-Barré syndrome. ZIKV encodes a polyprotein that is processed to produce three structural and seven nonstructural (NS) proteins. We investigated the evolution of the viral polyprotein in ZIKV and in related flaviviruses (DENV, Spondweni virus, and Kedougou virus). After accounting for saturation issues, alignment uncertainties, and recombination, we found evidence of episodic positive selection on the branch that separates DENV from the other flaviviruses. NS1 emerged as the major selection target, and selected sites were located in immune epitopes or in functionally important protein regions. Three of these sites are located in an NS1 region that interacts with structural proteins and is essential for virion biogenesis. Analysis of the more recent evolutionary history of ZIKV lineages indicated that positive selection acted on NS5 and NS4B, this latter representing the preferential target. All selected sites were located in the N-terminal portion of NS4B, which inhibits interferon response. One of the positively selected sites (26M/I/T/V) in ZIKV also represents a selection target in sylvatic DENV2 isolates, and a nearby residue evolves adaptively in JEV. Two additional positively selected sites are within a protein region that interacts with host (e.g. STING) and viral (i.e. NS1, NS4A) proteins. Notably, mutations in the NS4B region of other flaviviruses modulate neurovirulence and/or neuroinvasiveness. These results suggest that the positively selected sites we identified modulate viral replication and contribute to immune evasion. These sites should be prioritized in future experimental studies. However, analyses herein detected no selective events associated to the spread of the Asian

  16. Nonstructural Proteins Are Preferential Positive Selection Targets in Zika Virus and Related Flaviviruses

    PubMed Central

    Sironi, Manuela; Forni, Diego; Clerici, Mario; Cagliani, Rachele

    2016-01-01

    The Flavivirus genus comprises several human pathogens such as dengue virus (DENV), Japanese encephalitis virus (JEV), and Zika virus (ZIKV). Although ZIKV usually causes mild symptoms, growing evidence is linking it to congenital birth defects and to increased risk of Guillain-Barré syndrome. ZIKV encodes a polyprotein that is processed to produce three structural and seven nonstructural (NS) proteins. We investigated the evolution of the viral polyprotein in ZIKV and in related flaviviruses (DENV, Spondweni virus, and Kedougou virus). After accounting for saturation issues, alignment uncertainties, and recombination, we found evidence of episodic positive selection on the branch that separates DENV from the other flaviviruses. NS1 emerged as the major selection target, and selected sites were located in immune epitopes or in functionally important protein regions. Three of these sites are located in an NS1 region that interacts with structural proteins and is essential for virion biogenesis. Analysis of the more recent evolutionary history of ZIKV lineages indicated that positive selection acted on NS5 and NS4B, this latter representing the preferential target. All selected sites were located in the N-terminal portion of NS4B, which inhibits interferon response. One of the positively selected sites (26M/I/T/V) in ZIKV also represents a selection target in sylvatic DENV2 isolates, and a nearby residue evolves adaptively in JEV. Two additional positively selected sites are within a protein region that interacts with host (e.g. STING) and viral (i.e. NS1, NS4A) proteins. Notably, mutations in the NS4B region of other flaviviruses modulate neurovirulence and/or neuroinvasiveness. These results suggest that the positively selected sites we identified modulate viral replication and contribute to immune evasion. These sites should be prioritized in future experimental studies. However, analyses herein detected no selective events associated to the spread of the Asian

  17. Nonstructural Proteins Are Preferential Positive Selection Targets in Zika Virus and Related Flaviviruses.

    PubMed

    Sironi, Manuela; Forni, Diego; Clerici, Mario; Cagliani, Rachele

    2016-09-01

    The Flavivirus genus comprises several human pathogens such as dengue virus (DENV), Japanese encephalitis virus (JEV), and Zika virus (ZIKV). Although ZIKV usually causes mild symptoms, growing evidence is linking it to congenital birth defects and to increased risk of Guillain-Barré syndrome. ZIKV encodes a polyprotein that is processed to produce three structural and seven nonstructural (NS) proteins. We investigated the evolution of the viral polyprotein in ZIKV and in related flaviviruses (DENV, Spondweni virus, and Kedougou virus). After accounting for saturation issues, alignment uncertainties, and recombination, we found evidence of episodic positive selection on the branch that separates DENV from the other flaviviruses. NS1 emerged as the major selection target, and selected sites were located in immune epitopes or in functionally important protein regions. Three of these sites are located in an NS1 region that interacts with structural proteins and is essential for virion biogenesis. Analysis of the more recent evolutionary history of ZIKV lineages indicated that positive selection acted on NS5 and NS4B, this latter representing the preferential target. All selected sites were located in the N-terminal portion of NS4B, which inhibits interferon response. One of the positively selected sites (26M/I/T/V) in ZIKV also represents a selection target in sylvatic DENV2 isolates, and a nearby residue evolves adaptively in JEV. Two additional positively selected sites are within a protein region that interacts with host (e.g. STING) and viral (i.e. NS1, NS4A) proteins. Notably, mutations in the NS4B region of other flaviviruses modulate neurovirulence and/or neuroinvasiveness. These results suggest that the positively selected sites we identified modulate viral replication and contribute to immune evasion. These sites should be prioritized in future experimental studies. However, analyses herein detected no selective events associated to the spread of the Asian

  18. Selection in the Rapid Evolution of Gamete Recognition Proteins in Marine Invertebrates

    PubMed Central

    Vacquier, Victor D.; Swanson, Willie J.

    2011-01-01

    Animal fertilization is governed by the interaction (binding) of proteins on the surfaces of sperm and egg. In many examples presented herein, fertilization proteins evolve rapidly and show the signature of positive selection (adaptive evolution). This review describes the molecular evolution of fertilization proteins in sea urchins, abalone, and oysters, animals with external fertilization that broadcast their gametes into seawater. Theories regarding the selective forces responsible for the rapid evolution driven by positive selection seen in many fertilization proteins are discussed. This strong selection acting on divergence of interacting fertilization proteins might lead to prezygotic reproductive isolation and be a significant factor in the speciation process. Since only a fraction of all eggs are fertilized and only an infinitesimal fraction of male gametes succeed in fertilizing an egg, gametes are obviously a category of entities subjected to intense selection. It is curious that this is never mentioned in the literature dealing with selection, perhaps because we know so little about fitness differences among gametes.(ErnstMayr, 1997) PMID:21730046

  19. MaxMod: a hidden Markov model based novel interface to MODELLER for improved prediction of protein 3D models.

    PubMed

    Parida, Bikram K; Panda, Prasanna K; Misra, Namrata; Mishra, Barada K

    2015-02-01

    Modeling the three-dimensional (3D) structures of proteins assumes great significance because of its manifold applications in biomolecular research. Toward this goal, we present MaxMod, a graphical user interface (GUI) of the MODELLER program that combines profile hidden Markov model (profile HMM) method with Clustal Omega program to significantly improve the selection of homologous templates and target-template alignment for construction of accurate 3D protein models. MaxMod distinguishes itself from other existing GUIs of MODELLER software by implementing effortless modeling of proteins using templates that bear modified residues. Additionally, it provides various features such as loop optimization, express modeling (a feature where protein model can be generated directly from its sequence, without any further user intervention) and automatic update of PDB database, thus enhancing the user-friendly control of computational tasks. We find that HMM-based MaxMod performs better than other modeling packages in terms of execution time and model quality. MaxMod is freely available as a downloadable standalone tool for academic and non-commercial purpose at http://www.immt.res.in/maxmod/. PMID:25636267

  20. MaxMod: a hidden Markov model based novel interface to MODELLER for improved prediction of protein 3D models.

    PubMed

    Parida, Bikram K; Panda, Prasanna K; Misra, Namrata; Mishra, Barada K

    2015-02-01

    Modeling the three-dimensional (3D) structures of proteins assumes great significance because of its manifold applications in biomolecular research. Toward this goal, we present MaxMod, a graphical user interface (GUI) of the MODELLER program that combines profile hidden Markov model (profile HMM) method with Clustal Omega program to significantly improve the selection of homologous templates and target-template alignment for construction of accurate 3D protein models. MaxMod distinguishes itself from other existing GUIs of MODELLER software by implementing effortless modeling of proteins using templates that bear modified residues. Additionally, it provides various features such as loop optimization, express modeling (a feature where protein model can be generated directly from its sequence, without any further user intervention) and automatic update of PDB database, thus enhancing the user-friendly control of computational tasks. We find that HMM-based MaxMod performs better than other modeling packages in terms of execution time and model quality. MaxMod is freely available as a downloadable standalone tool for academic and non-commercial purpose at http://www.immt.res.in/maxmod/.

  1. On Optimal Input Design and Model Selection for Communication Channels

    SciTech Connect

    Li, Yanyan; Djouadi, Seddik M; Olama, Mohammed M

    2013-01-01

    In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

  2. Adaptive selection and coevolution at the proteins of the Polycomb repressive complexes in Drosophila.

    PubMed

    Calvo-Martín, J M; Librado, P; Aguadé, M; Papaceit, M; Segarra, C

    2016-02-01

    Polycomb group (PcG) proteins are important epigenetic regulatory proteins that modulate the chromatin state through posttranslational histone modifications. These interacting proteins form multimeric complexes that repress gene expression. Thus, PcG proteins are expected to evolve coordinately, which might be reflected in their phylogenetic trees by concordant episodes of positive selection and by a correlation in evolutionary rates. In order to detect these signals of coevolution, the molecular evolution of 17 genes encoding the subunits of five Polycomb repressive complexes has been analyzed in the Drosophila genus. The observed distribution of divergence differs substantially among and along proteins. Indeed, CAF1 is uniformly conserved, whereas only the established protein domains are conserved in other proteins, such as PHO, PHOL, PSC, PH-P and ASX. Moreover, regions with a low divergence not yet described as protein domains are present, for instance, in SFMBT and SU(Z)12. Maximum likelihood methods indicate an acceleration in the nonsynonymous substitution rate at the lineage ancestral to the obscura group species in most genes encoding subunits of the Pcl-PRC2 complex and in genes Sfmbt, Psc and Kdm2. These methods also allow inferring the action of positive selection in this lineage at genes E(z) and Sfmbt. Finally, the protein interaction network predicted from the complete proteomes of 12 Drosophila species using a coevolutionary approach shows two tight PcG clusters. These clusters include well-established binary interactions among PcG proteins as well as new putative interactions.

  3. Astrophysical Model Selection in Gravitational Wave Astronomy

    NASA Technical Reports Server (NTRS)

    Adams, Matthew R.; Cornish, Neil J.; Littenberg, Tyson B.

    2012-01-01

    Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%.

  4. Bayesian model selection for LISA pathfinder

    NASA Astrophysics Data System (ADS)

    Karnesis, Nikolaos; Nofrarias, Miquel; Sopuerta, Carlos F.; Gibert, Ferran; Armano, Michele; Audley, Heather; Congedo, Giuseppe; Diepholz, Ingo; Ferraioli, Luigi; Hewitson, Martin; Hueller, Mauro; Korsakova, Natalia; McNamara, Paul W.; Plagnol, Eric; Vitale, Stefano

    2014-03-01

    The main goal of the LISA Pathfinder (LPF) mission is to fully characterize the acceleration noise models and to test key technologies for future space-based gravitational-wave observatories similar to the eLISA concept. The data analysis team has developed complex three-dimensional models of the LISA Technology Package (LTP) experiment onboard the LPF. These models are used for simulations, but, more importantly, they will be used for parameter estimation purposes during flight operations. One of the tasks of the data analysis team is to identify the physical effects that contribute significantly to the properties of the instrument noise. A way of approaching this problem is to recover the essential parameters of a LTP model fitting the data. Thus, we want to define the simplest model that efficiently explains the observations. To do so, adopting a Bayesian framework, one has to estimate the so-called Bayes factor between two competing models. In our analysis, we use three main different methods to estimate it: the reversible jump Markov chain Monte Carlo method, the Schwarz criterion, and the Laplace approximation. They are applied to simulated LPF experiments in which the most probable LTP model that explains the observations is recovered. The same type of analysis presented in this paper is expected to be followed during flight operations. Moreover, the correlation of the output of the aforementioned methods with the design of the experiment is explored.

  5. Using multilevel models to quantify heterogeneity in resource selection

    USGS Publications Warehouse

    Wagner, T.; Diefenbach, D.R.; Christensen, S.A.; Norton, A.S.

    2011-01-01

    Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection. ?? The Wildlife Society, 2011.

  6. Positive Selection within a Diatom Species Acts on Putative Protein Interactions and Transcriptional Regulation

    PubMed Central

    Koester, Julie A.; Swanson, Willie J.; Armbrust, E. Virginia

    2013-01-01

    Diatoms are the most species-rich group of microalgae, and their contribution to marine primary production is important on a global scale. Diatoms can form dense blooms through rapid asexual reproduction; mutations acquired and propagated during blooms likely provide the genetic, and thus phenotypic, variability upon which natural selection may act. Positive selection was tested using genome and transcriptome-wide pair-wise comparisons of homologs in three genera of diatoms (Pseudo-nitzschia, Ditylum, and Thalassiosira) that represent decreasing phylogenetic distances. The signal of positive selection was greatest between two strains of Thalassiosira pseudonana. Further testing among seven strains of T. pseudonana yielded 809 candidate genes of positive selection, which are 7% of the protein-coding genes. Orphan genes and genes encoding protein-binding domains and transcriptional regulators were enriched within the set of positively selected genes relative to the genome as a whole. Positively selected genes were linked to the potential selective pressures of nutrient limitation and sea surface temperature based on analysis of gene expression profiles and identification of positively selected genes in subsets of strains from locations with similar environmental conditions. The identification of positively selected genes presents an opportunity to test new hypotheses in natural populations and the laboratory that integrate selected genotypes in T. pseudonana with their associated phenotypes and selective forces. PMID:23097498

  7. Positive selection within a diatom species acts on putative protein interactions and transcriptional regulation.

    PubMed

    Koester, Julie A; Swanson, Willie J; Armbrust, E Virginia

    2013-02-01

    Diatoms are the most species-rich group of microalgae, and their contribution to marine primary production is important on a global scale. Diatoms can form dense blooms through rapid asexual reproduction; mutations acquired and propagated during blooms likely provide the genetic, and thus phenotypic, variability upon which natural selection may act. Positive selection was tested using genome and transcriptome-wide pair-wise comparisons of homologs in three genera of diatoms (Pseudo-nitzschia, Ditylum, and Thalassiosira) that represent decreasing phylogenetic distances. The signal of positive selection was greatest between two strains of Thalassiosira pseudonana. Further testing among seven strains of T. pseudonana yielded 809 candidate genes of positive selection, which are 7% of the protein-coding genes. Orphan genes and genes encoding protein-binding domains and transcriptional regulators were enriched within the set of positively selected genes relative to the genome as a whole. Positively selected genes were linked to the potential selective pressures of nutrient limitation and sea surface temperature based on analysis of gene expression profiles and identification of positively selected genes in subsets of strains from locations with similar environmental conditions. The identification of positively selected genes presents an opportunity to test new hypotheses in natural populations and the laboratory that integrate selected genotypes in T. pseudonana with their associated phenotypes and selective forces. PMID:23097498

  8. Application of model bread baking in the examination of arabinoxylan-protein complexes in rye bread.

    PubMed

    Buksa, Krzysztof

    2016-09-01

    The changes in molecular mass of arabinoxylan (AX) and protein caused by bread baking process were examined using a model rye bread. Instead of the normal flour, the dough contained starch, water-extractable AX and protein which were isolated from rye wholemeal. From the crumb of selected model breads, starch was removed releasing AX-protein complexes, which were further examined by size exclusion chromatography. On the basis of the research, it was concluded that optimum model mix can be composed of 3-6% AX and 3-6% rye protein isolate at 94-88% of rye starch meaning with the most similar properties to low extraction rye flour. Application of model rye bread allowed to examine the interactions between AX and proteins. Bread baked with a share of AX, rye protein and starch, from which the complexes of the highest molar mass were isolated, was characterized by the strongest structure of the bread crumb. PMID:27185141

  9. Application of model bread baking in the examination of arabinoxylan-protein complexes in rye bread.

    PubMed

    Buksa, Krzysztof

    2016-09-01

    The changes in molecular mass of arabinoxylan (AX) and protein caused by bread baking process were examined using a model rye bread. Instead of the normal flour, the dough contained starch, water-extractable AX and protein which were isolated from rye wholemeal. From the crumb of selected model breads, starch was removed releasing AX-protein complexes, which were further examined by size exclusion chromatography. On the basis of the research, it was concluded that optimum model mix can be composed of 3-6% AX and 3-6% rye protein isolate at 94-88% of rye starch meaning with the most similar properties to low extraction rye flour. Application of model rye bread allowed to examine the interactions between AX and proteins. Bread baked with a share of AX, rye protein and starch, from which the complexes of the highest molar mass were isolated, was characterized by the strongest structure of the bread crumb.

  10. Constructor selection models for space construction missions

    NASA Technical Reports Server (NTRS)

    Johnson, Richard J.; Morgenthaler, George W.

    1990-01-01

    The topics are presented in viewgraph form and include the following: systems design; picking the best constructor pool; prototype model; linear programming; simulated annealing; neural networks; and genetic algorithms.

  11. Identification and Validation of Selected Universal Stress Protein Domain Containing Drought-Responsive Genes in Pigeonpea (Cajanus cajan L.).

    PubMed

    Sinha, Pallavi; Pazhamala, Lekha T; Singh, Vikas K; Saxena, Rachit K; Krishnamurthy, L; Azam, Sarwar; Khan, Aamir W; Varshney, Rajeev K

    2015-01-01

    Pigeonpea is a resilient crop, which is relatively more drought tolerant than many other legume crops. To understand the molecular mechanisms of this unique feature of pigeonpea, 51 genes were selected using the Hidden Markov Models (HMM) those codes for proteins having close similarity to universal stress protein domain. Validation of these genes was conducted on three pigeonpea genotypes (ICPL 151, ICPL 8755, and ICPL 227) having different levels of drought tolerance. Gene expression analysis using qRT-PCR revealed 6, 8, and 18 genes to be ≥2-fold differentially expressed in ICPL 151, ICPL 8755, and ICPL 227, respectively. A total of 10 differentially expressed genes showed ≥2-fold up-regulation in the more drought tolerant genotype, which encoded four different classes of proteins. These include plant U-box protein (four genes), universal stress protein A-like protein (four genes), cation/H(+) antiporter protein (one gene) and an uncharacterized protein (one gene). Genes C.cajan_29830 and C.cajan_33874 belonging to uspA, were found significantly expressed in all the three genotypes with ≥2-fold expression variations. Expression profiling of these two genes on the four other legume crops revealed their specific role in pigeonpea. Therefore, these genes seem to be promising candidates for conferring drought tolerance specifically to pigeonpea. PMID:26779199

  12. Identification and Validation of Selected Universal Stress Protein Domain Containing Drought-Responsive Genes in Pigeonpea (Cajanus cajan L.)

    PubMed Central

    Sinha, Pallavi; Pazhamala, Lekha T.; Singh, Vikas K.; Saxena, Rachit K.; Krishnamurthy, L.; Azam, Sarwar; Khan, Aamir W.; Varshney, Rajeev K.

    2016-01-01

    Pigeonpea is a resilient crop, which is relatively more drought tolerant than many other legume crops. To understand the molecular mechanisms of this unique feature of pigeonpea, 51 genes were selected using the Hidden Markov Models (HMM) those codes for proteins having close similarity to universal stress protein domain. Validation of these genes was conducted on three pigeonpea genotypes (ICPL 151, ICPL 8755, and ICPL 227) having different levels of drought tolerance. Gene expression analysis using qRT-PCR revealed 6, 8, and 18 genes to be ≥2-fold differentially expressed in ICPL 151, ICPL 8755, and ICPL 227, respectively. A total of 10 differentially expressed genes showed ≥2-fold up-regulation in the more drought tolerant genotype, which encoded four different classes of proteins. These include plant U-box protein (four genes), universal stress protein A-like protein (four genes), cation/H(+) antiporter protein (one gene) and an uncharacterized protein (one gene). Genes C.cajan_29830 and C.cajan_33874 belonging to uspA, were found significantly expressed in all the three genotypes with ≥2-fold expression variations. Expression profiling of these two genes on the four other legume crops revealed their specific role in pigeonpea. Therefore, these genes seem to be promising candidates for conferring drought tolerance specifically to pigeonpea. PMID:26779199

  13. Synthetic computational models of selective attention.

    PubMed

    Raffone, Antonino

    2006-11-01

    Computational modeling plays an important role to understand the mechanisms of attention. In this framework, synthetic computational models can uniquely contribute to integrate different explanatory levels and neurocognitive findings, with special reference to the integration of attention and awareness processes. Novel combined experimental and computational investigations can lead to important insights, as in the revived domain of neural correlates of attention- and awareness-related meditation states and traits.

  14. Python Program to Select HII Region Models

    NASA Astrophysics Data System (ADS)

    Miller, Clare; Lamarche, Cody; Vishwas, Amit; Stacey, Gordon J.

    2016-01-01

    HII regions are areas of singly ionized Hydrogen formed by the ionizing radiaiton of upper main sequence stars. The infrared fine-structure line emissions, particularly Oxygen, Nitrogen, and Neon, can give important information about HII regions including gas temperature and density, elemental abundances, and the effective temperature of the stars that form them. The processes involved in calculating this information from observational data are complex. Models, such as those provided in Rubin 1984 and those produced by Cloudy (Ferland et al, 2013) enable one to extract physical parameters from observational data. However, the multitude of search parameters can make sifting through models tedious. I digitized Rubin's models and wrote a Python program that is able to take observed line ratios and their uncertainties and find the Rubin or Cloudy model that best matches the observational data. By creating a Python script that is user friendly and able to quickly sort through models with a high level of accuracy, this work increases efficiency and reduces human error in matching HII region models to observational data.

  15. Methods for model selection in applied science and engineering.

    SciTech Connect

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  16. Screening and expression of selected taxonomically conserved and unique hypothetical proteins in Burkholderia pseudomallei K96243

    NASA Astrophysics Data System (ADS)

    Akhir, Nor Azurah Mat; Nadzirin, Nurul; Mohamed, Rahmah; Firdaus-Raih, Mohd

    2015-09-01

    Hypothetical proteins of bacterial pathogens represent a large numbers of novel biological mechanisms which could belong to essential pathways in the bacteria. They lack functional characterizations mainly due to the inability of sequence homology based methods to detect functional relationships in the absence of detectable sequence similarity. The dataset derived from this study showed 550 candidates conserved in genomes that has pathogenicity information and only present in the Burkholderiales order. The dataset has been narrowed down to taxonomic clusters. Ten proteins were selected for ORF amplification, seven of them were successfully amplified, and only four proteins were successfully expressed. These proteins will be great candidates in determining the true function via structural biology.

  17. In vitro Selection and Interaction Studies of a DNA Aptamer Targeting Protein A

    PubMed Central

    Stoltenburg, Regina; Schubert, Thomas; Strehlitz, Beate

    2015-01-01

    A new DNA aptamer targeting Protein A is presented. The aptamer was selected by use of the FluMag-SELEX procedure. The SELEX technology (Systematic Evolution of Ligands by EXponential enrichment) is widely applied as an in vitro selection and amplification method to generate target-specific aptamers and exists in various modified variants. FluMag-SELEX is one of them and is characterized by the use of magnetic beads for target immobilization and fluorescently labeled oligonucleotides for monitoring the aptamer selection progress. Structural investigations and sequence truncation experiments of the selected aptamer for Protein A led to the conclusion, that a stem-loop structure at its 5’-end including the 5’-primer binding site is essential for aptamer-target binding. Extensive interaction analyses between aptamer and Protein A were performed by methods like surface plasmon resonance, MicroScale Thermophoresis and bead-based binding assays using fluorescence measurements. The binding of the aptamer to its target was thus investigated in assays with immobilization of one of the binding partners each, and with both binding partners in solution. Affinity constants were determined in the low micromolar to submicromolar range, increasing to the nanomolar range under the assumption of avidity. Protein A provides more than one binding site for the aptamer, which may overlap with the known binding sites for immunoglobulins. The aptamer binds specifically to both native and recombinant Protein A, but not to other immunoglobulin-binding proteins like Protein G and L. Cross specificity to other proteins was not found. The application of the aptamer is directed to Protein A detection or affinity purification. Moreover, whole cells of Staphylococcus aureus, presenting Protein A on the cell surface, could also be bound by the aptamer. PMID:26221730

  18. A permutation approach for selecting the penalty parameter in penalized model selection.

    PubMed

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-12-01

    We describe a simple, computationally efficient, permutation-based procedure for selecting the penalty parameter in LASSO-penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), scaled sparse linear regression, and a selection method based on recently developed testing procedures for the LASSO.

  19. Modeling Selective Intergranular Oxidation of Binary Alloys

    SciTech Connect

    Xu, Zhijie; Li, Dongsheng; Schreiber, Daniel K.; Rosso, Kevin M.; Bruemmer, Stephen M.

    2015-01-07

    Intergranular attack of alloys under hydrothermal conditions is a complex problem that depends on metal and oxygen transport kinetics via solid-state and channel-like pathways to an advancing oxidation front. Experiments reveal very different rates of intergranular attack and minor element depletion distances ahead of the oxidation front for nickel-based binary alloys depending on the minor element. For example, a significant Cr depletion up to 9 µm ahead of grain boundary crack tips were documented for Ni-5Cr binary alloy, in contrast to relatively moderate Al depletion for Ni-5Al (~100s of nm). We present a mathematical kinetics model that adapts Wagner’s model for thick film growth to intergranular attack of binary alloys. The transport coefficients of elements O, Ni, Cr, and Al in bulk alloys and along grain boundaries were estimated from the literature. For planar surface oxidation, a critical concentration of the minor element can be determined from the model where the oxide of minor element becomes dominant over the major element. This generic model for simple grain boundary oxidation can predict oxidation penetration velocities and minor element depletion distances ahead of the advancing front that are comparable to experimental data. The significant distance of depletion of Cr in Ni-5Cr in contrast to the localized Al depletion in Ni-5Al can be explained by the model due to the combination of the relatively faster diffusion of Cr along the grain boundary and slower diffusion in bulk grains, relative to Al.

  20. Modeling selective intergranular oxidation of binary alloys

    NASA Astrophysics Data System (ADS)

    Xu, Zhijie; Li, Dongsheng; Schreiber, Daniel K.; Rosso, Kevin M.; Bruemmer, Stephen M.

    2015-01-01

    Intergranular attack of alloys under hydrothermal conditions is a complex problem that depends on metal and oxygen transport kinetics via solid-state and channel-like pathways to an advancing oxidation front. Experiments reveal very different rates of intergranular attack and minor element depletion distances ahead of the oxidation front for nickel-based binary alloys depending on the minor element. For example, a significant Cr depletion up to 9 μm ahead of grain boundary crack tips was documented for Ni-5Cr binary alloy, in contrast to relatively moderate Al depletion for Ni-5Al (˜100 s of nm). We present a mathematical kinetics model that adapts Wagner's model for thick film growth to intergranular attack of binary alloys. The transport coefficients of elements O, Ni, Cr, and Al in bulk alloys and along grain boundaries were estimated from the literature. For planar surface oxidation, a critical concentration of the minor element can be determined from the model where the oxide of minor element becomes dominant over the major element. This generic model for simple grain boundary oxidation can predict oxidation penetration velocities and minor element depletion distances ahead of the advancing front that are comparable to experimental data. The significant distance of depletion of Cr in Ni-5Cr in contrast to the localized Al depletion in Ni-5Al can be explained by the model due to the combination of the relatively faster diffusion of Cr along the grain boundary and slower diffusion in bulk grains, relative to Al.

  1. Boosting model performance and interpretation by entangling preprocessing selection and variable selection.

    PubMed

    Gerretzen, Jan; Szymańska, Ewa; Bart, Jacob; Davies, Antony N; van Manen, Henk-Jan; van den Heuvel, Edwin R; Jansen, Jeroen J; Buydens, Lutgarde M C

    2016-09-28

    The aim of data preprocessing is to remove data artifacts-such as a baseline, scatter effects or noise-and to enhance the contextually relevant information. Many preprocessing methods exist to deliver one or more of these benefits, but which method or combination of methods should be used for the specific data being analyzed is difficult to select. Recently, we have shown that a preprocessing selection approach based on Design of Experiments (DoE) enables correct selection of highly appropriate preprocessing strategies within reasonable time frames. In that approach, the focus was solely on improving the predictive performance of the chemometric model. This is, however, only one of the two relevant criteria in modeling: interpretation of the model results can be just as important. Variable selection is often used to achieve such interpretation. Data artifacts, however, may hamper proper variable selection by masking the true relevant variables. The choice of preprocessing therefore has a huge impact on the outcome of variable selection methods and may thus hamper an objective interpretation of the final model. To enhance such objective interpretation, we here integrate variable selection into the preprocessing selection approach that is based on DoE. We show that the entanglement of preprocessing selection and variable selection not only improves the interpretation, but also the predictive performance of the model. This is achieved by analyzing several experimental data sets of which the true relevant variables are available as prior knowledge. We show that a selection of variables is provided that complies more with the true informative variables compared to individual optimization of both model aspects. Importantly, the approach presented in this work is generic. Different types of models (e.g. PCR, PLS, …) can be incorporated into it, as well as different variable selection methods and different preprocessing methods, according to the taste and experience of

  2. Boosting model performance and interpretation by entangling preprocessing selection and variable selection.

    PubMed

    Gerretzen, Jan; Szymańska, Ewa; Bart, Jacob; Davies, Antony N; van Manen, Henk-Jan; van den Heuvel, Edwin R; Jansen, Jeroen J; Buydens, Lutgarde M C

    2016-09-28

    The aim of data preprocessing is to remove data artifacts-such as a baseline, scatter effects or noise-and to enhance the contextually relevant information. Many preprocessing methods exist to deliver one or more of these benefits, but which method or combination of methods should be used for the specific data being analyzed is difficult to select. Recently, we have shown that a preprocessing selection approach based on Design of Experiments (DoE) enables correct selection of highly appropriate preprocessing strategies within reasonable time frames. In that approach, the focus was solely on improving the predictive performance of the chemometric model. This is, however, only one of the two relevant criteria in modeling: interpretation of the model results can be just as important. Variable selection is often used to achieve such interpretation. Data artifacts, however, may hamper proper variable selection by masking the true relevant variables. The choice of preprocessing therefore has a huge impact on the outcome of variable selection methods and may thus hamper an objective interpretation of the final model. To enhance such objective interpretation, we here integrate variable selection into the preprocessing selection approach that is based on DoE. We show that the entanglement of preprocessing selection and variable selection not only improves the interpretation, but also the predictive performance of the model. This is achieved by analyzing several experimental data sets of which the true relevant variables are available as prior knowledge. We show that a selection of variables is provided that complies more with the true informative variables compared to individual optimization of both model aspects. Importantly, the approach presented in this work is generic. Different types of models (e.g. PCR, PLS, …) can be incorporated into it, as well as different variable selection methods and different preprocessing methods, according to the taste and experience of

  3. The Genealogy of Samples in Models with Selection

    PubMed Central

    Neuhauser, C.; Krone, S. M.

    1997-01-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models, DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case. PMID:9071604

  4. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    Following a request from the States of South Carolina and Georgia, downstream radiological consequences from postulated accidental aqueous releases at the three Savannah River Site nonreactor nuclear facilities will be examined. This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the accidents to be used in the future study.

  5. Evolution and physics in comparative protein structure modeling.

    PubMed

    Fiser, András; Feig, Michael; Brooks, Charles L; Sali, Andrej

    2002-06-01

    From a physical perspective, the native structure of a protein is a consequence of physical forces acting on the protein and solvent atoms during the folding process. From a biological perspective, the native structure of proteins is a result of evolution over millions of years. Correspondingly, there are two types of protein structure prediction methods, de novo prediction and comparative modeling. We review comparative protein structure modeling and discuss the incorporation of physical considerations into the modeling process. A good starting point for achieving this aim is provided by comparative modeling by satisfaction of spatial restraints. Incorporation of physical considerations is illustrated by an inclusion of solvation effects into the modeling of loops.

  6. Knowledge-based model building of proteins: concepts and examples.

    PubMed Central

    Bajorath, J.; Stenkamp, R.; Aruffo, A.

    1993-01-01

    We describe how to build protein models from structural templates. Methods to identify structural similarities between proteins in cases of significant, moderate to low, or virtually absent sequence similarity are discussed. The detection and evaluation of structural relationships is emphasized as a central aspect of protein modeling, distinct from the more technical aspects of model building. Computational techniques to generate and complement comparative protein models are also reviewed. Two examples, P-selectin and gp39, are presented to illustrate the derivation of protein model structures and their use in experimental studies. PMID:7505680

  7. Validation of a P-Glycoprotein (P-gp) Humanized Mouse Model by Integrating Selective Absolute Quantification of Human MDR1, Mouse Mdr1a and Mdr1b Protein Expressions with In Vivo Functional Analysis for Blood-Brain Barrier Transport

    PubMed Central

    Sadiq, Muhammad Waqas; Uchida, Yasuo; Hoshi, Yutaro; Tachikawa, Masanori; Terasaki, Tetsuya; Hammarlund-Udenaes, Margareta

    2015-01-01

    It is essential to establish a useful validation method for newly generated humanized mouse models. The novel approach of combining our established species-specific protein quantification method combined with in vivo functional studies is evaluated to validate a humanized mouse model of P-gp/MDR1 efflux transporter. The P-gp substrates digoxin, verapamil and docetaxel were administered to male FVB Mdr1a/1b(+/+) (FVB WT), FVB Mdr1a/1b(-/-) (Mdr1a/1b(-/-)), C57BL/6 Mdr1a/1b(+/+) (C57BL/6 WT) and humanized C57BL (hMDR1) mice. Brain-to-plasma total concentration ratios (Kp) were measured. Quantitative targeted absolute proteomic (QTAP) analysis was used to selectively quantify the protein expression levels of hMDR1, Mdr1a and Mdr1b in the isolated brain capillaries. The protein expressions of other transporters, receptors and claudin-5 were also quantified. The Kp for digoxin, verapamil, and docetaxel were 20, 30 and 4 times higher in the Mdr1a/1b(-/-) mice than in the FVB WT controls, as expected. The Kp for digoxin, verapamil and docetaxel were 2, 16 and 2-times higher in the hMDR1 compared to the C57BL/6 WT mice. The hMDR1 mice had 63- and 9.1-fold lower expressions of the hMDR1 and Mdr1a proteins than the corresponding expression of Mdr1a in C57BL/6 WT mice, respectively. The protein expression levels of other molecules were almost consistent between C57BL/6 WT and hMDR1 mice. The P-gp function at the BBB in the hMDR1 mice was smaller than that in WT mice due to lower protein expression levels of hMDR1 and Mdr1a. The combination of QTAP and in vivo functional analyses was successfully applied to validate the humanized animal model and evaluates its suitability for further studies. PMID:25932627

  8. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    PubMed

    Mannakee, Brian K; Gutenkunst, Ryan N

    2016-07-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  9. Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination.

    PubMed

    Zheng, Wei; Ye, Xiaoduan; Friedman, Alan M; Bailey-Kellogg, Chris

    2007-01-01

    Protein engineering by site-directed recombination seeks to develop proteins with new or improved function, by accumulating multiple mutations from a set of homologous parent proteins. A library of hybrid proteins is created by recombining the parent proteins at specified breakpoint locations; subsequent screening/selection identifies hybrids with desirable functional characteristics. In order to improve the frequency of generating novel hybrids, this paper develops the first approach to explicitly plan for diversity in site-directed recombination, including metrics for characterizing the diversity of a planned hybrid library and efficient algorithms for optimizing experiments accordingly. The goal is to choose breakpoint locations to sample sequence space as uniformly as possible (which we argue maximizes diversity), under the constraints imposed by the recombination process and the given set of parents. A dynamic programming approach selects optimal breakpoint locations in polynomial time. Application of our method to optimizing breakpoints for an example biosynthetic enzyme, purE, demonstrates the significance of diversity optimization and the effectiveness of our algorithms.

  10. In Vitro Selection of Proteins with Desired Characteristics Using mRNA-display

    PubMed Central

    Valencia, C. Alexander; Zou, Jianwei; Liu, Rihe

    2013-01-01

    mRNA-display is an amplification-based, iterative rounds of in vitro protein selection technique that circumvents a number of difficulties associated with yeast two-hybrid and phage display. Because of the covalent linkage between the genotype and the phenotype, mRNA-display provides a powerful means for reading and amplifying a peptide or protein sequence after it has been selected from a library with very high diversity. The purpose of this article is to provide a summary of the field and practical framework of mRNA-display-based selections. We summarize the advantages and limitations of selections using mRNA-display as well as the recent applications, namely, the identification of novel affinity reagents, target-binding partners, and enzyme substrates from synthetic peptide or natural proteome libraries. Practically, we provide a detailed procedure for performing mRNA-display-based selections with the aim of identifying protease substrates and binding partners of a target protein. Furthermore, we describe how to confirm the function of the selected protein sequences by biochemical assays and bioinformatic tools. PMID:23201412

  11. Widespread Positive Selection Drives Differentiation of Centromeric Proteins in the Drosophila melanogaster subgroup.

    PubMed

    Beck, Emily A; Llopart, Ana

    2015-11-25

    Rapid evolution of centromeric satellite repeats is thought to cause compensatory amino acid evolution in interacting centromere-associated kinetochore proteins. Cid, a protein that mediates kinetochore/centromere interactions, displays particularly high amino acid turnover. Rapid evolution of both Cid and centromeric satellite repeats led us to hypothesize that the apparent compensatory evolution may extend to interacting partners in the Condensin I complex (i.e., SMC2, SMC4, Cap-H, Cap-D2, and Cap-G) and HP1s. Missense mutations in these proteins often result in improper centromere formation and aberrant chromosome segregation, thus selection for maintained function and coevolution among proteins of the complex is likely strong. Here, we report evidence of rapid evolution and recurrent positive selection in seven centromere-associated proteins in species of the Drosophila melanogaster subgroup, and further postulate that positive selection on these proteins could be a result of centromere drive and compensatory changes, with kinetochore proteins competing for optimal spindle attachment.

  12. Highly selective isolation and purification of heme proteins in biological samples using multifunctional magnetic nanospheres.

    PubMed

    Liu, Yating; Li, Yan; Wei, Yun

    2014-12-01

    Magnetic particles with suitable surface modification are capable of binding proteins selectively, and magnetic separations have advantages of rapidity, convenience, and high selectivity. In this paper, new magnetic nanoparticles modified with imidazolium ionic liquid (Fe3O4 @SiO2 @ILs) were successfully fabricated. N-Methylimidazolium was immobilized onto silica-coated magnetic nanoparticles via γ-chloropropyl modification as a magnetic nanoadsorbent for heme protein separation. The particle size was about 90 nm without significant aggregation during the preparation process. Hemoglobin as one of heme proteins used in this experiment was compared with other nonheme proteins. It has been found that the magnetic nanoparticles can be used for more rapid, efficient, and specific adsorption of hemoglobin with a binding capacity as high as 5.78 mg/mg. In comparison with other adsorption materials of proteins in the previous reports, Fe3 O4 @SiO2 @ILs magnetic nanoparticles exhibit the excellent performance in isolation of heme proteins with higher binding capacity and selectivity. In addition, a short separation time makes the functionalized nanoparticles suitable for purifying unstable proteins, as well as having other potential applications in a variety of biomedical fields.

  13. Plant protein and secondary metabolites influence diet selection in a mammalian specialist herbivore

    PubMed Central

    Ulappa, Amy C.; Kelsey, Rick G.; Frye, Graham G.; Rachlow, Janet L.; Shipley, Lisa A.; Bond, Laura; Pu, Xinzhu; Forbey, Jennifer Sorensen

    2015-01-01

    For herbivores, nutrient intake is limited by the relatively low nutritional quality of plants and high concentrations of potentially toxic defensive compounds (plant secondary metabolites, PSMs) produced by many plants. In response to phytochemical challenges, some herbivores selectively forage on plants with higher nutrient and lower PSM concentrations relative to other plants. Pygmy rabbits (Brachylagus idahoensis) are dietary specialists that feed on sagebrush (Artemisia spp.) and forage on specific plants more than others within a foraging patch. We predicted that the plants with evidence of heavy foraging (browsed plants) would be of higher dietary quality than plants that were not browsed (unbrowsed). We used model selection to determine which phytochemical variables best explained the difference between browsed and unbrowsed plants. Higher crude protein increased the odds that plants would be browsed by pygmy rabbits and the opposite was the case for certain PSMs. Additionally, because pygmy rabbits can occupy foraging patches (burrows) for consecutive years, their browsing may influence the nutritional and PSM constituents of plants at the burrows. In a post hoc analysis, we did not find a significant relationship between phytochemical concentrations, browse status and burrow occupancy length. We concluded that pygmy rabbits use nutritional and chemical cues while making foraging decisions. PMID:26366011

  14. Selective destruction of protein function by chromophore-assisted laser inactivation

    SciTech Connect

    Jay, D.G.

    1988-08-01

    Chromophore-assisted laser inactivation of protein function has been achieved. After a protein binds a specific ligand or antibody conjugated with malachite green (C.I. 42,000), it is selectively inactivated by laser irradiation at a wavelength of light absorbed by the dye but not significantly absorbed by cellular components. Ligand-bound proteins in solution and on the surfaces of cells can be denatured without other proteins in the same samples being affected. Chromophore-assisted laser inactivation can be used to study cell surface phenomena by inactivating the functions of single proteins on living cells, a molecular extension of cellular laser ablation. It has an advantage over genetics and the use of specific inhibitors in that the protein function of a single cell within the organism can be inactivated by focusing the laser beam.

  15. Combining Design and Selection to Create Novel Protein-Peptide Interactions.

    PubMed

    Speltz, E B; Sawyer, N; Regan, L

    2016-01-01

    The ability to design new protein-protein interactions (PPIs) has many applications in biotechnology and medicine. The goal of designed PPIs is to achieve both high affinity and specificity for the target protein. A great challenge in protein design is to identify such proteins from an enormous number of potential sequences. Many computational and experimental methods have been developed to contend with this challenge. Here we describe one particularly powerful approach-semirational design-that combines design and selection. This approach has been applied to generate new PPIs for many applications, including novel affinity reagents for protein detection/purification and bioorthogonal modules for synthetic biology (Jackrel, Valverde, & Regan, 2009; Sawyer et al., 2014; Speltz, Brown, Hajare, Schlieker, & Regan, 2015; Speltz, Nathan, & Regan, 2015). PMID:27586335

  16. Quantifying attomole amounts of proteins from complex samples by nano-LC and selected reaction monitoring.

    PubMed

    Fröhlich, Thomas; Arnold, Georg J

    2011-01-01

    Selected reaction monitoring (SRM) is one of the most powerful techniques for the relative and absolute quantification of proteins from complex protein mixtures. In contrast to traditional protein quantification methods such as ELISAs or RIAs, the SRM method uses mass spectrometry for detection. Further benefits of SRM are as follows: (1) high specificity and sensitivity; (2) large linear dynamic range of at least three orders of magnitude; and (3) the possibility to quantify multiple proteins simultaneously in a single MS run from an individual sample. To perform SRM-based protein quantification reliably, a careful design of the assay is essential, and several pitfalls must be avoided. The aim of this chapter is to help SRM newcomers to establish SRM-based protein quantification assays and discuss an overview of typical work flows that are applied during SRM assay development.

  17. Selective Phosphorylation Inhibitor of Delta Protein Kinase C-Pyruvate Dehydrogenase Kinase Protein-Protein Interactions: Application for Myocardial Injury in Vivo.

    PubMed

    Qvit, Nir; Disatnik, Marie-Hélène; Sho, Eiketsu; Mochly-Rosen, Daria

    2016-06-22

    Protein kinases regulate numerous cellular processes, including cell growth, metabolism, and cell death. Because the primary sequence and the three-dimensional structure of many kinases are highly similar, the development of selective inhibitors for only one kinase is challenging. Furthermore, many protein kinases are pleiotropic, mediating diverse and sometimes even opposing functions by phosphorylating multiple protein substrates. Here, we set out to develop an inhibitor of a selective protein kinase phosphorylation of only one of its substrates. Focusing on the pleiotropic delta protein kinase C (δPKC), we used a rational approach to identify a distal docking site on δPKC for its substrate, pyruvate dehydrogenase kinase (PDK). We reasoned that an inhibitor of PDK's docking should selectively inhibit the phosphorylation of only PDK without affecting phosphorylation of the other δPKC substrates. Our approach identified a selective inhibitor of PDK docking to δPKC with an in vitro Kd of ∼50 nM and reducing cardiac injury IC50 of ∼5 nM. This inhibitor, which did not affect the phosphorylation of other δPKC substrates even at 1 μM, demonstrated that PDK phosphorylation alone is critical for δPKC-mediated injury by heart attack. The approach we describe is likely applicable for the identification of other substrate-specific kinase inhibitors. PMID:27218445

  18. Usefulness of a Darwinian System in a Biotechnological Application: Evolution of Optical Window Fluorescent Protein Variants under Selective Pressure

    PubMed Central

    Ng, David; Pauli, Jutta; Resch-Genger, Ute; Kühn, Enrico; Heuer, Steffen; Beisker, Wolfgang; Köster, Reinhard W.; Zitzelsberger, Horst; Caldwell, Randolph B

    2014-01-01

    With rare exceptions, natural evolution is an extremely slow process. One particularly striking exception in the case of protein evolution is in the natural production of antibodies. Developing B cells activate and diversify their immunoglobulin (Ig) genes by recombination, gene conversion (GC) and somatic hypermutation (SHM). Iterative cycles of hypermutation and selection continue until antibodies of high antigen binding specificity emerge (affinity maturation). The avian B cell line DT40, a cell line which is highly amenable to genetic manipulation and exhibits a high rate of targeted integration, utilizes both GC and SHM. Targeting the DT40's diversification machinery onto transgenes of interest inserted into the Ig loci and coupling selective pressure based on the desired outcome mimics evolution. Here we further demonstrate the usefulness of this platform technology by selectively pressuring a large shift in the spectral properties of the fluorescent protein eqFP615 into the highly stable and advanced optical imaging expediting fluorescent protein Amrose. The method is advantageous as it is time and cost effective and no prior knowledge of the outcome protein's structure is necessary. Amrose was evolved to have high excitation at 633 nm and excitation/emission into the far-red, which is optimal for whole-body and deep tissue imaging as we demonstrate in the zebrafish and mouse model. PMID:25192257

  19. Usefulness of a Darwinian system in a biotechnological application: evolution of optical window fluorescent protein variants under selective pressure.

    PubMed

    Schoetz, Ulrike; Deliolanis, Nikolaos C; Ng, David; Pauli, Jutta; Resch-Genger, Ute; Kühn, Enrico; Heuer, Steffen; Beisker, Wolfgang; Köster, Reinhard W; Zitzelsberger, Horst; Caldwell, Randolph B

    2014-01-01

    With rare exceptions, natural evolution is an extremely slow process. One particularly striking exception in the case of protein evolution is in the natural production of antibodies. Developing B cells activate and diversify their immunoglobulin (Ig) genes by recombination, gene conversion (GC) and somatic hypermutation (SHM). Iterative cycles of hypermutation and selection continue until antibodies of high antigen binding specificity emerge (affinity maturation). The avian B cell line DT40, a cell line which is highly amenable to genetic manipulation and exhibits a high rate of targeted integration, utilizes both GC and SHM. Targeting the DT40's diversification machinery onto transgenes of interest inserted into the Ig loci and coupling selective pressure based on the desired outcome mimics evolution. Here we further demonstrate the usefulness of this platform technology by selectively pressuring a large shift in the spectral properties of the fluorescent protein eqFP615 into the highly stable and advanced optical imaging expediting fluorescent protein Amrose. The method is advantageous as it is time and cost effective and no prior knowledge of the outcome protein's structure is necessary. Amrose was evolved to have high excitation at 633 nm and excitation/emission into the far-red, which is optimal for whole-body and deep tissue imaging as we demonstrate in the zebrafish and mouse model.

  20. Modelling protein side-chain conformations using constraint logic programming.

    PubMed

    Swain, M T; Kemp, G J

    2001-12-01

    Side-chain placement is an important sub-task in protein modelling. Selecting conformations for side-chains is a difficult problem because of the large search space to be explored. This problem can be addressed using constraint logic programming (CLP), which is an artificial intelligence technique developed to solve large combinatorial search problems. The side-chain placement problem can be expressed as a CLP program in which rotamer conformations are used as values for finite domain variables, and bad steric contacts involving rotamers are represented as constraints. This paper introduces the concept of null rotamers, and shows how these can be used in implementing a novel iterative approach. We present results that compare the accuracy of models constructed using different rotamer libraries and different domain variable enumeration heuristics. The results obtained using this CLP-based approach compare favourably with those obtained by other methods.

  1. Role of Positive Selection in Functional Divergence of Mammalian Neuronal Apoptosis Inhibitor Proteins during Evolution

    PubMed Central

    Kong, Fanzhi; Su, Zhaoliang; Zhou, Chenglin; Sun, Caixia; Liu, Yanfang; Zheng, Dong; Yuan, Hongyan; Yin, Jingping; Fang, Jie; Wang, Shengjun; Xu, Huaxi

    2011-01-01

    Neuronal apoptosis inhibitor proteins (NAIPs) are members of Nod-like receptor (NLR) protein family. Recent research demostrated that some NAIP genes were strongly associated with both innate immunity and many inflammatory diseases in humans. However, no similar phenomena have been reported in other mammals. Furthermore, some NAIP genes have undergone pseudogenization or have been lost during the evolution of some higher mammals. We therefore aimed to determine if functional divergence had occurred, and if natural selection had played an important role in the evolution of these genes. The results showed that NAIP genes have undergone pseudogenization and functional divergence, driven by positive selection. Positive selection has also influenced NAIP protein structure, resulting in further functional divergence. PMID:22131819

  2. Modeling Protein Folding and Applying It to a Relevant Activity

    ERIC Educational Resources Information Center

    Nelson, Allan; Goetze, Jim

    2004-01-01

    The different levels of protein structure that can be easily understood by creating a model that simulates protein folding, which can then be evaluated by applying it to a relevant activity, is presented. The materials required and the procedure for constructing a protein folding model are mentioned.

  3. Selection for Protein Kinetic Stability Connects Denaturation Temperatures to Organismal Temperatures and Provides Clues to Archaean Life.

    PubMed

    Romero-Romero, M Luisa; Risso, Valeria A; Martinez-Rodriguez, Sergio; Gaucher, Eric A; Ibarra-Molero, Beatriz; Sanchez-Ruiz, Jose M

    2016-01-01

    The relationship between the denaturation temperatures of proteins (Tm values) and the living temperatures of their host organisms (environmental temperatures: TENV values) is poorly understood. Since different proteins in the same organism may show widely different Tm's, no simple universal relationship between Tm and TENV should hold, other than Tm≥TENV. Yet, when analyzing a set of homologous proteins from different hosts, Tm's are oftentimes found to correlate with TENV's but this correlation is shifted upward on the Tm axis. Supporting this trend, we recently reported Tm's for resurrected Precambrian thioredoxins that mirror a proposed environmental cooling over long geological time, while remaining a shocking ~50°C above the proposed ancestral ocean temperatures. Here, we show that natural selection for protein kinetic stability (denaturation rate) can produce a Tm↔TENV correlation with a large upward shift in Tm. A model for protein stability evolution suggests a link between the Tm shift and the in vivo lifetime of a protein and, more specifically, allows us to estimate ancestral environmental temperatures from experimental denaturation rates for resurrected Precambrian thioredoxins. The TENV values thus obtained match the proposed ancestral ocean cooling, support comparatively high Archaean temperatures, and are consistent with a recent proposal for the environmental temperature (above 75°C) that hosted the last universal common ancestor. More generally, this work provides a framework for understanding how features of protein stability reflect the environmental temperatures of the host organisms. PMID:27253436

  4. Selection for Protein Kinetic Stability Connects Denaturation Temperatures to Organismal Temperatures and Provides Clues to Archaean Life

    PubMed Central

    Romero-Romero, M. Luisa; Risso, Valeria A.; Martinez-Rodriguez, Sergio; Gaucher, Eric A.; Ibarra-Molero, Beatriz; Sanchez-Ruiz, Jose M.

    2016-01-01

    The relationship between the denaturation temperatures of proteins (Tm values) and the living temperatures of their host organisms (environmental temperatures: TENV values) is poorly understood. Since different proteins in the same organism may show widely different Tm’s, no simple universal relationship between Tm and TENV should hold, other than Tm≥TENV. Yet, when analyzing a set of homologous proteins from different hosts, Tm’s are oftentimes found to correlate with TENV’s but this correlation is shifted upward on the Tm axis. Supporting this trend, we recently reported Tm’s for resurrected Precambrian thioredoxins that mirror a proposed environmental cooling over long geological time, while remaining a shocking ~50°C above the proposed ancestral ocean temperatures. Here, we show that natural selection for protein kinetic stability (denaturation rate) can produce a Tm↔TENV correlation with a large upward shift in Tm. A model for protein stability evolution suggests a link between the Tm shift and the in vivo lifetime of a protein and, more specifically, allows us to estimate ancestral environmental temperatures from experimental denaturation rates for resurrected Precambrian thioredoxins. The TENV values thus obtained match the proposed ancestral ocean cooling, support comparatively high Archaean temperatures, and are consistent with a recent proposal for the environmental temperature (above 75°C) that hosted the last universal common ancestor. More generally, this work provides a framework for understanding how features of protein stability reflect the environmental temperatures of the host organisms. PMID:27253436

  5. Selective repression of transcriptional activators at a distance by the Drosophila Krüppel protein.

    PubMed Central

    Licht, J D; Ro, M; English, M A; Grossel, M; Hansen, U

    1993-01-01

    The Krüppel (Kr) protein, bound at kilobase distances from the start site of transcription, represses transcription by RNA polymerase II in mammalian cells. Repression is monotonically dependent on the dose of Kr protein and the presence of Kr binding site(s) on the DNA. These data suggest an inhibitory protein-protein interaction between the Kr protein and proximal transcription factors. Repression by Kr depends on the specific activator protein driving transcription. In particular, Kr protein selectively represses transcription mediated by the Sp1 glutamine-rich activation domain, tethered to the promoter by a GAL4 DNA-binding domain, but does not repress transcription stimulated by the acidic GAL4 activator. We believe this represents repression by a quenching interaction between DNA-bound Kr protein and the activation region of Sp1, rather than competition between Sp1 and Kr for a limiting transcriptional component. Selective, context-related repression affords an added layer of combinatorial control of gene expression by sequence-specific transcription factors. Images Fig. 1 Fig. 4 PMID:8248254

  6. Bidimensional tandem mass spectrometry for selective identification of nitration sites in proteins.

    PubMed

    Amoresano, Angela; Chiappetta, Giovanni; Pucci, Piero; D'Ischia, Marco; Marino, Gennaro

    2007-03-01

    Nitration of protein tyrosine residues is very often regarded as a molecular signal of peroxynitrite formation during development, oxidative stress, and aging. However, protein nitration might also have biological functions comparable to protein phosphorylation, mainly in redox signaling and in signal transduction. The major challenge in the proteomic analysis of nitroproteins is the need to discriminate modified proteins, usually occurring at substoichiometric levels from the large amount of nonmodified proteins. Moreover, precise localization of the nitration site is often required to fully describe the biological process. Existing methodologies essentially rely on immunochemical techniques either using 2D-PAGE fractionation in combination with western blot analyses or exploiting immunoaffinity procedures to selectively capture nitrated proteins. Here we report a totally new approach involving dansyl chloride labeling of the nitration sites that rely on the enormous potential of MSn analysis. The tryptic digest from the entire protein mixture is directly analyzed by MS on a linear ion trap mass spectrometer. Discrimination between nitro- and unmodified peptide is based on two selectivity criteria obtained by combining a precursor ion scan and an MS3 analysis. This new procedure was successfully applied to the identification of 3-nitrotyrosine residues in complex protein mixtures. PMID:17243771

  7. Towards a Model for Protein Production Rates

    NASA Astrophysics Data System (ADS)

    Dong, J. J.; Schmittmann, B.; Zia, R. K. P.

    2007-07-01

    In the process of translation, ribosomes read the genetic code on an mRNA and assemble the corresponding polypeptide chain. The ribosomes perform discrete directed motion which is well modeled by a totally asymmetric simple exclusion process (TASEP) with open boundaries. Using Monte Carlo simulations and a simple mean-field theory, we discuss the effect of one or two "bottlenecks" (i.e., slow codons) on the production rate of the final protein. Confirming and extending previous work by Chou and Lakatos, we find that the location and spacing of the slow codons can affect the production rate quite dramatically. In particular, we observe a novel "edge" effect, i.e., an interaction of a single slow codon with the system boundary. We focus in detail on ribosome density profiles and provide a simple explanation for the length scale which controls the range of these interactions.

  8. Modelling protein functional domains in signal transduction using Maude

    NASA Technical Reports Server (NTRS)

    Sriram, M. G.

    2003-01-01

    Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

  9. A structural bioinformatics approach for identifying proteins predisposed to bind linear epitopes on pre-selected target proteins.

    PubMed

    Choi, Eun Jung; Jacak, Ron; Kuhlman, Brian

    2013-04-01

    We have developed a protocol for identifying proteins that are predisposed to bind linear epitopes on target proteins of interest. The protocol searches through the protein database for proteins (scaffolds) that are bound to peptides with sequences similar to accessible, linear epitopes on the target protein. The sequence match is considered more significant if residues calculated to be important in the scaffold-peptide interaction are present in the target epitope. The crystal structure of the scaffold-peptide complex is then used as a template for creating a model of the scaffold bound to the target epitope. This model can then be used in conjunction with sequence optimization algorithms or directed evolution methods to search for scaffold mutations that further increase affinity for the target protein. To test the applicability of this approach we targeted three disease-causing proteins: a tuberculosis virulence factor (TVF), the apical membrane antigen (AMA) from malaria, and hemagglutinin from influenza. In each case the best scoring scaffold was tested, and binders with Kds equal to 37 μM and 50 nM for TVF and AMA, respectively, were identified. A web server (http://rosettadesign.med.unc.edu/scaffold/) has been created for performing the scaffold search process with user-defined target sequences.

  10. Near-instant surface-selective fluorogenic protein quantification using sulfonated triarylmethane dyes and fluorogen activating proteins.

    PubMed

    Yan, Qi; Schmidt, Brigitte F; Perkins, Lydia A; Naganbabu, Matharishwan; Saurabh, Saumya; Andreko, Susan K; Bruchez, Marcel P

    2015-02-21

    Agonist-promoted G-protein coupled receptor (GPCR) endocytosis and recycling plays an important role in many signaling events in the cell. However, the approaches that allow fast and quantitative analysis of such processes still remain limited. Here we report an improved labeling approach based on the genetic fusion of a fluorogen activating protein (FAP) to a GPCR and binding of a sulfonated analog of the malachite green (MG) fluorogen to rapidly and selectively label cell surface receptors. Fluorescence microscopy and flow cytometry demonstrate that this dye does not cross the plasma membrane, binds with high affinity to a dL5** FAP-GPCR fusion construct, activating tagged surface receptors within seconds of addition. The ability to rapidly and selectively label cell surface receptors with a fluorogenic genetically encoded tag allows quantitative imaging and analysis of highly dynamic processes like receptor endocytosis and recycling. PMID:25520058

  11. An Evaluation of Some Models for Culture-Fair Selection.

    ERIC Educational Resources Information Center

    Petersen, Nancy S.; Novick, Melvin R.

    Models proposed by Cleary, Thorndike, Cole, Linn, Einhorn and Bass, Darlington, and Gross and Su for analyzing bias in the use of tests in a selection strategy are surveyed. Several additional models are also introduced. The purpose is to describe, compare, contrast, and evaluate these models while extracting such useful ideas as may be found in…

  12. A Conditional Logit Model of Collegiate Major Selection.

    ERIC Educational Resources Information Center

    Milley, Donald J.; Bee, Richard H.

    1982-01-01

    Hypothesizes a conditional logit model of decision making to explain collegiate major selection. Results suggest a link between student environment and preference structure and preference structures and student major selection. Suggests findings are limited by use of a largely commuter student population. (KMF)

  13. Augmented Self-Modeling as an Intervention for Selective Mutism

    ERIC Educational Resources Information Center

    Kehle, Thomas J.; Bray, Melissa A.; Byer-Alcorace, Gabriel F.; Theodore, Lea A.; Kovac, Lisa M.

    2012-01-01

    Selective mutism is a rare disorder that is difficult to treat. It is often associated with oppositional defiant behavior, particularly in the home setting, social phobia, and, at times, autism spectrum disorder characteristics. The augmented self-modeling treatment has been relatively successful in promoting rapid diminishment of selective mutism…

  14. A Working Model of Natural Selection Illustrated by Table Tennis

    ERIC Educational Resources Information Center

    Dinc, Muhittin; Kilic, Selda; Aladag, Caner

    2013-01-01

    Natural selection is one of the most important topics in biology and it helps to clarify the variety and complexity of organisms. However, students in almost every stage of education find it difficult to understand the mechanism of natural selection and they can develop misconceptions about it. This article provides an active model of natural…

  15. A Model for Investigating Predictive Validity at Highly Selective Institutions.

    ERIC Educational Resources Information Center

    Gross, Alan L.; And Others

    A statistical model for investigating predictive validity at highly selective institutions is described. When the selection ratio is small, one must typically deal with a data set containing relatively large amounts of missing data on both criterion and predictor variables. Standard statistical approaches are based on the strong assumption that…

  16. Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

    PubMed

    Gupta, Aditi; Adami, Christoph

    2016-03-01

    Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient) condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing environment. PMID

  17. Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

    PubMed

    Gupta, Aditi; Adami, Christoph

    2016-03-01

    Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient) condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing environment.

  18. Elucidating factors important for monovalent cation selectivity in enzymes: E. coli β-galactosidase as a model.

    PubMed

    Wheatley, Robert W; Juers, Douglas H; Lev, Bogdan B; Huber, Reuben E; Noskov, Sergei Yu

    2015-04-28

    Many enzymes require a specific monovalent cation (M(+)), that is either Na(+) or K(+), for optimal activity. While high selectivity M(+) sites in transport proteins have been extensively studied, enzyme M(+) binding sites generally have lower selectivity and are less characterized. Here we study the M(+) binding site of the model enzyme E. coli β-galactosidase, which is about 10 fold selective for Na(+) over K(+). Combining data from X-ray crystallography and computational models, we find the electrostatic environment predominates in defining the Na(+) selectivity. In this lower selectivity site rather subtle influences on the electrostatic environment become significant, including the induced polarization effects of the M(+) on the coordinating ligands and the effect of second coordination shell residues on the charge distribution of the primary ligands. This work expands the knowledge of ion selectivity in proteins to denote novel mechanisms important for the selectivity of M(+) sites in enzymes.

  19. Fluctuating Selection Models and Mcdonald-Kreitman Type Analyses

    PubMed Central

    Gossmann, Toni I.; Waxman, David; Eyre-Walker, Adam

    2014-01-01

    It is likely that the strength of selection acting upon a mutation varies through time due to changes in the environment. However, most population genetic theory assumes that the strength of selection remains constant. Here we investigate the consequences of fluctuating selection pressures on the quantification of adaptive evolution using McDonald-Kreitman (MK) style approaches. In agreement with previous work, we show that fluctuating selection can generate evidence of adaptive evolution even when the expected strength of selection on a mutation is zero. However, we also find that the mutations, which contribute to both polymorphism and divergence tend, on average, to be positively selected during their lifetime, under fluctuating selection models. This is because mutations that fluctuate, by chance, to positive selected values, tend to reach higher frequencies in the population than those that fluctuate towards negative values. Hence the evidence of positive adaptive evolution detected under a fluctuating selection model by MK type approaches is genuine since fixed mutations tend to be advantageous on average during their lifetime. Never-the-less we show that methods tend to underestimate the rate of adaptive evolution when selection fluctuates. PMID:24409303

  20. Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection

    PubMed Central

    Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

    2015-01-01

    Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification. PMID:26339638

  1. Rational design of selective small-molecule inhibitors for β-catenin/B-cell lymphoma 9 protein-protein interactions.

    PubMed

    Hoggard, Logan R; Zhang, Yongqiang; Zhang, Min; Panic, Vanja; Wisniewski, John A; Ji, Haitao

    2015-09-30

    Selective inhibition of α-helix-mediated protein-protein interactions (PPIs) with small organic molecules provides great potential for the discovery of chemical probes and therapeutic agents. Protein Data Bank data mining using the HippDB database indicated that (1) the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix had few orientations when interacting with the second protein and (2) the hot spot pockets of PPI complexes had different sizes, shapes, and chemical groups when interacting with the same hydrophobic projecting hot spots of α-helix. On the basis of these observations, a small organic molecule, 4'-fluoro-N-phenyl-[1,1'-biphenyl]-3-carboxamide, was designed as a generic scaffold that itself directly mimics the binding mode of the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix. Convenient decoration of this generic scaffold led to the selective disruption of α-helix-mediated PPIs. A series of small-molecule inhibitors selective for β-catenin/B-cell lymphoma 9 (BCL9) over β-catenin/cadherin PPIs was designed and synthesized. The binding mode of new inhibitors was characterized by site-directed mutagenesis and structure-activity relationship studies. This new class of inhibitors can selectively disrupt β-catenin/BCL9 over β-catenin/cadherin PPIs, suppress the transactivation of canonical Wnt signaling, downregulate the expression of Wnt target genes, and inhibit the growth of Wnt/β-catenin-dependent cancer cells. PMID:26352795

  2. Ecohydrological model parameter selection for stream health evaluation.

    PubMed

    Woznicki, Sean A; Nejadhashemi, A Pouyan; Ross, Dennis M; Zhang, Zhen; Wang, Lizhu; Esfahanian, Abdol-Hossein

    2015-04-01

    Variable selection is a critical step in development of empirical stream health prediction models. This study develops a framework for selecting important in-stream variables to predict four measures of biological integrity: total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, family index of biotic integrity (FIBI), Hilsenhoff biotic integrity (HBI), and fish index of biotic integrity (IBI). Over 200 flow regime and water quality variables were calculated using the Hydrologic Index Tool (HIT) and Soil and Water Assessment Tool (SWAT). Streams of the River Raisin watershed in Michigan were grouped using the Strahler stream classification system (orders 1-3 and orders 4-6), k-means clustering technique (two clusters: C1 and C2), and all streams (one grouping). For each grouping, variable selection was performed using Bayesian variable selection, principal component analysis, and Spearman's rank correlation. Following selection of best variable sets, models were developed to predict the measures of biological integrity using adaptive-neuro fuzzy inference systems (ANFIS), a technique well-suited to complex, nonlinear ecological problems. Multiple unique variable sets were identified, all which differed by selection method and stream grouping. Final best models were mostly built using the Bayesian variable selection method. The most effective stream grouping method varied by health measure, although k-means clustering and grouping by stream order were always superior to models built without grouping. Commonly selected variables were related to streamflow magnitude, rate of change, and seasonal nitrate concentration. Each best model was effective in simulating stream health observations, with EPT taxa validation R2 ranging from 0.67 to 0.92, FIBI ranging from 0.49 to 0.85, HBI from 0.56 to 0.75, and fish IBI at 0.99 for all best models. The comprehensive variable selection and modeling process proposed here is a robust method that extends our

  3. Ecohydrological model parameter selection for stream health evaluation.

    PubMed

    Woznicki, Sean A; Nejadhashemi, A Pouyan; Ross, Dennis M; Zhang, Zhen; Wang, Lizhu; Esfahanian, Abdol-Hossein

    2015-04-01

    Variable selection is a critical step in development of empirical stream health prediction models. This study develops a framework for selecting important in-stream variables to predict four measures of biological integrity: total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, family index of biotic integrity (FIBI), Hilsenhoff biotic integrity (HBI), and fish index of biotic integrity (IBI). Over 200 flow regime and water quality variables were calculated using the Hydrologic Index Tool (HIT) and Soil and Water Assessment Tool (SWAT). Streams of the River Raisin watershed in Michigan were grouped using the Strahler stream classification system (orders 1-3 and orders 4-6), k-means clustering technique (two clusters: C1 and C2), and all streams (one grouping). For each grouping, variable selection was performed using Bayesian variable selection, principal component analysis, and Spearman's rank correlation. Following selection of best variable sets, models were developed to predict the measures of biological integrity using adaptive-neuro fuzzy inference systems (ANFIS), a technique well-suited to complex, nonlinear ecological problems. Multiple unique variable sets were identified, all which differed by selection method and stream grouping. Final best models were mostly built using the Bayesian variable selection method. The most effective stream grouping method varied by health measure, although k-means clustering and grouping by stream order were always superior to models built without grouping. Commonly selected variables were related to streamflow magnitude, rate of change, and seasonal nitrate concentration. Each best model was effective in simulating stream health observations, with EPT taxa validation R2 ranging from 0.67 to 0.92, FIBI ranging from 0.49 to 0.85, HBI from 0.56 to 0.75, and fish IBI at 0.99 for all best models. The comprehensive variable selection and modeling process proposed here is a robust method that extends our

  4. Chasing Phosphoarginine Proteins: Development of a Selective Enrichment Method Using a Phosphatase Trap*

    PubMed Central

    Trentini, Débora Broch; Fuhrmann, Jakob; Mechtler, Karl; Clausen, Tim

    2014-01-01

    Arginine phosphorylation is an emerging post-translational protein modification implicated in the bacterial stress response. Although early reports suggested that arginine phosphorylation also occurs in higher eukaryotes, its overall prevalence was never studied using modern mass spectrometry methods, owing to technical difficulties arising from the acid lability of phosphoarginine. As shown recently, the McsB and YwlE proteins from Bacillus subtilis function as a highly specific protein arginine kinase and phosphatase couple, shaping the phosphoarginine proteome. Using a B. subtilis ΔywlE strain as a source for arginine-phosphorylated proteins, we were able to adapt mass spectrometry (MS) protocols to the special chemical properties of the arginine modification. Despite this progress, the analysis of protein arginine phosphorylation in eukaryotes is still challenging, given the great abundance of serine/threonine phosphorylations that would compete with phosphoarginine during the phosphopeptide enrichment procedure, as well as during data-dependent MS acquisition. We thus set out to establish a method for the selective enrichment of arginine-phosphorylated proteins as an initial step in the phosphoproteomic analysis. For this purpose, we developed a substrate-trapping mutant of the YwlE phosphatase that retains binding affinity toward arginine-phosphorylated proteins but cannot hydrolyze the captured substrates. By testing a number of active site substitutions, we identified a YwlE mutant (C9A) that stably binds to arginine-phosphorylated proteins. We further improved the substrate-trapping efficiency by impeding the oligomerization of the phosphatase mutant. The engineered YwlE trap efficiently captured arginine-phosphorylated proteins from complex B. subtilis ΔywlE cell extracts, thus facilitating identification of phosphoarginine sites in the large pool of cellular protein modifications. In conclusion, we present a novel tool for the selective enrichment and

  5. Transient fusion and selective secretion of vesicle proteins in Phytophthora nicotianae zoospores

    PubMed Central

    Zhang, Weiwei; Blackman, Leila M.

    2013-01-01

    Secretion of pathogen proteins is crucial for the establishment of disease in animals and plants. Typically, early interactions between host and pathogen trigger regulated secretion of pathogenicity factors that function in pathogen adhesion and host penetration. During the onset of plant infection by spores of the Oomycete, Phytophthora nicotianae, proteins are secreted from three types of cortical vesicles. Following induction of spore encystment, two vesicle types undergo full fusion, releasing their entire contents onto the cell surface. However, the third vesicle type, so-called large peripheral vesicles, selectively secretes a small Sushi domain-containing protein, PnCcp, while retaining a large glycoprotein, PnLpv, before moving away from the plasma membrane. Selective secretion of PnCcp is associated with its compartmentalization within the vesicle periphery. Pharmacological inhibition of dynamin function, purportedly in vesicle fission, by dynasore treatment provides evidence that selective secretion of PnCcp requires transient fusion of the large peripheral vesicles. This is the first report of selective protein secretion via transient fusion outside mammalian cells. Selective secretion is likely to be an important aspect of plant infection by this destructive pathogen. PMID:24392285

  6. Transient fusion and selective secretion of vesicle proteins in Phytophthora nicotianae zoospores.

    PubMed

    Zhang, Weiwei; Blackman, Leila M; Hardham, Adrienne R

    2013-01-01

    Secretion of pathogen proteins is crucial for the establishment of disease in animals and plants. Typically, early interactions between host and pathogen trigger regulated secretion of pathogenicity factors that function in pathogen adhesion and host penetration. During the onset of plant infection by spores of the Oomycete, Phytophthora nicotianae, proteins are secreted from three types of cortical vesicles. Following induction of spore encystment, two vesicle types undergo full fusion, releasing their entire contents onto the cell surface. However, the third vesicle type, so-called large peripheral vesicles, selectively secretes a small Sushi domain-containing protein, PnCcp, while retaining a large glycoprotein, PnLpv, before moving away from the plasma membrane. Selective secretion of PnCcp is associated with its compartmentalization within the vesicle periphery. Pharmacological inhibition of dynamin function, purportedly in vesicle fission, by dynasore treatment provides evidence that selective secretion of PnCcp requires transient fusion of the large peripheral vesicles. This is the first report of selective protein secretion via transient fusion outside mammalian cells. Selective secretion is likely to be an important aspect of plant infection by this destructive pathogen. PMID:24392285

  7. Robust Decision-making Applied to Model Selection

    SciTech Connect

    Hemez, Francois M.

    2012-08-06

    The scientific and engineering communities are relying more and more on numerical models to simulate ever-increasingly complex phenomena. Selecting a model, from among a family of models that meets the simulation requirements, presents a challenge to modern-day analysts. To address this concern, a framework is adopted anchored in info-gap decision theory. The framework proposes to select models by examining the trade-offs between prediction accuracy and sensitivity to epistemic uncertainty. The framework is demonstrated on two structural engineering applications by asking the following question: Which model, of several numerical models, approximates the behavior of a structure when parameters that define each of those models are unknown? One observation is that models that are nominally more accurate are not necessarily more robust, and their accuracy can deteriorate greatly depending upon the assumptions made. It is posited that, as reliance on numerical models increases, establishing robustness will become as important as demonstrating accuracy.

  8. Development, Selection, and Validation of Tumor Growth Models

    NASA Astrophysics Data System (ADS)

    Shahmoradi, Amir; Lima, Ernesto; Oden, J. Tinsley

    In recent years, a multitude of different mathematical approaches have been taken to develop multiscale models of solid tumor growth. Prime successful examples include the lattice-based, agent-based (off-lattice), and phase-field approaches, or a hybrid of these models applied to multiple scales of tumor, from subcellular to tissue level. Of overriding importance is the predictive power of these models, particularly in the presence of uncertainties. This presentation describes our attempt at developing lattice-based, agent-based and phase-field models of tumor growth and assessing their predictive power through new adaptive algorithms for model selection and model validation embodied in the Occam Plausibility Algorithm (OPAL), that brings together model calibration, determination of sensitivities of outputs to parameter variances, and calculation of model plausibilities for model selection. Institute for Computational Engineering and Sciences.

  9. Enzastaurin (LY317615), a Protein Kinase C Beta Selective Inhibitor, Enhances Antiangiogenic Effect of Radiation

    SciTech Connect

    Willey, Christopher D.; Xiao Dakai; Tu Tianxiang; Kim, Kwang Woon; Moretti, Luigi; Niermann, Kenneth J.; Tawtawy, Mohammed N.; Quarles, Chad C. Ph.D.; Lu Bo

    2010-08-01

    Purpose: Angiogenesis has generated interest in oncology because of its important role in cancer growth and progression, particularly when combined with cytotoxic therapies, such as radiotherapy. Among the numerous pathways influencing vascular growth and stability, inhibition of protein kinase B(Akt) or protein kinase C(PKC) can influence tumor blood vessels within tumor microvasculature. Therefore, we wanted to determine whether PKC inhibition could sensitize lung tumors to radiation. Methods and Materials: The combination of the selective PKC{beta} inhibitor Enzastaurin (ENZ, LY317615) and ionizing radiation were used in cell culture and a mouse model of lung cancer. Lung cancer cell lines and human umbilical vascular endothelial cells (HUVEC) were examined using immunoblotting, cytotoxic assays including cell proliferation and clonogenic assays, and Matrigel endothelial tubule formation. In vivo, H460 lung cancer xenografts were examined for tumor vasculature and proliferation using immunohistochemistry. Results: ENZ effectively radiosensitizes HUVEC within in vitro models. Furthermore, concurrent ENZ treatment of lung cancer xenografts enhanced radiation-induced destruction of tumor vasculature and proliferation by IHC. However, tumor growth delay was not enhanced with combination treatment compared with either treatment alone. Analysis of downstream effectors revealed that HUVEC and the lung cancer cell lines differed in their response to ENZ and radiation such that only HUVEC demonstrate phosphorylated S6 suppression, which is downstream of mTOR. When ENZ was combined with the mTOR inhibitor, rapamycin, in H460 lung cancer cells, radiosensitization was observed. Conclusion: PKC appears to be crucial for angiogenesis, and its inhibition by ENZ has potential to enhance radiotherapy in vivo.

  10. Model Organisms in G Protein-Coupled Receptor Research.

    PubMed

    Langenhan, Tobias; Barr, Maureen M; Bruchas, Michael R; Ewer, John; Griffith, Leslie C; Maiellaro, Isabella; Taghert, Paul H; White, Benjamin H; Monk, Kelly R

    2015-09-01

    The study of G protein-coupled receptors (GPCRs) has benefited greatly from experimental approaches that interrogate their functions in controlled, artificial environments. Working in vitro, GPCR receptorologists discovered the basic biologic mechanisms by which GPCRs operate, including their eponymous capacity to couple to G proteins; their molecular makeup, including the famed serpentine transmembrane unit; and ultimately, their three-dimensional structure. Although the insights gained from working outside the native environments of GPCRs have allowed for the collection of low-noise data, such approaches cannot directly address a receptor's native (in vivo) functions. An in vivo approach can complement the rigor of in vitro approaches: as studied in model organisms, it imposes physiologic constraints on receptor action and thus allows investigators to deduce the most salient features of receptor function. Here, we briefly discuss specific examples in which model organisms have successfully contributed to the elucidation of signals controlled through GPCRs and other surface receptor systems. We list recent examples that have served either in the initial discovery of GPCR signaling concepts or in their fuller definition. Furthermore, we selectively highlight experimental advantages, shortcomings, and tools of each model organism. PMID:25979002

  11. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

    PubMed Central

    Mannakee, Brian K.; Gutenkunst, Ryan N.

    2016-01-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

  12. Novel strategy for the selection of human recombinant Fab fragments to membrane proteins from a phage-display library.

    PubMed

    Labrijn, Aran F; Koppelman, Marco H G M; Verhagen, Janneke; Brouwer, Mieke C; Schuitemaker, Hanneke; Hack, C Erik; Huisman, Han G

    2002-03-01

    Traditionally, the selection of phage-display libraries is performed on purified antigens (Ags), immobilized to a solid substrate. However, this approach may not be applicable for some Ags, such as membrane proteins, which for structural integrity strongly rely on their native environment. Here we describe an approach for the selection of phage-libraries against membrane proteins. The envelope glycoproteins (Env) of the Human Immunodeficiency Virus type-1 (HIV-1) were used as a model for a type-1 integral membrane protein. HIV-1IHI Env, expressed on the surface of Rabbit Kidney cells (RK13) with a recombinant vaccinia virus (rVV), was solubilized using the non-ionic detergent n-Octyl beta-D-glucopyranoside (OG). Membrane associated Env was reconstituted into vesicles by the simultaneous removal of detergent and free monomeric Env subunits by gel-filtration. The resulting antigen preparation, termed OG-P1IHI, was captured on microtiter plates coated with Galanthus nivalis agglutinin (GNA) and used for rounds of selection (panning) of a well-characterized phage-display library derived from an HIV-1 seropositive donor. Simultaneously, an identical experiment was performed with OG-P1IHI vesicles disrupted by Nonidet P-40 (NP-P1IHI). Both membrane-associated and soluble Ags were selected for vaccinia-specific clones (OG-P1IHI: 59/75 and NP-P1IHI: 1/75) and HIV-1-specific clones (OG-P1IHI: 11/75 and NP-P1IHI: 65/75) using our approach. Hence, the novel panning strategy described here may be applicable for selection of phage-libraries against membrane proteins.

  13. [Near-infrared spectrum quantitative analysis model based on principal components selected by elastic net].

    PubMed

    Chen, Wan-hui; Liu, Xu-hua; He, Xiong-kui; Min, Shun-geng; Zhang, Lu-da

    2010-11-01

    Elastic net is an improvement of the least-squares method by introducing in L1 and L2 penalties, and it has the advantages of the variable selection. The quantitative analysis model build by Elastic net can improve the prediction accuracy. Using 89 wheat samples as the experiment material, the spectrum principal components of the samples were selected by Elastic net. The analysis model was established for the near-infrared spectrum and the wheat's protein content, and the feasibility of using Elastic net to establish the quantitative analysis model was confirmed. In experiment, the 89 wheat samples were randomly divided into two groups, with 60 samples being the model set and 29 samples being the prediction set. The 60 samples were used to build analysis model to predict the protein contents of the 29 samples, and correlation coefficient (R) of the predicted value and chemistry observed value was 0. 984 9, with the mean relative error being 2.48%. To further investigate the feasibility and stability of the model, the 89 samples were randomly selected five times, with 60 samples to be model set and 29 samples to be prediction set. The five groups of principal components which were selected by Elastic net for building model were basically consistent, and compared with the PCR and PLS method, the model prediction accuracies were all better than PCR and similar with PLS. In view of the fact that Elastic net can realize the variable selection and the model has good prediction, it was shown that Elastic net is suitable method for building chemometrics quantitative analysis model. PMID:21284156

  14. Selected Reaction Monitoring to Measure Proteins of Interest in Complex Samples: A Practical Guide.

    PubMed

    Feng, Yuehan; Picotti, Paola

    2016-01-01

    Biology and especially systems biology projects increasingly require the capability to detect and quantify specific sets of proteins across multiple samples, for example the components of a biological pathway through a set of perturbation-response experiments. Targeted proteomics based on selected reaction monitoring (SRM) has emerged as an ideal tool to this purpose, and complements the discovery capabilities of shotgun proteomics methods. SRM experiments rely on the development of specific, quantitative mass spectrometric assays for each protein of interest and their application to the quantification of the protein set in various biological samples. SRM measurements are multiplexed, namely, multiple proteins can be quantified simultaneously, and are characterized by a high reproducibility and a broad dynamic range. We provide here a practical guide to the development of SRM assays targeting a set of proteins of interest and to their application to complex biological samples.

  15. Site-selective protein-modification chemistry for basic biology and drug development.

    PubMed

    Krall, Nikolaus; da Cruz, Filipa P; Boutureira, Omar; Bernardes, Gonçalo J L

    2016-02-01

    Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

  16. Site-selective protein-modification chemistry for basic biology and drug development

    NASA Astrophysics Data System (ADS)

    Krall, Nikolaus; da Cruz, Filipa P.; Boutureira, Omar; Bernardes, Gonçalo J. L.

    2016-02-01

    Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

  17. A guide to Bayesian model selection for ecologists

    USGS Publications Warehouse

    Hooten, Mevin B.; Hobbs, N.T.

    2015-01-01

    The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

  18. Computer model for selecting flow measuring structures in open channels

    SciTech Connect

    Hickey, M. J.

    1980-01-01

    Quantifying various pollutants in natural waterways has received increased emphasis with more stringent regulations issued by the Environmental Protection Agency (E.P.A.). Measuring natural stream fows presents a magnitude of problems, the most significant is the type of structure needed to measure the flows at the desired level of accuracy. A computer model designed to select a structure to best fit the engineer's needs is under development. This model, given the pertinent boundary conditions, will pinpoint the structure most suitable, if one exists. This selection process greatly facilitates the old selection process of trial and error.

  19. The different roles of selective autophagic protein degradation in mammalian cells

    PubMed Central

    Wang, Da-wei; Peng, Zhen-ju; Ren, Guang-fang; Wang, Guang-xin

    2015-01-01

    Autophagy is an intracellular pathway for bulk protein degradation and the removal of damaged organelles by lysosomes. Autophagy was previously thought to be unselective; however, studies have increasingly confirmed that autophagy-mediated protein degradation is highly regulated. Abnormal autophagic protein degradation has been associated with multiple human diseases such as cancer, neurological disability and cardiovascular disease; therefore, further elucidation of protein degradation by autophagy may be beneficial for protein-based clinical therapies. Macroautophagy and chaperone-mediated autophagy (CMA) can both participate in selective protein degradation in mammalian cells, but the process is quite different in each case. Here, we summarize the various types of macroautophagy and CMA involved in determining protein degradation. For this summary, we divide the autophagic protein degradation pathways into four categories: the post-translational modification dependent and independent CMA pathways and the ubiquitin dependent and independent macroautophagy pathways, and describe how some non-canonical pathways and modifications such as phosphorylation, acetylation and arginylation can influence protein degradation by the autophagy lysosome system (ALS). Finally, we comment on why autophagy can serve as either diagnostics or therapeutic targets in different human diseases. PMID:26415220

  20. Binding of Bacillus thuringiensis proteins to a laboratory-selected line of Heliothis virescens.

    PubMed

    MacIntosh, S C; Stone, T B; Jokerst, R S; Fuchs, R L

    1991-10-15

    A laboratory-selected colony of Heliothis virescens displaying a 20- to 70-fold level of resistance to Bacillus thuringiensis proteins was evaluated to identify mechanism(s) of resistance. Brush-border membrane vesicles were isolated from larval midgut epithelium from the susceptible and resistant strains of H. virescens. Two B. thuringiensis proteins, CryIA(b) and CryIA(c), were iodinated and shown to specifically bind to brush-border membrane vesicles of both insect strains. Multiple changes in the receptor-binding parameters were seen in the resistant strain as compared with the susceptible strain. A 2- to 4-fold reduction in binding affinity was accompanied by a 4- to 6-fold increase in binding-site concentration for both proteins. Although these two B. thuringiensis proteins competed for the same high-affinity binding site, competition experiments revealed different receptor specificity toward these proteins in the resistant H. virescens line. The H. virescens strains were not sensitive to a coleopteran-active protein, CryIIIA, nor did these proteins compete with the CryIA proteins for binding. Complexity of the mechanism of resistance is consistent with the complex mode of action of B. thuringiensis proteins. PMID:1924353

  1. Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein

    PubMed Central

    Gupta, Aditi; Adami, Christoph

    2016-01-01

    Epistatic interactions between residues determine a protein’s adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient) condition that detects epistasis in most cases. We analyze the “fossils” of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing environment. PMID

  2. Performance-based selection of likelihood models for phylogeny estimation.

    PubMed

    Minin, Vladimir; Abdo, Zaid; Joyce, Paul; Sullivan, Jack

    2003-10-01

    Phylogenetic estimation has largely come to rely on explicitly model-based methods. This approach requires that a model be chosen and that that choice be justified. To date, justification has largely been accomplished through use of likelihood-ratio tests (LRTs) to assess the relative fit of a nested series of reversible models. While this approach certainly represents an important advance over arbitrary model selection, the best fit of a series of models may not always provide the most reliable phylogenetic estimates for finite real data sets, where all available models are surely incorrect. Here, we develop a novel approach to model selection, which is based on the Bayesian information criterion, but incorporates relative branch-length error as a performance measure in a decision theory (DT) framework. This DT method includes a penalty for overfitting, is applicable prior to running extensive analyses, and simultaneously compares all models being considered and thus does not rely on a series of pairwise comparisons of models to traverse model space. We evaluate this method by examining four real data sets and by using those data sets to define simulation conditions. In the real data sets, the DT method selects the same or simpler models than conventional LRTs. In order to lend generality to the simulations, codon-based models (with parameters estimated from the real data sets) were used to generate simulated data sets, which are therefore more complex than any of the models we evaluate. On average, the DT method selects models that are simpler than those chosen by conventional LRTs. Nevertheless, these simpler models provide estimates of branch lengths that are more accurate both in terms of relative error and absolute error than those derived using the more complex (yet still wrong) models chosen by conventional LRTs. This method is available in a program called DT-ModSel. PMID:14530134

  3. Applying Four Different Risk Models in Local Ore Selection

    SciTech Connect

    Richmond, Andrew

    2002-12-15

    Given the uncertainty in grade at a mine location, a financially risk-averse decision-maker may prefer to incorporate this uncertainty into the ore selection process. A FORTRAN program risksel is presented to calculate local risk-adjusted optimal ore selections using a negative exponential utility function and three dominance models: mean-variance, mean-downside risk, and stochastic dominance. All four methods are demonstrated in a grade control environment. In the case study, optimal selections range with the magnitude of financial risk that a decision-maker is prepared to accept. Except for the stochastic dominance method, the risk models reassign material from higher cost to lower cost processing options as the aversion to financial risk increases. The stochastic dominance model usually was unable to determine the optimal local selection.

  4. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.

    PubMed

    An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Chen, Xing; Yan, Gui-Ying; Hu, Ji-Pu

    2016-10-01

    Predicting protein-protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high-throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherently high false positive rates. For these reasons, many computational methods have been proposed for predicting PPIs. However, the problem is still far from being solved. In this article, we propose a novel computational method called RVM-BiGP that combines the relevance vector machine (RVM) model and Bi-gram Probabilities (BiGP) for PPIs detection from protein sequences. The major improvement includes (1) Protein sequences are represented using the Bi-gram probabilities (BiGP) feature representation on a Position Specific Scoring Matrix (PSSM), in which the protein evolutionary information is contained; (2) For reducing the influence of noise, the Principal Component Analysis (PCA) method is used to reduce the dimension of BiGP vector; (3) The powerful and robust Relevance Vector Machine (RVM) algorithm is used for classification. Five-fold cross-validation experiments executed on yeast and Helicobacter pylori datasets, which achieved very high accuracies of 94.57 and 90.57%, respectively. Experimental results are significantly better than previous methods. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-BiGP method is significantly better than the SVM-based method. In addition, we achieved 97.15% accuracy on imbalance yeast dataset, which is higher than that of balance yeast dataset. The promising experimental results show the efficiency and robust of the proposed method, which can be an automatic decision support tool for future

  5. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.

    PubMed

    An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Chen, Xing; Yan, Gui-Ying; Hu, Ji-Pu

    2016-10-01

    Predicting protein-protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high-throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherently high false positive rates. For these reasons, many computational methods have been proposed for predicting PPIs. However, the problem is still far from being solved. In this article, we propose a novel computational method called RVM-BiGP that combines the relevance vector machine (RVM) model and Bi-gram Probabilities (BiGP) for PPIs detection from protein sequences. The major improvement includes (1) Protein sequences are represented using the Bi-gram probabilities (BiGP) feature representation on a Position Specific Scoring Matrix (PSSM), in which the protein evolutionary information is contained; (2) For reducing the influence of noise, the Principal Component Analysis (PCA) method is used to reduce the dimension of BiGP vector; (3) The powerful and robust Relevance Vector Machine (RVM) algorithm is used for classification. Five-fold cross-validation experiments executed on yeast and Helicobacter pylori datasets, which achieved very high accuracies of 94.57 and 90.57%, respectively. Experimental results are significantly better than previous methods. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-BiGP method is significantly better than the SVM-based method. In addition, we achieved 97.15% accuracy on imbalance yeast dataset, which is higher than that of balance yeast dataset. The promising experimental results show the efficiency and robust of the proposed method, which can be an automatic decision support tool for future

  6. Modeling Protein Aggregate Assembly and Structure

    NASA Astrophysics Data System (ADS)

    Guo, Jun-tao; Hall, Carol K.; Xu, Ying; Wetzel, Ronald

    One might say that "protein science" got its start in the domestic arts, built around the abilities of proteins to aggregate in response to environmental stresses such as heating (boiled eggs), heating and cooling (gelatin), and pH (cheese). Characterization of proteins in the late nineteenth century likewise focused on the ability of proteins to precipitate in response to certain salts and to aggregate in response to heating. Investigations by Chick and Martin (Chick and Martin, 1910) showed that the inactivating response of proteins to heat or solvent treatment is a two-step process involving separate denaturation and precipitation steps. Monitoring the coagulation and flocculation responses of proteins to heat and other stresses remained a major approach to understanding protein structure for decades, with solubility, or susceptibility to aggregation, serving as a kind of benchmark against which results of other methods, such as viscosity, chemical susceptibility, immune activity, crystallizability, and susceptibility to proteolysis, were compared (Mirsky and Pauling, 1936;Wu, 1931). Toward the middle of the last century, protein aggregation studies were largely left behind, as improved methods allowed elucidation of the primary sequence of proteins, reversible unfolding studies, and ultimately high-resolution structures. Curiously, the field of protein science, and in particular protein folding, is now gravitating back to a closer look at protein aggregation and protein aggregates. Unfortunately, the means developed during the second half of the twentieth century for studying native, globular proteins have not proved immediately amenable to the study of aggregate structures. Great progress is being made, however, to modify classical methods, including NMR and X-ray diffraction, as well as to develop newer techniques, that together should continue to expand our picture of aggregate structure (Kheterpal and Wetzel, 2006; Wetzel, 1999).

  7. Multicriteria framework for selecting a process modelling language

    NASA Astrophysics Data System (ADS)

    Scanavachi Moreira Campos, Ana Carolina; Teixeira de Almeida, Adiel

    2016-01-01

    The choice of process modelling language can affect business process management (BPM) since each modelling language shows different features of a given process and may limit the ways in which a process can be described and analysed. However, choosing the appropriate modelling language for process modelling has become a difficult task because of the availability of a large number modelling languages and also due to the lack of guidelines on evaluating, and comparing languages so as to assist in selecting the most appropriate one. This paper proposes a framework for selecting a modelling language in accordance with the purposes of modelling. This framework is based on the semiotic quality framework (SEQUAL) for evaluating process modelling languages and a multicriteria decision aid (MCDA) approach in order to select the most appropriate language for BPM. This study does not attempt to set out new forms of assessment and evaluation criteria, but does attempt to demonstrate how two existing approaches can be combined so as to solve the problem of selection of modelling language. The framework is described in this paper and then demonstrated by means of an example. Finally, the advantages and disadvantages of using SEQUAL and MCDA in an integrated manner are discussed.

  8. Modeling Proteins at the Interface of Structure, Evolution, and Population Genetics

    NASA Astrophysics Data System (ADS)

    Teufel, Ashley I.; Grahnen, Johan A.; Liberles, David A.

    Biological systems span multiple layers of organization and modeling across layers of organization enables inference that is not possible by analyzing just one layer. An example of this is seen in an organism's fitness, which can be directly impacted by selection for output from a metabolic or signal transduction pathway. Even this complex process is already several layers removed from the environment and ecosystem. Within the pathway are individual enzymatic reactions and protein-protein, protein-small molecule, and protein-DNA interactions. Enzymatic and physical constants characterize these reactions and interactions, where selection dictates ranges and thresholds of values that are dependent upon values for other links in the pathway. The physical constants (for protein-protein binding, for example) are dictated by the amino acid sequences at the interface. These constants are also constrained by the amino acid sequences that are necessary to maintain a properly folded structure as a scaffold to maintain the interaction interface. As sequences evolve, population genetic and molecular evolutionary models describe the availability of combinations of amino acid changes for selection, depending in turn on parameters like the mutation rate and effective population size. As the systems biology level of constraints has not been thoroughly characterized, it is this multiscale modeling problem that describes the interplay between protein biophysical chemistry and population genetics/molecular evolution that we will describe.

  9. Bioinorganic Chemical Modeling of Dioxygen-Activating Copper Proteins.

    ERIC Educational Resources Information Center

    Karlin, Kenneth D.; Gultneh, Yilma

    1985-01-01

    Discusses studies done in modeling the copper centers in the proteins hemocyanin (a dioxygen carrier), tyrosinase, and dopamine beta-hydroxylase. Copper proteins, model approach in copper bioinorganic chemistry, characterization of reversible oxygen carriers and dioxygen-metal complexes, a copper mono-oxygenase model reaction, and other topics are…

  10. Tactile Teaching: Exploring Protein Structure/Function Using Physical Models

    ERIC Educational Resources Information Center

    Herman, Tim; Morris, Jennifer; Colton, Shannon; Batiza, Ann; Patrick, Michael; Franzen, Margaret; Goodsell, David S.

    2006-01-01

    The technology now exists to construct physical models of proteins based on atomic coordinates of solved structures. We review here our recent experiences in using physical models to teach concepts of protein structure and function at both the high school and the undergraduate levels. At the high school level, physical models are used in a…

  11. A protein engineered to bind uranyl selectively and with femtomolar affinity

    NASA Astrophysics Data System (ADS)

    Zhou, Lu; Bosscher, Mike; Zhang, Changsheng; Özçubukçu, Salih; Zhang, Liang; Zhang, Wen; Li, Charles J.; Liu, Jianzhao; Jensen, Mark P.; Lai, Luhua; He, Chuan

    2014-03-01

    Uranyl (UO22+), the predominant aerobic form of uranium, is present in the ocean at a concentration of ~3.2 parts per 109 (13.7 nM) however, the successful enrichment of uranyl from this vast resource has been limited by the high concentrations of metal ions of similar size and charge, which makes it difficult to design a binding motif that is selective for uranyl. Here we report the design and rational development of a uranyl-binding protein using a computational screening process in the initial search for potential uranyl-binding sites. The engineered protein is thermally stable and offers very high affinity and selectivity for uranyl with a Kd of 7.4 femtomolar (fM) and >10,000-fold selectivity over other metal ions. We also demonstrated that the uranyl-binding protein can repeatedly sequester 30-60% of the uranyl in synthetic sea water. The chemical strategy employed here may be applied to engineer other selective metal-binding proteins for biotechnology and remediation applications.

  12. Self-Assembly of Protein Nanofibrils Orchestrates Calcite Step Movement through Selective Nonchiral Interactions.

    PubMed

    So, Christopher R; Liu, Jinny; Fears, Kenan P; Leary, Dagmar H; Golden, Joel P; Wahl, Kathryn J

    2015-06-23

    The recognition of atomically distinct surface features by adsorbed biomolecules is central to the formation of surface-templated peptide or protein nanostructures. On mineral surfaces such as calcite, biomolecular recognition of, and self-assembly on, distinct atomic kinks and steps could additionally orchestrate changes to the overall shape and symmetry of a bulk crystal. In this work, we show through in situ atomic force microscopy (AFM) experiments that an acidic 20 kDa cement protein from the barnacle Megabalanus rosa (MRCP20) binds specifically to step edge atoms on {101̅4} calcite surfaces, remains bound and further assembles over time to form one-dimensional nanofibrils. Protein nanofibrils are continuous and organized at the nanoscale, exhibiting striations with a period of ca. 45 nm. These fibrils, templated by surface steps of a preferred geometry, in turn selectively dissolve underlying calcite features displaying the same atomic arrangement. To demonstrate this, we expose the protein solution to bare and fibril-associated rhombohedral etch pits to reveal that nanofibrils accelerate only the movement of fibril-forming steps when compared to undecorated steps exposed to the same solution conditions. Calcite mineralized in the presence of MRCP20 results in asymmetric crystals defined by frustrated faces with shared mirror symmetry, suggesting a similar step-selective behavior by MRCP20 in crystal growth. As shown here, selective surface interactions with step edge atoms lead to a cooperative regime of calcite modification, where templated long-range protein nanostructures shape crystals.

  13. "Smart" molecularly imprinted monoliths for the selective capture and easy release of proteins.

    PubMed

    Wen, Liyin; Tan, Xinyi; Sun, Qi; Svec, Frantisek; Lv, Yongqin

    2016-08-01

    A new thermally switchable molecularly imprinted monolith for the selective capture and release of proteins has been designed. First, a generic poly(glycidyl methacrylate-co-ethylene dimethacrylate) monolith reacted with ethylenediamine followed by functionalization with 2-bromoisobutyryl bromide to introduce the initiator for atom transfer radical polymerization. Subsequently, a protein-imprinted poly(N-isopropylacrylamide) layer was grafted onto the surface of the monolithic matrix by atom transfer radical polymerization. Scanning electron microscopy and energy-dispersive X-ray spectroscopy of the cross-sections of imprinted monoliths confirmed the formation of dense poly(N-isopropylacrylamide) brushes on the pore surface. The imprinted monolith exhibited high specificity and selectivity toward its template protein myoglobin over competing proteins and a remarkably large maximum adsorption capacity of 1641 mg/g. Moreover, this "smart" imprinted monolith featured thermally responsive characteristics that enabled selective capture and easy release of proteins triggered only by change in temperature with water as the mobile phase and avoided use of stronger organic solvents or change in ionic strength and pH. PMID:27352958

  14. Self-Assembly of Protein Nanofibrils Orchestrates Calcite Step Movement through Selective Nonchiral Interactions.

    PubMed

    So, Christopher R; Liu, Jinny; Fears, Kenan P; Leary, Dagmar H; Golden, Joel P; Wahl, Kathryn J

    2015-06-23

    The recognition of atomically distinct surface features by adsorbed biomolecules is central to the formation of surface-templated peptide or protein nanostructures. On mineral surfaces such as calcite, biomolecular recognition of, and self-assembly on, distinct atomic kinks and steps could additionally orchestrate changes to the overall shape and symmetry of a bulk crystal. In this work, we show through in situ atomic force microscopy (AFM) experiments that an acidic 20 kDa cement protein from the barnacle Megabalanus rosa (MRCP20) binds specifically to step edge atoms on {101̅4} calcite surfaces, remains bound and further assembles over time to form one-dimensional nanofibrils. Protein nanofibrils are continuous and organized at the nanoscale, exhibiting striations with a period of ca. 45 nm. These fibrils, templated by surface steps of a preferred geometry, in turn selectively dissolve underlying calcite features displaying the same atomic arrangement. To demonstrate this, we expose the protein solution to bare and fibril-associated rhombohedral etch pits to reveal that nanofibrils accelerate only the movement of fibril-forming steps when compared to undecorated steps exposed to the same solution conditions. Calcite mineralized in the presence of MRCP20 results in asymmetric crystals defined by frustrated faces with shared mirror symmetry, suggesting a similar step-selective behavior by MRCP20 in crystal growth. As shown here, selective surface interactions with step edge atoms lead to a cooperative regime of calcite modification, where templated long-range protein nanostructures shape crystals. PMID:25970003

  15. Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

    PubMed

    Karkov, Hanne Sophie; Krogh, Berit Olsen; Woo, James; Parimal, Siddharth; Ahmadian, Haleh; Cramer, Steven M

    2015-11-01

    In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules.

  16. Selective Ligand Recognition by a Diversity-Generating Retroelement Variable Protein

    PubMed Central

    Miller, Jason L; Coq, Johanne Le; Hodes, Asher; Barbalat, Roman; Miller, Jeff F; Ghosh, Partho

    2008-01-01

    Diversity-generating retroelements (DGRs) recognize novel ligands through massive protein sequence variation, a property shared uniquely with the adaptive immune response. Little is known about how recognition is achieved by DGR variable proteins. Here, we present the structure of the Bordetella bacteriophage DGR variable protein major tropism determinant (Mtd) bound to the receptor pertactin, revealing remarkable adaptability in the static binding sites of Mtd. Despite large dissimilarities in ligand binding mode, principles underlying selective recognition were strikingly conserved between Mtd and immunoreceptors. Central to this was the differential amplification of binding strengths by avidity (i.e., multivalency), which not only relaxed the demand for optimal complementarity between Mtd and pertactin but also enhanced distinctions among binding events to provide selectivity. A quantitatively similar balance between complementarity and avidity was observed for Bordetella bacteriophage DGR as occurs in the immune system, suggesting that variable repertoires operate under a narrow set of conditions to recognize novel ligands. PMID:18532877

  17. Selective ligand recognition by a diversity-generating retroelement variable protein.

    PubMed

    Miller, Jason L; Le Coq, Johanne; Hodes, Asher; Barbalat, Roman; Miller, Jeff F; Ghosh, Partho

    2008-06-01

    Diversity-generating retroelements (DGRs) recognize novel ligands through massive protein sequence variation, a property shared uniquely with the adaptive immune response. Little is known about how recognition is achieved by DGR variable proteins. Here, we present the structure of the Bordetella bacteriophage DGR variable protein major tropism determinant (Mtd) bound to the receptor pertactin, revealing remarkable adaptability in the static binding sites of Mtd. Despite large dissimilarities in ligand binding mode, principles underlying selective recognition were strikingly conserved between Mtd and immunoreceptors. Central to this was the differential amplification of binding strengths by avidity (i.e., multivalency), which not only relaxed the demand for optimal complementarity between Mtd and pertactin but also enhanced distinctions among binding events to provide selectivity. A quantitatively similar balance between complementarity and avidity was observed for Bordetella bacteriophage DGR as occurs in the immune system, suggesting that variable repertoires operate under a narrow set of conditions to recognize novel ligands.

  18. Thymocyte selection is regulated by the helix-loop-helix inhibitor protein, Id3.

    PubMed

    Rivera, R R; Johns, C P; Quan, J; Johnson, R S; Murre, C

    2000-01-01

    E2A, HEB, E2-2, and daughterless are basic helix-loop-helix (bHLH) proteins that play key roles in multiple developmental pathways. The DNA binding activity of E2A, HEB, and E2-2 is regulated by a distinct class of inhibitor HLH proteins, the Id gene products. Here, we show that Id3 is required for major histocompatability (MHC) class I- and class II-restricted thymocyte positive selection. Additionally, H-Y TCR-mediated negative selection is severely perturbed in Id3 null mutant mice. Finally, we show that E2A and Id3 interact genetically to regulate thymocyte development. These observations identify the HLH inhibitory protein Id3 as an essential component required for proper thymocyte maturation.

  19. BeEP Server: using evolutionary information for quality assessment of protein structure models

    PubMed Central

    Palopoli, Nicolas; Lanzarotti, Esteban; Parisi, Gustavo

    2013-01-01

    The BeEP Server (http://www.embnet.qb.fcen.uba.ar/embnet/beep.php) is an online resource aimed to help in the endgame of protein structure prediction. It is able to rank submitted structural models of a protein through an explicit use of evolutionary information, a criterion differing from structural or energetic considerations commonly used in other assessment programs. The idea behind BeEP (Best Evolutionary Pattern) is to benefit from the substitution pattern derived from structural constraints present in a set of homologous proteins adopting a given protein conformation. The BeEP method uses a model of protein evolution that takes into account the structure of a protein to build site-specific substitution matrices. The suitability of these substitution matrices is assessed through maximum likelihood calculations from which position-specific and global scores can be derived. These scores estimate how well the structural constraints derived from each structural model are represented in a sequence alignment of homologous proteins. Our assessment on a subset of proteins from the Critical Assessment of techniques for protein Structure Prediction (CASP) experiment has shown that BeEP is capable of discriminating the models and selecting one or more native-like structures. Moreover, BeEP is not explicitly parameterized to find structural similarities between models and given targets, potentially helping to explore the conformational ensemble of the native state. PMID:23729471

  20. BeEP Server: Using evolutionary information for quality assessment of protein structure models.

    PubMed

    Palopoli, Nicolas; Lanzarotti, Esteban; Parisi, Gustavo

    2013-07-01

    The BeEP Server (http://www.embnet.qb.fcen.uba.ar/embnet/beep.php) is an online resource aimed to help in the endgame of protein structure prediction. It is able to rank submitted structural models of a protein through an explicit use of evolutionary information, a criterion differing from structural or energetic considerations commonly used in other assessment programs. The idea behind BeEP (Best Evolutionary Pattern) is to benefit from the substitution pattern derived from structural constraints present in a set of homologous proteins adopting a given protein conformation. The BeEP method uses a model of protein evolution that takes into account the structure of a protein to build site-specific substitution matrices. The suitability of these substitution matrices is assessed through maximum likelihood calculations from which position-specific and global scores can be derived. These scores estimate how well the structural constraints derived from each structural model are represented in a sequence alignment of homologous proteins. Our assessment on a subset of proteins from the Critical Assessment of techniques for protein Structure Prediction (CASP) experiment has shown that BeEP is capable of discriminating the models and selecting one or more native-like structures. Moreover, BeEP is not explicitly parameterized to find structural similarities between models and given targets, potentially helping to explore the conformational ensemble of the native state.

  1. Optimal experiment design for model selection in biochemical networks

    PubMed Central

    2014-01-01

    Background Mathematical modeling is often used to formalize hypotheses on how a biochemical network operates by discriminating between competing models. Bayesian model selection offers a way to determine the amount of evidence that data provides to support one model over the other while favoring simple models. In practice, the amount of experimental data is often insufficient to make a clear distinction between competing models. Often one would like to perform a new experiment which would discriminate between competing hypotheses. Results We developed a novel method to perform Optimal Experiment Design to predict which experiments would most effectively allow model selection. A Bayesian approach is applied to infer model parameter distributions. These distributions are sampled and used to simulate from multivariate predictive densities. The method is based on a k-Nearest Neighbor estimate of the Jensen Shannon divergence between the multivariate predictive densities of competing models. Conclusions We show that the method successfully uses predictive differences to enable model selection by applying it to several test cases. Because the design criterion is based on predictive distributions, which can be computed for a wide range of model quantities, the approach is very flexible. The method reveals specific combinations of experiments which improve discriminability even in cases where data is scarce. The proposed approach can be used in conjunction with existing Bayesian methodologies where (approximate) posteriors have been determined, making use of relations that exist within the inferred posteriors. PMID:24555498

  2. Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors.

    PubMed

    Bharatham, Kavitha; Bharatham, Nagakumar; Lee, Keun Woo

    2007-05-01

    A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 microM, was selected as a training set. Hypol, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypol) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypol performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypol model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.

  3. Skeleton-based shape analysis of protein models.

    PubMed

    Li, Zhong; Qin, Shengwei; Yu, Zeyun; Jin, Yao

    2014-09-01

    In order to compare the similarity between two protein models, a shape analysis algorithm based on skeleton extraction is presented in this paper. It firstly extracts the skeleton of a given protein surface by an improved Multi-resolution Reeb Graph (MRG) method. A number of points on the model surface are then collected to compute the local diameter (LD) according to the skeleton. Finally the LD frequency is calculated to build up the line chart, which is employed to analyze the shape similarity between protein models. Experimental results show that the similarity comparison using the proposed shape descriptor is more accurate especially for protein models with large deformations.

  4. Signal Peptide-Binding Drug as a Selective Inhibitor of Co-Translational Protein Translocation

    PubMed Central

    Vermeire, Kurt; Bell, Thomas W.; Van Puyenbroeck, Victor; Giraut, Anne; Noppen, Sam; Liekens, Sandra; Schols, Dominique; Hartmann, Enno

    2014-01-01

    In eukaryotic cells, surface expression of most type I transmembrane proteins requires translation and simultaneous insertion of the precursor protein into the endoplasmic reticulum (ER) membrane for subsequent routing to the cell surface. This co-translational translocation pathway is initiated when a hydrophobic N-terminal signal peptide (SP) on the nascent protein emerges from the ribosome, binds the cytosolic signal recognition particle (SRP), and targets the ribosome-nascent chain complex to the Sec61 translocon, a universally conserved protein-conducting channel in the ER-membrane. Despite their common function in Sec61 targeting and ER translocation, SPs have diverse but unique primary sequences. Thus, drugs that recognise SPs could be exploited to inhibit translocation of specific proteins into the ER. Here, through flow cytometric analysis the small-molecule macrocycle cyclotriazadisulfonamide (CADA) is identified as a highly selective human CD4 (hCD4) down-modulator. We show that CADA inhibits CD4 biogenesis and that this is due to its ability to inhibit co-translational translocation of CD4 into the lumen of the ER, both in cells as in a cell-free in vitro translation/translocation system. The activity of CADA maps to the cleavable N-terminal SP of hCD4. Moreover, through surface plasmon resonance analysis we were able to show direct binding of CADA to the SP of hCD4 and identify this SP as the target of our drug. Furthermore, CADA locks the SP in the translocon during a post-targeting step, possibly in a folded state, and prevents the translocation of the associated protein into the ER lumen. Instead, the precursor protein is routed to the cytosol for degradation. These findings demonstrate that a synthetic, cell-permeable small-molecule can be developed as a SP-binding drug to selectively inhibit protein translocation and to reversibly regulate the expression of specific target proteins. PMID:25460167

  5. Multilabel learning via random label selection for protein subcellular multilocations prediction.

    PubMed

    Wang, Xiao; Li, Guo-Zheng

    2013-01-01

    Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multilocation proteins to multiple proteins with single location, which does not take correlations among different subcellular locations into account. In this paper, a novel method named random label selection (RALS) (multilabel learning via RALS), which extends the simple binary relevance (BR) method, is proposed to learn from multilocation proteins in an effective and efficient way. RALS does not explicitly find the correlations among labels, but rather implicitly attempts to learn the label correlations from data by augmenting original feature space with randomly selected labels as its additional input features. Through the fivefold cross-validation test on a benchmark data set, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark data sets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multilocations of proteins. The prediction web server is available at >http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage. PMID:23929867

  6. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    PubMed

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-01-01

    Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks using disease-related selected genes has garnered much attention. Support vector machines (SVMs) are commonly used to classify patients, and a number of useful tools such as lasso, elastic net, SCAD, or other regularization methods can be combined with SVM models to select genes that are related to a disease. In the current study, we propose a new Net-SVM model that is different from other SVM models as it is combined with L1/2-norm regularization, which has good performance with high-dimensional and low-sample size microarray data for cancer classification, gene selection, and PPI network construction. Both simulation studies and real data experiments demonstrated that our proposed method outperformed other regularization methods such as lasso, SCAD, and elastic net. In conclusion, our model may help to select fewer but more relevant genes, and can be used to construct simple and informative PPI networks that are highly relevant to cancer. PMID:27525863

  7. Towards a Model Selection Rule for Quantum State Tomography

    NASA Astrophysics Data System (ADS)

    Scholten, Travis; Blume-Kohout, Robin

    Quantum tomography on large and/or complex systems will rely heavily on model selection techniques, which permit on-the-fly selection of small efficient statistical models (e.g. small Hilbert spaces) that accurately fit the data. Many model selection tools, such as hypothesis testing or Akaike's AIC, rely implicitly or explicitly on the Wilks Theorem, which predicts the behavior of the loglikelihood ratio statistic (LLRS) used to choose between models. We used Monte Carlo simulations to study the behavior of the LLRS in quantum state tomography, and found that it disagrees dramatically with Wilks' prediction. We propose a simple explanation for this behavior; namely, that boundaries (in state space and between models) play a significant role in determining the distribution of the LLRS. The resulting distribution is very complex, depending strongly both on the true state and the nature of the data. We consider a simplified model that neglects anistropy in the Fisher information, derive an almost analytic prediction for the mean value of the LLRS, and compare it to numerical experiments. While our simplified model outperforms the Wilks Theorem, it still does not predict the LLRS accurately, implying that alternative methods may be necessary for tomographic model selection. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE.

  8. Selective and programmed cleavage of GPI-anchored proteins from the surface membrane by phospholipase C.

    PubMed

    Müller, Alexandra; Klöppel, Christine; Smith-Valentine, Megan; Van Houten, Judith; Simon, Martin

    2012-01-01

    Many surface proteins of eukaryotic cells are tethered to the membrane by a GPI-anchor which is enzymatically cleavable. Here, we investigate cleavage and release of different GPI-proteins by phospholipase C from the outer membrane of the ciliate Paramecium tetraurelia. Our data indicate that different GPI-proteins are not equally cleaved as proteins of the surface antigen family are preferentially released in vitro compared to several smaller GPI-proteins. Likewise, the analysis of culture medium indicates exclusive in vivo release of surface antigens by two phospholipase C isoforms (PLC2 and PLC6). This suggests that phospholipase C shows affinity for select groups of GPI-anchored proteins. Our data also reveal an up-regulation of PLC isoforms in GPI-anchored protein cleavage during antigenic switching. As a consequence, silencing of these PLCs leads to a drastic decrease of antigen concentration in the medium. These results suggest a higher order of GPI-regulation by phospholipase C as cleavage occurs programmed and specific for single GPI-proteins instead of an unspecific shedding of the entire surface membrane GPI-content.

  9. Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis.

    PubMed

    Ding, Hui; Feng, Peng-Mian; Chen, Wei; Lin, Hao

    2014-08-01

    The bacteriophage virion proteins play extremely important roles in the fate of host bacterial cells. Accurate identification of bacteriophage virion proteins is very important for understanding their functions and clarifying the lysis mechanism of bacterial cells. In this study, a new sequence-based method was developed to identify phage virion proteins. In the new method, the protein sequences were initially formulated by the g-gap dipeptide compositions. Subsequently, the analysis of variance (ANOVA) with incremental feature selection (IFS) was used to search for the optimal feature set. It was observed that, in jackknife cross-validation, the optimal feature set including 160 optimized features can produce the maximum accuracy of 85.02%. By performing feature analysis, we found that the correlation between two amino acids with one gap was more important than other correlations for phage virion protein prediction and that some of the 1-gap dipeptides were important and mainly contributed to the virion protein prediction. This analysis will provide novel insights into the function of phage virion proteins. On the basis of the proposed method, an online web-server, PVPred, was established and can be freely accessed from the website (http://lin.uestc.edu.cn/server/PVPred). We believe that the PVPred will become a powerful tool to study phage virion proteins and to guide the related experimental validations.

  10. Clusters for biology: immobilization of proteins by size-selected metal clusters

    NASA Astrophysics Data System (ADS)

    Collins, J. A.; Xirouchaki, C.; Palmer, R. E.; Heath, J. K.; Jones, C. H.

    2004-03-01

    Lateral features of size 1-10 nm are created on graphite, using an RF magnetron gas-condensation cluster beam deposition source. Specifically, size-selected gold clusters, Au55+ and Au70+, are pinned to the graphite surface, in order to explore the immobilization of protein molecules. Refined sample preparation protocols enable the utilization of the atomic force microscope (AFM) to visualize two proteins, histidine affinity tagged green fluorescent protein (pHAT-GFP) and Human Oncostatin M, both in air, and in physiological buffer solution, which mimics their natural environment. Both protein islands (complexes) and individual (or a few) protein molecules are identified. The impetus for single molecule science studies lies in the possible observation of the structural conformation changes of proteins as they perform their individual functions in their native environments. The manner in which specific proteins organize themselves spatially is a key consideration in understanding how they function, e.g., in disease control. The cluster approach creates sufficiently dilute arrays of truly nanoscale features that single molecule optical experiments may also be feasible in the future. Experiments on the re-usability of the nanocluster films provide further proof of the resilience and versatility of this type of nanostructured surface for protein immobilization work.

  11. Interferon-. alpha. selectively activates the. beta. isoform of protein kinase C through phosphatidylcholine hydrolysis

    SciTech Connect

    Pfeffer, L.M.; Saltiel, A.R. ); Strulovici, B. )

    1990-09-01

    The early events that occur after interferon binds to discrete cell surface receptors remain largely unknown. Human leukocyte interferon (interferon-{alpha}) rapidly increases the binding of ({sup 3}H)phorbol dibutyrate to intact HeLa cells a measure of protein kinase C activation, and induces the selective translocation of the {beta} isoform of protein kinase C from the cytosol to the particulate fraction of HeLa cells. The subcellular distribution of the {alpha} and {epsilon} isoforms is unaffected by interferon-{alpha} treatment. Activation of protein kinase C by phorbol esters mimics the inhibitory action of interferon-{alpha} on HeLa cell proliferation and down-regulation of protein kinase C blocks the induction of antiviral activity by interferon-{alpha} in HeLa cells. Increased phosphatidylcholine hydrolysis and phosphorylcholine production is accompanied by diacylglycerol production in response to interferon. However, inositol phospholipid turnover and free intracellular calcium concentration are unaffected. These results suggest that the transient increase in diacylglycerol, resulting from phosphatidylcholine hydrolysis, may selectively activate the {beta} isoform of protein kinase C. Moreover, the activation of protein kinase C is a necessary element in interferon action on cells.

  12. Ensemble-based evaluation for protein structure models

    PubMed Central

    Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

    2016-01-01

    Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation: https://bitbucket.org/mjamroz/flexscore Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307633

  13. Structural Basis for Receptor Activity-Modifying Protein-Dependent Selective Peptide Recognition by a G Protein-Coupled Receptor

    PubMed Central

    Booe, Jason M.; Walker, Christopher S.; Barwell, James; Kuteyi, Gabriel; Simms, John; Jamaluddin, Muhammad A.; Warner, Margaret L.; Bill, Roslyn M.; Harris, Paul W.; Brimble, Margaret A.; Poyner, David R.; Hay, Debbie L.; Pioszak, Augen A.

    2015-01-01

    Summary Association of receptor activity-modifying proteins (RAMP1-3) with the G protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) enables selective recognition of the peptides calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) that have diverse functions in the cardiovascular and lymphatic systems. How peptides selectively bind GPCR:RAMP complexes is unknown. We report crystal structures of CGRP analog-bound CLR:RAMP1 and AM-bound CLR:RAMP2 extracellular domain heterodimers at 2.5 and 1.8 Å resolutions, respectively. The peptides similarly occupy a shared binding site on CLR with conformations characterized by a β-turn structure near their C termini rather than the α-helical structure common to peptides that bind related GPCRs. The RAMPs augment the binding site with distinct contacts to the variable C-terminal peptide residues and elicit subtly different CLR conformations. The structures and accompanying pharmacology data reveal how a class of accessory membrane proteins modulate ligand binding of a GPCR and may inform drug development targeting CLR:RAMP complexes. PMID:25982113

  14. Carbon-Decorated TiO2 Nanotube Membranes: A Renewable Nanofilter for Charge-Selective Enrichment of Proteins.

    PubMed

    Xu, Jingwen; Yang, Lingling; Han, Yuyao; Wang, Yongmei; Zhou, Xuemei; Gao, Zhida; Song, Yan-Yan; Schmuki, Patrik

    2016-08-31

    In this work, we design a TiO2 nanomembrane (TiNM) that can be used as a nanofilter platform for selective enrichment of specific proteins. After a first use, the photocatalytic properties of TiO2 allow the decomposition of unwanted remnants on the substrate and thus make the platform reusable. To construct this platform, we fabricate a free-standing TiO2 nanotube array and remove the bottom oxide to form a both-end-open TiNM. By pyrolysis of the natural tube wall contamination, the walls become decorated with graphitic carbon patches (C/TiNM). Owing to the large surface area, the amphiphilic nature and the charge-adjustable character, this C/TiNM can be used to extract and enrich hydrophobic charged biomolecules. Using human serum albumin (HSA) as a model protein as well as protein mixtures, we show that the composite membrane exhibits a highly enhanced loading capacity and protein selectivity and is reusable after a short UV treatment. PMID:27509326

  15. Sexual selection and the adaptive evolution of PKDREJ protein in primates and rodents.

    PubMed

    Vicens, Alberto; Gómez Montoto, Laura; Couso-Ferrer, Francisco; Sutton, Keith A; Roldan, Eduardo R S

    2015-02-01

    PKDREJ is a testis-specific protein thought to be located on the sperm surface. Functional studies in the mouse revealed that loss of PKDREJ has effects on sperm transport and the ability to undergo an induced acrosome reaction. Thus, PKDREJ has been considered a potential target of post-copulatory sexual selection in the form of sperm competition. Proteins involved in reproductive processes often show accelerated evolution. In many cases, this rapid divergence is promoted by positive selection which may be driven, at least in part, by post-copulatory sexual selection. We analysed the evolution of the PKDREJ protein in primates and rodents and assessed whether PKDREJ divergence is associated with testes mass relative to body mass, which is a reliable proxy of sperm competition levels. Evidence of an association between the evolutionary rate of the PKDREJ gene and testes mass relative to body mass was not found in primates. Among rodents, evidence of positive selection was detected in the Pkdrej gene in the family Cricetidae but not in Muridae. We then assessed whether Pkdrej divergence is associated with episodes of sperm competition in these families. We detected a positive significant correlation between the evolutionary rates of Pkdrej and testes mass relative to body mass in cricetids. These findings constitute the first evidence of post-copulatory sexual selection influencing the evolution of a protein that participates in the mechanisms regulating sperm transport and the acrosome reaction, strongly suggesting that positive selection may act on these fertilization steps, leading to advantages in situations of sperm competition. PMID:25304980

  16. Mechanical Modeling and Computer Simulation of Protein Folding

    ERIC Educational Resources Information Center

    Prigozhin, Maxim B.; Scott, Gregory E.; Denos, Sharlene

    2014-01-01

    In this activity, science education and modern technology are bridged to teach students at the high school and undergraduate levels about protein folding and to strengthen their model building skills. Students are guided from a textbook picture of a protein as a rigid crystal structure to a more realistic view: proteins are highly dynamic…

  17. Selective actions of Lynx proteins on different nicotinic acetylcholine receptors in the locust, Locusta migratoria manilensis.

    PubMed

    Wang, Xin; Bao, Haibo; Sun, Huahua; Zhang, Yixi; Fang, Jichao; Liu, Qinghong; Liu, Zewen

    2015-08-01

    Nicotinic acetylcholine receptors (nAChRs) are major neurotransmitter receptors and targets of neonicotinoid insecticides in the insect nervous system. The full function of nAChRs is often dependent on associated proteins, such as chaperones, regulators and modulators. Here, three Lynx (Ly-6/neurotoxin) proteins, Loc-lynx1, Loc-lynx2 and Loc-lynx3, were identified in the locust, Locusta migratoria manilensis. Co-expression with Lynx resulted in a dramatic increase in agonist-evoked macroscopic currents on nAChRs Locα1/β2 and Locα2/β2 in Xenopus oocytes, but no changes in agonist sensitivity. Loc-lynx1 and Loc-lynx3 only modulated nAChRs Locα1/β2 while Loc-lynx2 modulated Locα2/β2 specifically. Meanwhile, Loc-lynx1 induced a more significant increase in currents evoked by imidacloprid and epibatidine than Loc-lynx3, and the effects of Loc-lynx1 on imidacloprid and epibatidine were significantly higher than those on acetylcholine. Among three lynx proteins, only Loc-lynx1 significantly increased [(3) H]epibatidine binding on Locα1/β2. The results indicated that Loc-lynx1 had different modulation patterns in nAChRs compared to Loc-lynx2 and Loc-lynx3. Taken together, these findings indicated that three Lynx proteins were nAChR modulators and had selective activities in different nAChRs. Lynx proteins might display their selectivities from three aspects: nAChR subtypes, various agonists and different modulation patterns. Insect Lynx (Ly-6/neurotoxin) proteins act as the allosteric modulators on insect nicotinic acetylcholine receptors (nAChRs), the important targets of insecticides. We found that insect lynx proteins showed their selectivities from at least three aspects: nAChR subtypes, various agonists and different modulation patterns.

  18. A nonionic surfactant-decorated liquid crystal sensor for sensitive and selective detection of proteins.

    PubMed

    Wang, Yi; Hu, Qiongzheng; Tian, Tongtong; Gao, Yan'an; Yu, Li

    2016-09-21

    Proteins are responsible for most biochemical events in human body. It is essential to develop sensitive and selective methods for the detection of proteins. In this study, liquid crystal (LC)-based sensor for highly selective and sensitive detection of lysozyme, concanavalin A (Con A), and bovine serum albumin (BSA) was constructed by utilizing the LC interface decorated with a nonionic surfactant, dodecyl β-d-glucopyranoside. A change of the LC optical images from bright to dark appearance was observed after transferring dodecyl β-d-glucopyranoside onto the aqueous/LC interface due to the formation of stable self-assembled surfactant monolayer, regardless of pH and ion concentrations studied in a wide range. The optical images turned back from dark to bright appearance after addition of lysozyme, Con A and BSA, respectively. Noteworthy is that these proteins can be further distinguished by adding enzyme inhibitors and controlling incubation temperature of the protein solutions based on three different interaction mechanisms between proteins and dodecyl β-d-glucopyranoside, viz. enzymatic hydrolysis, specific saccharide binding, and physical absorption. The LC-based sensor decorated with dodecyl β-d-glucopyranoside shows high sensitivity for protein detection. The limit of detection (LOD) for lysozyme, Con A and BSA reaches around 0.1 μg/mL, 0.01 μg/mL and 0.001 μg/mL, respectively. These results might provide new insights into increasing selectivity and sensitivity of LC-based sensors for the detection of proteins.

  19. A nonionic surfactant-decorated liquid crystal sensor for sensitive and selective detection of proteins.

    PubMed

    Wang, Yi; Hu, Qiongzheng; Tian, Tongtong; Gao, Yan'an; Yu, Li

    2016-09-21

    Proteins are responsible for most biochemical events in human body. It is essential to develop sensitive and selective methods for the detection of proteins. In this study, liquid crystal (LC)-based sensor for highly selective and sensitive detection of lysozyme, concanavalin A (Con A), and bovine serum albumin (BSA) was constructed by utilizing the LC interface decorated with a nonionic surfactant, dodecyl β-d-glucopyranoside. A change of the LC optical images from bright to dark appearance was observed after transferring dodecyl β-d-glucopyranoside onto the aqueous/LC interface due to the formation of stable self-assembled surfactant monolayer, regardless of pH and ion concentrations studied in a wide range. The optical images turned back from dark to bright appearance after addition of lysozyme, Con A and BSA, respectively. Noteworthy is that these proteins can be further distinguished by adding enzyme inhibitors and controlling incubation temperature of the protein solutions based on three different interaction mechanisms between proteins and dodecyl β-d-glucopyranoside, viz. enzymatic hydrolysis, specific saccharide binding, and physical absorption. The LC-based sensor decorated with dodecyl β-d-glucopyranoside shows high sensitivity for protein detection. The limit of detection (LOD) for lysozyme, Con A and BSA reaches around 0.1 μg/mL, 0.01 μg/mL and 0.001 μg/mL, respectively. These results might provide new insights into increasing selectivity and sensitivity of LC-based sensors for the detection of proteins. PMID:27590553

  20. Mathematical model of zinc absorption: effects of dietary calcium, protein and iron on zinc absorption.

    PubMed

    Miller, Leland V; Krebs, Nancy F; Hambidge, K Michael

    2013-02-28

    A previously described mathematical model of Zn absorption as a function of total daily dietary Zn and phytate was fitted to data from studies in which dietary Ca, Fe and protein were also measured. An analysis of regression residuals indicated statistically significant positive relationships between the residuals and Ca, Fe and protein, suggesting that the presence of any of these dietary components enhances Zn absorption. Based on the hypotheses that (1) Ca and Fe both promote Zn absorption by binding with phytate and thereby making it unavailable for binding Zn and (2) protein enhances the availability of Zn for transporter binding, the model was modified to incorporate these effects. The new model of Zn absorption as a function of dietary Zn, phytate, Ca, Fe and protein was then fitted to the data. The proportion of variation in absorbed Zn explained by the new model was 0·88, an increase from 0·82 with the original model. A reduced version of the model without Fe produced an equally good fit to the data and an improved value for the model selection criterion, demonstrating that when dietary Ca and protein are controlled for, there is no evidence that dietary Fe influences Zn absorption. Regression residuals and testing with additional data supported the validity of the new model. It was concluded that dietary Ca and protein modestly enhanced Zn absorption and Fe had no statistically discernable effect. Furthermore, the model provides a meaningful foundation for efforts to model nutrient interactions in mineral absorption.

  1. Selection of climate change scenario data for impact modelling.

    PubMed

    Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

  2. Completion of autobuilt protein models using a database of protein fragments

    SciTech Connect

    Cowtan, Kevin

    2012-04-01

    Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature.

  3. Effects of protein transduction domain (PTD) selection and position for improved intracellular delivery of PTD-Hsp27 fusion protein formulations.

    PubMed

    Ul Ain, Qurrat; Lee, Jong Hwan; Woo, Young Sun; Kim, Yong-Hee

    2016-09-01

    Protein drugs have attracted considerable attention as therapeutic agents due to their diversity and biocompatibility. However, hydrophilic proteins possess difficulty in penetrating lipophilic cell membrane. Although protein transduction domains (PTDs) have shown effectiveness in protein delivery, the importance of selection and position of PTDs in recombinant protein vector constructs has not been investigated. This study intends to investigate the significance of PTD selection and position for therapeutic protein delivery. Heat shock protein 27 (Hsp27) would be a therapeutic protein for the treatment of ischemic heart diseases, but itself is insufficient to prevent systemic degradation and overcoming biochemical barriers during cellular transport. Among all PTD-Hsp27 fusion proteins we cloned, Tat-Hsp27 fusion protein showed the highest efficacy. Nona-arginine (9R) conjugation to the N-terminal of Hsp27 (Hsp27-T) showed higher efficacy than C-terminal. To test the synergistic effect of two PTDs, Tat was inserted to the N-terminal of Hsp27-9R. Tat-Hsp27-9R exhibited enhanced transduction efficiency and significant improvement against oxidative stress and apoptosis. PTD-Hsp27 fusion proteins have strong potential to be developed as therapeutic proteins for the treatment of ischemic heart diseases and selection and position of PTDs for improved efficacy of PTD-fusion proteins need to be optimized considering protein's nature, transduction efficiency and stability.

  4. Improving genome-wide scans of positive selection by using protein isoforms of similar length.

    PubMed

    Villanueva-Cañas, José Luis; Laurie, Steve; Albà, M Mar

    2013-01-01

    Large-scale evolutionary studies often require the automated construction of alignments of a large number of homologous gene families. The majority of eukaryotic genes can produce different transcripts due to alternative splicing or transcription initiation, and many such transcripts encode different protein isoforms. As analyses tend to be gene centered, one single-protein isoform per gene is selected for the alignment, with the de facto approach being to use the longest protein isoform per gene (Longest), presumably to avoid including partial sequences and to maximize sequence information. Here, we show that this approach is problematic because it increases the number of indels in the alignments due to the inclusion of nonhomologous regions, such as those derived from species-specific exons, increasing the number of misaligned positions. With the aim of ameliorating this problem, we have developed a novel heuristic, Protein ALignment Optimizer (PALO), which, for each gene family, selects the combination of protein isoforms that are most similar in length. We examine several evolutionary parameters inferred from alignments in which the only difference is the method used to select the protein isoform combination: Longest, PALO, the combination that results in the highest sequence conservation, and a randomly selected combination. We observe that Longest tends to overestimate both nonsynonymous and synonymous substitution rates when compared with PALO, which is most likely due to an excess of misaligned positions. The estimation of the fraction of genes that have experienced positive selection by maximum likelihood is very sensitive to the method of isoform selection employed, both when alignments are constructed with MAFFT and with Prank(+F). Longest performs better than a random combination but still estimates up to 3 times more positively selected genes than the combination showing the highest conservation, indicating the presence of many false positives. We show

  5. Mushroom tyrosinase oxidizes tyrosine-rich sequences to allow selective protein functionalization.

    PubMed

    Long, Marcus J C; Hedstrom, Lizbeth

    2012-08-13

    We show that mushroom tyrosinase catalyzes the formation of reactive o-quinones on unstructured, tyrosine-rich sequences such as hemagglutinin (HA) tags (YPYDVPDYA). In the absence of exogenous nucleophiles and at low protein concentrations, the o-quinone decomposes with fragmentation of the HA tag. At higher protein concentrations (>5 mg mL⁻¹), crosslinking is observed. Besthorn's reagent intercepts the o-quinone to give a characteristic pink complex that can be observed directly on a denaturing SDS-PAGE gel. Similar labeled species can be formed by using other nucleophiles such as Cy5-hydrazide. These reactions are selective for proteins bearing HA and other unstructured poly-tyrosine-containing tags and can be performed in lysates to create specifically tagged proteins. PMID:22807021

  6. Construction of antibody-like nanoparticles for selective protein sequestration in living cells.

    PubMed

    Liu, Yibin; Fang, Simin; Zhai, Junqiu; Zhao, Meiping

    2015-04-28

    We demonstrate the successful construction of fluorescently labeled magnetic antibody-like nanoparticles (ANPs) via a facile one-step surface-initiated in situ molecular imprinting approach over silica coated magnetite (Fe3O4@SiO2) core-shell nanocomposites. The as-prepared ANPs had a highly compact structure with an overall size of 83 ± 5 nm in diameter and showed excellent aqueous dispersion stability. With the predetermined high specificity to the target protein and high biocompatibility, the ANPs enabled rapid, efficient, selective and optically trackable sequestration of target proteins within living cells. This work represents the first example of fully artificially engineered multifunctional ANPs for the intracellular protein-sequestration without disruption of the cells. The established approach may be further extended to generate ANPs for various proteins of interest and provide useful tools for related biological research and biomedical applications.

  7. Genetic variability and natural selection at the ligand domain of the Duffy binding protein in brazilian Plasmodium vivax populations

    PubMed Central

    2010-01-01

    Background Plasmodium vivax malaria is a major public health challenge in Latin America, Asia and Oceania, with 130-435 million clinical cases per year worldwide. Invasion of host blood cells by P. vivax mainly depends on a type I membrane protein called Duffy binding protein (PvDBP). The erythrocyte-binding motif of PvDBP is a 170 amino-acid stretch located in its cysteine-rich region II (PvDBPII), which is the most variable segment of the protein. Methods To test whether diversifying natural selection has shaped the nucleotide diversity of PvDBPII in Brazilian populations, this region was sequenced in 122 isolates from six different geographic areas. A Bayesian method was applied to test for the action of natural selection under a population genetic model that incorporates recombination. The analysis was integrated with a structural model of PvDBPII, and T- and B-cell epitopes were localized on the 3-D structure. Results The results suggest that: (i) recombination plays an important role in determining the haplotype structure of PvDBPII, and (ii) PvDBPII appears to contain neutrally evolving codons as well as codons evolving under natural selection. Diversifying selection preferentially acts on sites identified as epitopes, particularly on amino acid residues 417, 419, and 424, which show strong linkage disequilibrium. Conclusions This study shows that some polymorphisms of PvDBPII are present near the erythrocyte-binding domain and might serve to elude antibodies that inhibit cell invasion. Therefore, these polymorphisms should be taken into account when designing vaccines aimed at eliciting antibodies to inhibit erythrocyte invasion. PMID:21092207

  8. Homology-Based Modeling of Protein Structure

    NASA Astrophysics Data System (ADS)

    Xiang, Zhexin

    The human genome project has already discovered millions of proteins (http://www.swissprot.com). The potential of the genome project can only be fully realized once we can assign, understand, manipulate, and predict the function of these new proteins (Sanchez and Sali, 1997; Frishman et al., 2000; Domingues et al., 2000). Predicting protein function generally requires knowledge of protein three-dimensional structure (Blundell et al., 1978;Weber, 1990), which is ultimately determined by protein sequence (Anfinsen, 1973). Protein structure determination using experimental methods such as X-ray crystallography or NMR spectroscopy is very time consuming (Johnson et al. 1994). To date, fewer than 2% of the known proteins have had their structures solved experimentally. In 2004, more than half a million new proteins were sequenced that almost doubled the efforts in the previous year, but only 5300 structures were solved. Although the rate of experimental structure determination will continue to increase, the number of newly discovered sequences grows much faster than the number of structures solved (see Fig. 10.1).

  9. Proteins.

    ERIC Educational Resources Information Center

    Doolittle, Russell F.

    1985-01-01

    Examines proteins which give rise to structure and, by virtue of selective binding to other molecules, make genes. Binding sites, amino acids, protein evolution, and molecular paleontology are discussed. Work with encoding segments of deoxyribonucleic acid (exons) and noncoding stretches (introns) provides new information for hypotheses. (DH)

  10. The effect of geometrical presentation of multimodal cation-exchange ligands on selective recognition of hydrophobic regions on protein surfaces.

    PubMed

    Woo, James; Parimal, Siddharth; Brown, Matthew R; Heden, Ryan; Cramer, Steven M

    2015-09-18

    The effects of spatial organization of hydrophobic and charged moieties on multimodal (MM) cation-exchange ligands were examined by studying protein retention behavior on two commercial chromatographic media, Capto™ MMC and Nuvia™ cPrime™. Proteins with extended regions of surface-exposed aliphatic residues were found to have enhanced retention on the Capto MMC system as compared to the Nuvia cPrime resin. The results further indicated that while the Nuvia cPrime ligand had a strong preference for interactions with aromatic groups, the Capto MMC ligand appeared to interact with both aliphatic and aromatic clusters on the protein surfaces. These observations were formalized into a new set of protein surface property descriptors, which quantified the local distribution of electrostatic and hydrophobic potentials as well as distinguishing between aromatic and aliphatic properties. Using these descriptors, high-performing quantitative structure-activity relationship (QSAR) models (R(2)>0.88) were generated for both the Capto MMC and Nuvia cPrime datasets at pH 5 and pH 6. Descriptors of electrostatic properties were generally common across the four models; however both Capto MMC models included descriptors that quantified regions of aliphatic-based hydrophobicity in addition to aromatic descriptors. Retention was generally reduced by lowering the ligand densities on both MM resins. Notably, elution order was largely unaffected by the change in surface density, but smaller and more aliphatic proteins tended to be more affected by this drop in ligand density. This suggests that modulating the exposure, shape and density of the hydrophobic moieties in multimodal chromatographic systems can alter the preference for surface exposed aliphatic or aromatic residues, thus providing an additional dimension for modulating the selectivity of MM protein separation systems. PMID:26292626

  11. Fast and Selective Modification of Thiol Proteins/Peptides by N-(Phenylseleno)phthalimide

    NASA Astrophysics Data System (ADS)

    Wang, Zhengfang; Zhang, Yun; Zhang, Hao; Harrington, Peter B.; Chen, Hao

    2012-03-01

    We previously reported that selenamide reagents such as ebselen and N-(phenylseleno)phthalimide (NPSP) can be used to selectively derivatize thiols for mass spectrometric analysis, and the introduced selenium tags are useful as they could survive or removed with collision-induced dissociation (CID). Described herein is the further study of the reactivity of various protein/peptide thiols toward NPSP and its application to derivatize thiol peptides in protein digests. With a modified protocol (i.e., dissolving NPSP in acetonitrile instead of aqueous solvent), we found that quantitative conversion of thiols can be obtained in seconds, using NPSP in a slight excess amount (NPSP:thiol of 1.1-2:1). Further investigation shows that the thiol reactivity toward NPSP reflects its chemical environment and accessibility in proteins/peptides. For instance, adjacent basic amino acid residues increase the thiol reactivity, probably because they could stabilize the thiolate form to facilitate the nucleophilic attack of thiol on NPSP. In the case of creatine phosphokinase, the native protein predominately has one thiol reacted with NPSP while all of four thiol groups of the denatured protein can be derivatized, in accordance with the corresponding protein conformation. In addition, thiol peptides in protein/peptide enzymatic digests can be quickly and effectively tagged by NPSP following tri- n-butylphosphine (TBP) reduction. Notably, all three thiols of the peptide QCCASVCSL in the insulin peptic digest can be modified simultaneously by NPSP. These results suggest a novel and selective method for protecting thiols in the bottom-up approach for protein structure analysis.

  12. Construction of antibody-like nanoparticles for selective protein sequestration in living cells

    NASA Astrophysics Data System (ADS)

    Liu, Yibin; Fang, Simin; Zhai, Junqiu; Zhao, Meiping

    2015-04-01

    We demonstrate the successful construction of fluorescently labeled magnetic antibody-like nanoparticles (ANPs) via a facile one-step surface-initiated in situ molecular imprinting approach over silica coated magnetite (Fe3O4@SiO2) core-shell nanocomposites. The as-prepared ANPs had a highly compact structure with an overall size of 83 +/- 5 nm in diameter and showed excellent aqueous dispersion stability. With the predetermined high specificity to the target protein and high biocompatibility, the ANPs enabled rapid, efficient, selective and optically trackable sequestration of target proteins within living cells. This work represents the first example of fully artificially engineered multifunctional ANPs for the intracellular protein-sequestration without disruption of the cells. The established approach may be further extended to generate ANPs for various proteins of interest and provide useful tools for related biological research and biomedical applications.We demonstrate the successful construction of fluorescently labeled magnetic antibody-like nanoparticles (ANPs) via a facile one-step surface-initiated in situ molecular imprinting approach over silica coated magnetite (Fe3O4@SiO2) core-shell nanocomposites. The as-prepared ANPs had a highly compact structure with an overall size of 83 +/- 5 nm in diameter and showed excellent aqueous dispersion stability. With the predetermined high specificity to the target protein and high biocompatibility, the ANPs enabled rapid, efficient, selective and optically trackable sequestration of target proteins within living cells. This work represents the first example of fully artificially engineered multifunctional ANPs for the intracellular protein-sequestration without disruption of the cells. The established approach may be further extended to generate ANPs for various proteins of interest and provide useful tools for related biological research and biomedical applications. Electronic supplementary information (ESI

  13. Fast and Selective Modification of Thiol Proteins/Peptides by N-(Phenylseleno) phthalimide

    PubMed Central

    Wang, Zhengfang; Zhang, Yun; Zhang, Hao; Harrington, Peter B.; Chen, Hao

    2013-01-01

    We previously reported that selenamide reagents such as ebselen and N-(phenylseleno) phthalimide (NPSP) can be used to selectively derivatize thiols for mass spectrometric analysis, and the introduced selenium tags are useful as they could survive or removed with collision-induced dissociation (CID). Described herein is the further study of the reactivity of various protein/peptide thiols toward NPSP and its application to derivatize thiol peptides in protein digests. With a modified protocol (i.e., dissolving NPSP in acetonitrile instead of aqueous solvent), we found that quantitative conversion of thiols can be obtained in seconds, using NPSP in a slight excess amount (NPSP:thiol of 1.1–2:1). Further investigation shows that the thiol reactivity toward NPSP reflects its chemical environment and accessibility in proteins/peptides. For instance, adjacent basic amino acid residues increase the thiol reactivity, probably because they could stabilize the thiolate form to facilitate the nucleophilic attack of thiol on NPSP. In the case of creatine phosphokinase, the native protein predominately has one thiol reacted with NPSP while all of four thiol groups of the denatured protein can be derivatized, in accordance with the corresponding protein conformation. In addition, thiol peptides in protein/peptide enzymatic digests can be quickly and effectively tagged by NPSP following tri-n-butylphosphine (TBP) reduction. Notably, all three thiols of the peptide QCCASVCSL in the insulin peptic digest can be modified simultaneously by NPSP. These results suggest a novel and selective method for protecting thiols in the bottom-up approach for protein structure analysis. PMID:22223263

  14. IT vendor selection model by using structural equation model & analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Maitra, Sarit; Dominic, P. D. D.

    2012-11-01

    Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

  15. Control of active sites in selective flocculation: I -- Mathematical model

    SciTech Connect

    Behl, S.; Moudgil, B.M.; Prakash, T.S. . Dept. of Materials Science and Engineering)

    1993-12-01

    Heteroflocculation has been determined to be another major reason for loss in selectivity for flocculation process. In a mathematical model developed earlier, conditions for controlling heteroflocculation were discussed. Blocking active sites to control selective adsorption of a flocculant oil a desirable solid surface is discussed. It has been demonstrated that the lower molecular weight fraction of a flocculant which is incapable of flocculating the particles is an efficient site blocking agent. The major application of selective flocculation has been in mineral processing but many potential uses exist in biological and other colloidal systems. These include purification of ceramic powders, separating hazardous solids from chemical waste, and removal of deleterious components from paper pulp.

  16. Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: Approaches with minimal redundancy maximal relevance feature selection.

    PubMed

    Jiao, Ya-Sen; Du, Pu-Feng

    2016-08-01

    Recently, several efforts have been made in predicting Golgi-resident proteins. However, it is still a challenging task to identify the type of a Golgi-resident protein. Precise prediction of the type of a Golgi-resident protein plays a key role in understanding its molecular functions in various biological processes. In this paper, we proposed to use a mutual information based feature selection scheme with the general form Chou's pseudo-amino acid compositions to predict the Golgi-resident protein types. The positional specific physicochemical properties were applied in the Chou's pseudo-amino acid compositions. We achieved 91.24% prediction accuracy in a jackknife test with 49 selected features. It has the best performance among all the present predictors. This result indicates that our computational model can be useful in identifying Golgi-resident protein types. PMID:27155042

  17. Spectral modeling of channel band shapes in wavelength selective switches.

    PubMed

    Pulikkaseril, Cibby; Stewart, Luke A; Roelens, Michaël A F; Baxter, Glenn W; Poole, Simon; Frisken, Steve

    2011-04-25

    A model for characterizing the spectral response of the passband of Wavelength Selective Switches (WSS) is presented. We demonstrate that, in contrast to the commonly used supergaussian model, the presented model offers a more complete match to measured results, as it is based on the physical operation of the optical system. We also demonstrate that this model is better suited for calculation of WSS channel bandwidths, as well as predicting the final bandwidth of cascaded WSS modules. Finally, we show the utility of this model in predicting channel shapes in flexible bandwidth WSS channel plans.

  18. Novel screening assay for the selective detection of G-protein-coupled receptor heteromer signaling.

    PubMed

    van Rijn, Richard M; Harvey, Jessica H; Brissett, Daniela I; DeFriel, Julia N; Whistler, Jennifer L

    2013-01-01

    Drugs targeting G-protein-coupled receptors (GPCRs) make up more than 25% of all prescribed medicines. The ability of GPCRs to form heteromers with unique signaling properties suggests an entirely new and unexplored pool of drug targets. However, current in vitro assays are ill equipped to detect heteromer-selective compounds. We have successfully adapted an approach, using fusion proteins of GPCRs and chimeric G proteins, to create an in vitro screening assay (in human embryonic kidney cells) in which only activated heteromers are detectable. Here we show that this assay can demonstrate heteromer-selective G-protein bias as well as measure transinhibition. Using this assay, we reveal that the δ-opioid receptor agonist ADL5859, which is currently in clinical trials, has a 10-fold higher potency against δ-opioid receptor homomers than δ/μ-opioid receptor heteromers (pEC(50) = 6.7 ± 0.1 versus 5.8 ± 0.2). The assay enables the screening of large compound libraries to identify heteromer-selective compounds that could then be used in vivo to determine the functional role of heteromers and develop potential therapeutic agents.

  19. A Peptidomimetic Antibiotic Targets Outer Membrane Proteins and Disrupts Selectively the Outer Membrane in Escherichia coli.

    PubMed

    Urfer, Matthias; Bogdanovic, Jasmina; Lo Monte, Fabio; Moehle, Kerstin; Zerbe, Katja; Omasits, Ulrich; Ahrens, Christian H; Pessi, Gabriella; Eberl, Leo; Robinson, John A

    2016-01-22

    Increasing antibacterial resistance presents a major challenge in antibiotic discovery. One attractive target in Gram-negative bacteria is the unique asymmetric outer membrane (OM), which acts as a permeability barrier that protects the cell from external stresses, such as the presence of antibiotics. We describe a novel β-hairpin macrocyclic peptide JB-95 with potent antimicrobial activity against Escherichia coli. This peptide exhibits no cellular lytic activity, but electron microscopy and fluorescence studies reveal an ability to selectively disrupt the OM but not the inner membrane of E. coli. The selective targeting of the OM probably occurs through interactions of JB-95 with selected β-barrel OM proteins, including BamA and LptD as shown by photolabeling experiments. Membrane proteomic studies reveal rapid depletion of many β-barrel OM proteins from JB-95-treated E. coli, consistent with induction of a membrane stress response and/or direct inhibition of the Bam folding machine. The results suggest that lethal disruption of the OM by JB-95 occurs through a novel mechanism of action at key interaction sites within clusters of β-barrel proteins in the OM. These findings open new avenues for developing antibiotics that specifically target β-barrel proteins and the integrity of the Gram-negative OM.

  20. A Peptidomimetic Antibiotic Targets Outer Membrane Proteins and Disrupts Selectively the Outer Membrane in Escherichia coli.

    PubMed

    Urfer, Matthias; Bogdanovic, Jasmina; Lo Monte, Fabio; Moehle, Kerstin; Zerbe, Katja; Omasits, Ulrich; Ahrens, Christian H; Pessi, Gabriella; Eberl, Leo; Robinson, John A

    2016-01-22

    Increasing antibacterial resistance presents a major challenge in antibiotic discovery. One attractive target in Gram-negative bacteria is the unique asymmetric outer membrane (OM), which acts as a permeability barrier that protects the cell from external stresses, such as the presence of antibiotics. We describe a novel β-hairpin macrocyclic peptide JB-95 with potent antimicrobial activity against Escherichia coli. This peptide exhibits no cellular lytic activity, but electron microscopy and fluorescence studies reveal an ability to selectively disrupt the OM but not the inner membrane of E. coli. The selective targeting of the OM probably occurs through interactions of JB-95 with selected β-barrel OM proteins, including BamA and LptD as shown by photolabeling experiments. Membrane proteomic studies reveal rapid depletion of many β-barrel OM proteins from JB-95-treated E. coli, consistent with induction of a membrane stress response and/or direct inhibition of the Bam folding machine. The results suggest that lethal disruption of the OM by JB-95 occurs through a novel mechanism of action at key interaction sites within clusters of β-barrel proteins in the OM. These findings open new avenues for developing antibiotics that specifically target β-barrel proteins and the integrity of the Gram-negative OM. PMID:26627837

  1. Protein adsorption on nanoparticles: model development using computer simulation.

    PubMed

    Shao, Qing; Hall, Carol K

    2016-10-19

    The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler-Guggenheim and Hill-de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles. PMID:27546610

  2. Protein adsorption on nanoparticles: model development using computer simulation

    NASA Astrophysics Data System (ADS)

    Shao, Qing; Hall, Carol K.

    2016-10-01

    The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler-Guggenheim and Hill-de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles.

  3. Microfluidics-Based Selection of Red-Fluorescent Proteins with Decreased Rates of Photobleaching

    PubMed Central

    Dean, Kevin M.; Lubbeck, Jennifer L.; Davis, Lloyd M.; Regmi, Chola K.; Chapagain, Prem P.; Gerstman, Bernard S.; Jimenez, Ralph; Palmer, Amy E.

    2014-01-01

    Fluorescent proteins offer exceptional labeling specificity in living cells and organisms. Unfortunately, their photophysical properties remain far from ideal for long-term imaging of low-abundance cellular constituents, in large part because of their poor photostability. Despite widespread engineering efforts, improving the photostability of fluorescent proteins remains challenging due to lack of appropriate high-throughput selection methods. Here, we use molecular dynamics guided mutagenesis in conjunction with a recently developed microfluidic-based platform, which sorts cells based on their fluorescence photostability, to identify red fluorescent proteins with decreased photobleaching from a HeLa cell-based library. The identified mutant, named Kriek, has 2.5- and 4-fold higher photostability than its progenitor, mCherry, under widefield and confocal illumination, respectively. Furthermore, the results provide insight into mechanisms for enhancing photostability and their connections with other photophysical processes, thereby providing direction for ongoing development of fluorescent proteins with improved single-molecule and low-copy imaging capabilities. Insight, innovation, integration Fluorescent proteins enable imaging in situ, throughout the visible spectrum, with superb molecular specificity and single-molecule sensitivity. Unfortunately, when compared to leading small-molecule fluorophores (e.g., Cy3), fluorescent proteins, suffer from accelerated photobleaching and poor integrated photon output. This results from a lack of appropriate high-throughput methods for improving the photostability of fluorescent proteins, as well as a poor molecular understanding of fluorescent protein photobleaching. Here, we report the first application of a recently developed microfluidic cell-sorter to identify fluorescent proteins from a mCherry-derived library with improved photostability. The results provide insight into fluorescent protein photophysics, greatly

  4. Model Selection in Historical Research Using Approximate Bayesian Computation

    PubMed Central

    Rubio-Campillo, Xavier

    2016-01-01

    Formal Models and History Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our understanding of past societies based on their written sources. The extensive use of formal models allows historians to re-evaluate hypotheses formulated decades ago and still subject to debate due to the lack of an adequate quantitative framework. The initiative has the potential to transform the discipline if it solves the challenges posed by the study of historical dynamics. These difficulties are based on the complexities of modelling social interaction, and the methodological issues raised by the evaluation of formal models against data with low sample size, high variance and strong fragmentation. Case Study This work examines an alternate approach to this evaluation based on a Bayesian-inspired model selection method. The validity of the classical Lanchester’s laws of combat is examined against a dataset comprising over a thousand battles spanning 300 years. Four variations of the basic equations are discussed, including the three most common formulations (linear, squared, and logarithmic) and a new variant introducing fatigue. Approximate Bayesian Computation is then used to infer both parameter values and model selection via Bayes Factors. Impact Results indicate decisive evidence favouring the new fatigue model. The interpretation of both parameter estimations and model selection provides new insights into the factors guiding the evolution of warfare. At a methodological level, the case study shows how model selection methods can be used to guide historical research through the comparison between existing hypotheses and empirical evidence. PMID:26730953

  5. Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

    PubMed Central

    Kundrotas, Petras J.; Vakser, Ilya A.

    2010-01-01

    The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Å, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Åmodeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes. PMID:20369011

  6. Robust model selection and the statistical classification of languages

    NASA Astrophysics Data System (ADS)

    García, J. E.; González-López, V. A.; Viola, M. L. L.

    2012-10-01

    In this paper we address the problem of model selection for the set of finite memory stochastic processes with finite alphabet, when the data is contaminated. We consider m independent samples, with more than half of them being realizations of the same stochastic process with law Q, which is the one we want to retrieve. We devise a model selection procedure such that for a sample size large enough, the selected process is the one with law Q. Our model selection strategy is based on estimating relative entropies to select a subset of samples that are realizations of the same law. Although the procedure is valid for any family of finite order Markov models, we will focus on the family of variable length Markov chain models, which include the fixed order Markov chain model family. We define the asymptotic breakdown point (ABDP) for a model selection procedure, and we show the ABDP for our procedure. This means that if the proportion of contaminated samples is smaller than the ABDP, then, as the sample size grows our procedure selects a model for the process with law Q. We also use our procedure in a setting where we have one sample conformed by the concatenation of sub-samples of two or more stochastic processes, with most of the subsamples having law Q. We conducted a simulation study. In the application section we address the question of the statistical classification of languages according to their rhythmic features using speech samples. This is an important open problem in phonology. A persistent difficulty on this problem is that the speech samples correspond to several sentences produced by diverse speakers, corresponding to a mixture of distributions. The usual procedure to deal with this problem has been to choose a subset of the original sample which seems to best represent each language. The selection is made by listening to the samples. In our application we use the full dataset without any preselection of samples. We apply our robust methodology estimating

  7. Bayesian Nonlinear Model Selection for Gene Regulatory Networks

    PubMed Central

    Ni, Yang; Stingo, Francesco C.; Baladandayuthapani, Veerabhadran

    2015-01-01

    Summary Gene regulatory networks represent the regulatory relationships between genes and their products and are important for exploring and defining the underlying biological processes of cellular systems. We develop a novel framework to recover the structure of nonlinear gene regulatory networks using semiparametric spline-based directed acyclic graphical models. Our use of splines allows the model to have both flexibility in capturing nonlinear dependencies as well as control of overfitting via shrinkage, using mixed model representations of penalized splines. We propose a novel discrete mixture prior on the smoothing parameter of the splines that allows for simultaneous selection of both linear and nonlinear functional relationships as well as inducing sparsity in the edge selection. Using simulation studies, we demonstrate the superior performance of our methods in comparison with several existing approaches in terms of network reconstruction and functional selection. We apply our methods to a gene expression dataset in glioblastoma multiforme, which reveals several interesting and biologically relevant nonlinear relationships. PMID:25854759

  8. Time-shared experiments for efficient assignment of triple-selectively labeled proteins.

    PubMed

    Löhr, Frank; Laguerre, Aisha; Bock, Christoph; Reckel, Sina; Connolly, Peter J; Abdul-Manan, Norzehan; Tumulka, Franz; Abele, Rupert; Moore, Jonathan M; Dötsch, Volker

    2014-11-01

    Combinatorial triple-selective labeling facilitates the NMR assignment process for proteins that are subject to signal overlap and insufficient signal-to-noise in standard triple-resonance experiments. Aiming at maximum amino-acid type and sequence-specific information, the method represents a trade-off between the number of selectively labeled samples that have to be prepared and the number of spectra to be recorded per sample. In order to address the demand of long measurement times, we here propose pulse sequences in which individual phase-shifted transients are stored separately and recombined later to produce several 2D HN(CX) type spectra that are usually acquired sequentially. Sign encoding by the phases of (13)C 90° pulses allows to either select or discriminate against (13)C' or (13)C(α) spins coupled to (15)N. As a result, (1)H-(15)N correlation maps of the various isotopomeric species present in triple-selectively labeled proteins are deconvoluted which in turn reduces problems due to spectral overlap. The new methods are demonstrated with four different membrane proteins with rotational correlation times ranging from 18 to 52 ns.

  9. Time-shared experiments for efficient assignment of triple-selectively labeled proteins

    PubMed Central

    Löhr, Frank; Laguerre, Aisha; Bock, Christoph; Reckel, Sina; Connolly, Peter J.; Abdul-Manan, Norzehan; Tumulka, Franz; Abele, Rupert; Moore, Jonathan M.; Dötsch, Volker

    2014-01-01

    Combinatorial triple-selective labeling facilitates the NMR assignment process for proteins that are subject to signal overlap and insufficient signal-to-noise in standard triple-resonance experiments. Aiming at maximum amino-acid type and sequence-specific information, the method represents a trade-off between the number of selectively labeled samples that have to be prepared and the number of spectra to be recorded per sample. In order to address the demand of long measurement times, we here propose pulse sequences in which individual phase-shifted transients are stored separately and recombined later to produce several 2D HN(CX) type spectra that are usually acquired sequentially. Sign encoding by the phases of 13C 90° pulses allows to either select or discriminate against 13C’ or 13Cα spins coupled to 15N. As a result, 1H-15N correlation maps of the various isotopomeric species present in triple-selectively labeled proteins are deconvoluted which in turn reduces problems due to spectral overlap. The new methods are demonstrated with four different membrane proteins with rotational correlation times ranging from 18 to 52 ns. PMID:25442777

  10. Uncertain programming models for portfolio selection with uncertain returns

    NASA Astrophysics Data System (ADS)

    Zhang, Bo; Peng, Jin; Li, Shengguo

    2015-10-01

    In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.

  11. Differential Nanos 2 protein stability results in selective germ cell accumulation in the sea urchin.

    PubMed

    Oulhen, Nathalie; Wessel, Gary M

    2016-10-01

    Nanos is a translational regulator required for the survival and maintenance of primordial germ cells. In the sea urchin, Strongylocentrotus purpuratus (Sp), Nanos 2 mRNA is broadly transcribed but accumulates specifically in the small micromere (sMic) lineage, in part because of the 3'UTR element GNARLE leads to turnover in somatic cells but retention in the sMics. Here we found that the Nanos 2 protein is also selectively stabilized; it is initially translated throughout the embryo but turned over in the future somatic cells and retained only in the sMics, the future germ line in this animal. This differential stability of Nanos protein is dependent on the open reading frame (ORF), and is independent of the sumoylation and ubiquitylation pathways. Manipulation of the ORF indicates that 68 amino acids in the N terminus of the Nanos protein are essential for its stability in the sMics whereas a 45 amino acid element adjacent to the zinc fingers targets its degradation. Further, this regulation of Nanos protein is cell autonomous, following formation of the germ line. These results are paradigmatic for the unique presence of Nanos in the germ line by a combination of selective RNA retention, distinctive translational control mechanisms (Oulhen et al., 2013), and now also by defined Nanos protein stability.

  12. Differential Nanos 2 protein stability results in selective germ cell accumulation in the sea urchin.

    PubMed

    Oulhen, Nathalie; Wessel, Gary M

    2016-10-01

    Nanos is a translational regulator required for the survival and maintenance of primordial germ cells. In the sea urchin, Strongylocentrotus purpuratus (Sp), Nanos 2 mRNA is broadly transcribed but accumulates specifically in the small micromere (sMic) lineage, in part because of the 3'UTR element GNARLE leads to turnover in somatic cells but retention in the sMics. Here we found that the Nanos 2 protein is also selectively stabilized; it is initially translated throughout the embryo but turned over in the future somatic cells and retained only in the sMics, the future germ line in this animal. This differential stability of Nanos protein is dependent on the open reading frame (ORF), and is independent of the sumoylation and ubiquitylation pathways. Manipulation of the ORF indicates that 68 amino acids in the N terminus of the Nanos protein are essential for its stability in the sMics whereas a 45 amino acid element adjacent to the zinc fingers targets its degradation. Further, this regulation of Nanos protein is cell autonomous, following formation of the germ line. These results are paradigmatic for the unique presence of Nanos in the germ line by a combination of selective RNA retention, distinctive translational control mechanisms (Oulhen et al., 2013), and now also by defined Nanos protein stability. PMID:27424271

  13. Betulinic Acid Selectively Increases Protein Degradation and Enhances Prostate Cancer-Specific Apoptosis: Possible Role for Inhibition of Deubiquitinase Activity

    PubMed Central

    Reiner, Teresita; Parrondo, Ricardo; de las Pozas, Alicia; Palenzuela, Deanna; Perez-Stable, Carlos

    2013-01-01

    Inhibition of the ubiquitin-proteasome system (UPS) of protein degradation is a valid anti-cancer strategy and has led to the approval of bortezomib for the treatment of multiple myeloma. However, the alternative approach of enhancing the degradation of oncoproteins that are frequently overexpressed in cancers is less developed. Betulinic acid (BA) is a plant-derived small molecule that can increase apoptosis specifically in cancer but not in normal cells, making it an attractive anti-cancer agent. Our results in prostate cancer suggested that BA inhibited multiple deubiquitinases (DUBs), which resulted in the accumulation of poly-ubiquitinated proteins, decreased levels of oncoproteins, and increased apoptotic cell death. In normal fibroblasts, however, BA did not inhibit DUB activity nor increased total poly-ubiquitinated proteins, which was associated with a lack of effect on cell death. In the TRAMP transgenic mouse model of prostate cancer, treatment with BA (10 mg/kg) inhibited primary tumors, increased apoptosis, decreased angiogenesis and proliferation, and lowered androgen receptor and cyclin D1 protein. BA treatment also inhibited DUB activity and increased ubiquitinated proteins in TRAMP prostate cancer but had no effect on apoptosis or ubiquitination in normal mouse tissues. Overall, our data suggests that BA-mediated inhibition of DUBs and induction of apoptotic cell death specifically in prostate cancer but not in normal cells and tissues may provide an effective non-toxic and clinically selective agent for chemotherapy. PMID:23424652

  14. Optimization of Parameter Selection for Partial Least Squares Model Development

    NASA Astrophysics Data System (ADS)

    Zhao, Na; Wu, Zhi-Sheng; Zhang, Qiao; Shi, Xin-Yuan; Ma, Qun; Qiao, Yan-Jiang

    2015-07-01

    In multivariate calibration using a spectral dataset, it is difficult to optimize nonsystematic parameters in a quantitative model, i.e., spectral pretreatment, latent factors and variable selection. In this study, we describe a novel and systematic approach that uses a processing trajectory to select three parameters including different spectral pretreatments, variable importance in the projection (VIP) for variable selection and latent factors in the Partial Least-Square (PLS) model. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the ratio of standard error of prediction to standard deviation (RPD), and the determination coefficient of calibration (Rcal2) and validation (Rpre2) were simultaneously assessed to optimize the best modeling path. We used three different near-infrared (NIR) datasets, which illustrated that there was more than one modeling path to ensure good modeling. The PLS model optimizes modeling parameters step-by-step, but the robust model described here demonstrates better efficiency than other published papers.

  15. The E-MS Algorithm: Model Selection with Incomplete Data

    PubMed Central

    Jiang, Jiming; Nguyen, Thuan; Rao, J. Sunil

    2014-01-01

    We propose a procedure associated with the idea of the E-M algorithm for model selection in the presence of missing data. The idea extends the concept of parameters to include both the model and the parameters under the model, and thus allows the model to be part of the E-M iterations. We develop the procedure, known as the E-MS algorithm, under the assumption that the class of candidate models is finite. Some special cases of the procedure are considered, including E-MS with the generalized information criteria (GIC), and E-MS with the adaptive fence (AF; Jiang et al. 2008). We prove numerical convergence of the E-MS algorithm as well as consistency in model selection of the limiting model of the E-MS convergence, for E-MS with GIC and E-MS with AF. We study the impact on model selection of different missing data mechanisms. Furthermore, we carry out extensive simulation studies on the finite-sample performance of the E-MS with comparisons to other procedures. The methodology is also illustrated on a real data analysis involving QTL mapping for an agricultural study on barley grains. PMID:26783375

  16. From Genomes to Protein Models and Back

    NASA Astrophysics Data System (ADS)

    Tramontano, Anna; Giorgetti, Alejandro; Orsini, Massimiliano; Raimondo, Domenico

    2007-12-01

    The alternative splicing mechanism allows genes to generate more than one product. When the splicing events occur within protein coding regions they can modify the biological function of the protein. Alternative splicing has been suggested as one way for explaining the discrepancy between the number of human genes and functional complexity. We analysed the putative structure of the alternatively spliced gene products annotated in the ENCODE pilot project and discovered that many of the potential alternative gene products will be unlikely to produce stable functional proteins.

  17. Tracking Membrane Protein Association in Model Membranes

    PubMed Central

    Reffay, Myriam; Gambin, Yann; Benabdelhak, Houssain; Phan, Gilles; Taulier, Nicolas; Ducruix, Arnaud; Hodges, Robert S.; Urbach, Wladimir

    2009-01-01

    Membrane proteins are essential in the exchange processes of cells. In spite of great breakthrough in soluble proteins studies, membrane proteins structures, functions and interactions are still a challenge because of the difficulties related to their hydrophobic properties. Most of the experiments are performed with detergent-solubilized membrane proteins. However widely used micellar systems are far from the biological two-dimensions membrane. The development of new biomimetic membrane systems is fundamental to tackle this issue. We present an original approach that combines the Fluorescence Recovery After fringe Pattern Photobleaching technique and the use of a versatile sponge phase that makes it possible to extract crucial informations about interactions between membrane proteins embedded in the bilayers of a sponge phase. The clear advantage lies in the ability to adjust at will the spacing between two adjacent bilayers. When the membranes are far apart, the only possible interactions occur laterally between proteins embedded within the same bilayer, whereas when membranes get closer to each other, interactions between proteins embedded in facing membranes may occur as well. After validating our approach on the streptavidin-biotinylated peptide complex, we study the interactions between two membrane proteins, MexA and OprM, from a Pseudomonas aeruginosa efflux pump. The mode of interaction, the size of the protein complex and its potential stoichiometry are determined. In particular, we demonstrate that: MexA is effectively embedded in the bilayer; MexA and OprM do not interact laterally but can form a complex if they are embedded in opposite bilayers; the population of bound proteins is at its maximum for bilayers separated by a distance of about 200 Å, which is the periplasmic thickness of Pseudomonas aeruginosa. We also show that the MexA-OprM association is enhanced when the position and orientation of the protein is restricted by the bilayers. We

  18. Accuracy of functional surfaces on comparatively modeled protein structures

    PubMed Central

    Zhao, Jieling; Dundas, Joe; Kachalo, Sema; Ouyang, Zheng; Liang, Jie

    2012-01-01

    Identification and characterization of protein functional surfaces are important for predicting protein function, understanding enzyme mechanism, and docking small compounds to proteins. As the rapid speed of accumulation of protein sequence information far exceeds that of structures, constructing accurate models of protein functional surfaces and identify their key elements become increasingly important. A promising approach is to build comparative models from sequences using known structural templates such as those obtained from structural genome projects. Here we assess how well this approach works in modeling binding surfaces. By systematically building three-dimensional comparative models of proteins using Modeller, we determine how well functional surfaces can be accurately reproduced. We use an alpha shape based pocket algorithm to compute all pockets on the modeled structures, and conduct a large-scale computation of similarity measurements (pocket RMSD and fraction of functional atoms captured) for 26,590 modeled enzyme protein structures. Overall, we find that when the sequence fragment of the binding surfaces has more than 45% identity to that of the tempalte protein, the modeled surfaces have on average an RMSD of 0.5 Å, and contain 48% or more of the binding surface atoms, with nearly all of the important atoms in the signatures of binding pockets captured. PMID:21541664

  19. Selection and demographic history shape the molecular evolution of the gamete compatibility protein bindin in Pisaster sea stars

    PubMed Central

    Popovic, Iva; Marko, Peter B; Wares, John P; Hart, Michael W

    2014-01-01

    Reproductive compatibility proteins have been shown to evolve rapidly under positive selection leading to reproductive isolation, despite the potential homogenizing effects of gene flow. This process has been implicated in both primary divergence among conspecific populations and reinforcement during secondary contact; however, these two selective regimes can be difficult to discriminate from each other. Here, we describe the gene that encodes the gamete compatibility protein bindin for three sea star species in the genus Pisaster. First, we compare the full-length bindin-coding sequence among all three species and analyze the evolutionary relationships between the repetitive domains of the variable second bindin exon. The comparison suggests that concerted evolution of repetitive domains has an effect on bindin divergence among species and bindin variation within species. Second, we characterize population variation in the second bindin exon of two species: We show that positive selection acts on bindin variation in Pisaster ochraceus but not in Pisaster brevispinus, which is consistent with higher polyspermy risk in P. ochraceus. Third, we show that there is no significant genetic differentiation among populations and no apparent effect of sympatry with congeners that would suggest selection based on reinforcement. Fourth, we combine bindin and cytochrome c oxidase 1 data in isolation-with-migration models to estimate gene flow parameter values and explore the historical demographic context of our positive selection results. Our findings suggest that positive selection on bindin divergence among P. ochraceus alleles can be accounted for in part by relatively recent northward population expansions that may be coupled with the potential homogenizing effects of concerted evolution. PMID:24967076

  20. Selection and demographic history shape the molecular evolution of the gamete compatibility protein bindin in Pisaster sea stars.

    PubMed

    Popovic, Iva; Marko, Peter B; Wares, John P; Hart, Michael W

    2014-05-01

    Reproductive compatibility proteins have been shown to evolve rapidly under positive selection leading to reproductive isolation, despite the potential homogenizing effects of gene flow. This process has been implicated in both primary divergence among conspecific populations and reinforcement during secondary contact; however, these two selective regimes can be difficult to discriminate from each other. Here, we describe the gene that encodes the gamete compatibility protein bindin for three sea star species in the genus Pisaster. First, we compare the full-length bindin-coding sequence among all three species and analyze the evolutionary relationships between the repetitive domains of the variable second bindin exon. The comparison suggests that concerted evolution of repetitive domains has an effect on bindin divergence among species and bindin variation within species. Second, we characterize population variation in the second bindin exon of two species: We show that positive selection acts on bindin variation in Pisaster ochraceus but not in Pisaster brevispinus, which is consistent with higher polyspermy risk in P. ochraceus. Third, we show that there is no significant genetic differentiation among populations and no apparent effect of sympatry with congeners that would suggest selection based on reinforcement. Fourth, we combine bindin and cytochrome c oxidase 1 data in isolation-with-migration models to estimate gene flow parameter values and explore the historical demographic context of our positive selection results. Our findings suggest that positive selection on bindin divergence among P. ochraceus alleles can be accounted for in part by relatively recent northward population expansions that may be coupled with the potential homogenizing effects of concerted evolution. PMID:24967076

  1. Selection and demographic history shape the molecular evolution of the gamete compatibility protein bindin in Pisaster sea stars.

    PubMed

    Popovic, Iva; Marko, Peter B; Wares, John P; Hart, Michael W

    2014-05-01

    Reproductive compatibility proteins have been shown to evolve rapidly under positive selection leading to reproductive isolation, despite the potential homogenizing effects of gene flow. This process has been implicated in both primary divergence among conspecific populations and reinforcement during secondary contact; however, these two selective regimes can be difficult to discriminate from each other. Here, we describe the gene that encodes the gamete compatibility protein bindin for three sea star species in the genus Pisaster. First, we compare the full-length bindin-coding sequence among all three species and analyze the evolutionary relationships between the repetitive domains of the variable second bindin exon. The comparison suggests that concerted evolution of repetitive domains has an effect on bindin divergence among species and bindin variation within species. Second, we characterize population variation in the second bindin exon of two species: We show that positive selection acts on bindin variation in Pisaster ochraceus but not in Pisaster brevispinus, which is consistent with higher polyspermy risk in P. ochraceus. Third, we show that there is no significant genetic differentiation among populations and no apparent effect of sympatry with congeners that would suggest selection based on reinforcement. Fourth, we combine bindin and cytochrome c oxidase 1 data in isolation-with-migration models to estimate gene flow parameter values and explore the historical demographic context of our positive selection results. Our findings suggest that positive selection on bindin divergence among P. ochraceus alleles can be accounted for in part by relatively recent northward population expansions that may be coupled with the potential homogenizing effects of concerted evolution.

  2. Identification and Structure-Function Analysis of Subfamily Selective G Protein-Coupled Receptor Kinase Inhibitors

    SciTech Connect

    Homan, Kristoff T.; Larimore, Kelly M.; Elkins, Jonathan M.; Szklarz, Marta; Knapp, Stefan; Tesmer, John J.G.

    2015-02-13

    Selective inhibitors of individual subfamilies of G protein-coupled receptor kinases (GRKs) would serve as useful chemical probes as well as leads for therapeutic applications ranging from heart failure to Parkinson’s disease. To identify such inhibitors, differential scanning fluorimetry was used to screen a collection of known protein kinase inhibitors that could increase the melting points of the two most ubiquitously expressed GRKs: GRK2 and GRK5. Enzymatic assays on 14 of the most stabilizing hits revealed that three exhibit nanomolar potency of inhibition for individual GRKs, some of which exhibiting orders of magnitude selectivity. Most of the identified compounds can be clustered into two chemical classes: indazole/dihydropyrimidine-containing compounds that are selective for GRK2 and pyrrolopyrimidine-containing compounds that potently inhibit GRK1 and GRK5 but with more modest selectivity. The two most potent inhibitors representing each class, GSK180736A and GSK2163632A, were cocrystallized with GRK2 and GRK1, and their atomic structures were determined to 2.6 and 1.85 Å spacings, respectively. GSK180736A, developed as a Rho-associated, coiled-coil-containing protein kinase inhibitor, binds to GRK2 in a manner analogous to that of paroxetine, whereas GSK2163632A, developed as an insulin-like growth factor 1 receptor inhibitor, occupies a novel region of the GRK active site cleft that could likely be exploited to achieve more selectivity. However, neither compound inhibits GRKs more potently than their initial targets. This data provides the foundation for future efforts to rationally design even more potent and selective GRK inhibitors.

  3. Identification and structure-function analysis of subfamily selective G protein-coupled receptor kinase inhibitors.

    PubMed

    Homan, Kristoff T; Larimore, Kelly M; Elkins, Jonathan M; Szklarz, Marta; Knapp, Stefan; Tesmer, John J G

    2015-01-16

    Selective inhibitors of individual subfamilies of G protein-coupled receptor kinases (GRKs) would serve as useful chemical probes as well as leads for therapeutic applications ranging from heart failure to Parkinson's disease. To identify such inhibitors, differential scanning fluorimetry was used to screen a collection of known protein kinase inhibitors that could increase the melting points of the two most ubiquitously expressed GRKs: GRK2 and GRK5. Enzymatic assays on 14 of the most stabilizing hits revealed that three exhibit nanomolar potency of inhibition for individual GRKs, some of which exhibiting orders of magnitude selectivity. Most of the identified compounds can be clustered into two chemical classes: indazole/dihydropyrimidine-containing compounds that are selective for GRK2 and pyrrolopyrimidine-containing compounds that potently inhibit GRK1 and GRK5 but with more modest selectivity. The two most potent inhibitors representing each class, GSK180736A and GSK2163632A, were cocrystallized with GRK2 and GRK1, and their atomic structures were determined to 2.6 and 1.85 Å spacings, respectively. GSK180736A, developed as a Rho-associated, coiled-coil-containing protein kinase inhibitor, binds to GRK2 in a manner analogous to that of paroxetine, whereas GSK2163632A, developed as an insulin-like growth factor 1 receptor inhibitor, occupies a novel region of the GRK active site cleft that could likely be exploited to achieve more selectivity. However, neither compound inhibits GRKs more potently than their initial targets. This data provides the foundation for future efforts to rationally design even more potent and selective GRK inhibitors.

  4. Positive Selection Pressure Drives Variation on the Surface-Exposed Variable Proteins of the Pathogenic Neisseria

    PubMed Central

    Hill, Stuart

    2016-01-01

    Pathogenic species of Neisseria utilize variable outer membrane proteins to facilitate infection and proliferation within the human host. However, the mechanisms behind the evolution of these variable alleles remain largely unknown due to analysis of previously limited datasets. In this study, we have expanded upon the previous analyses to substantially increase the number of analyzed sequences by including multiple diverse strains, from various geographic locations, to determine whether positive selective pressure is exerted on the evolution of these variable genes. Although Neisseria are naturally competent, this analysis indicates that only intrastrain horizontal gene transfer among the pathogenic Neisseria principally account for these genes exhibiting linkage equilibrium which drives the polymorphisms evidenced within these alleles. As the majority of polymorphisms occur across species, the divergence of these variable genes is dependent upon the species and is independent of geographical location, disease severity, or serogroup. Tests of neutrality were able to detect strong selection pressures acting upon both the opa and pil gene families, and were able to locate the majority of these sites within the exposed variable regions of the encoded proteins. Evidence of positive selection acting upon the hypervariable domains of Opa contradicts previous beliefs and provides evidence for selection of receptor binding. As the pathogenic Neisseria reside exclusively within the human host, the strong selection pressures acting upon both the opa and pil gene families provide support for host immune system pressure driving sequence polymorphisms within these variable genes. PMID:27532335

  5. Routes to covalent catalysis by reactive selection for nascent protein nucleophiles.

    PubMed

    Reshetnyak, Andrey V; Armentano, Maria Francesca; Ponomarenko, Natalia A; Vizzuso, Domenica; Durova, Oxana M; Ziganshin, Rustam; Serebryakova, Marina; Govorun, Vadim; Gololobov, Gennady; Morse, Herbert C; Friboulet, Alain; Makker, Sudesh P; Gabibov, Alexander G; Tramontano, Alfonso

    2007-12-26

    Reactivity-based selection strategies have been used to enrich combinatorial libraries for encoded biocatalysts having revised substrate specificity or altered catalytic activity. This approach can also assist in artificial evolution of enzyme catalysis from protein templates without bias for predefined catalytic sites. The prevalence of covalent intermediates in enzymatic mechanisms suggests the universal utility of the covalent complex as the basis for selection. Covalent selection by phosphonate ester exchange was applied to a phage display library of antibody variable fragments (scFv) to sample the scope and mechanism of chemical reactivity in a naive molecular library. Selected scFv segregated into structurally related covalent and noncovalent binders. Clones that reacted covalently utilized tyrosine residues exclusively as the nucleophile. Two motifs were identified by structural analysis, recruiting distinct Tyr residues of the light chain. Most clones employed Tyr32 in CDR-L1, whereas a unique clone (A.17) reacted at Tyr36 in FR-L2. Enhanced phosphonylation kinetics and modest amidase activity of A.17 suggested a primitive catalytic site. Covalent selection may thus provide access to protein molecules that approximate an early apparatus for covalent catalysis. PMID:18044899

  6. Characterization of quinone derived protein adducts and their selective identification using redox cycling based chemiluminescence assay.

    PubMed

    Elgawish, Mohamed Saleh; Kishikawa, Naoya; Ohyama, Kaname; Kuroda, Naotaka

    2015-07-17

    The cytotoxic mechanism of many quinones has been correlated to covalent modification of cellular proteins. However, the identification of relevant proteins targets is essential but challenging goals. To better understand the quinones cytotoxic mechanism, human serum albumin (HSA) was incubated in vitro with different concentration of menadione (MQ). In this respect, the initial nucleophilic addition of proteins to quinone converts the conjugates to redox-cycling quinoproteins with altered conformation and secondary structure and extended life span than the short lived, free quinones. The conjugation of MQ with nucleophilic sites likewise, free cysteine as well as ɛ-amino group of lysine residue of HSA has been found to be in concentration dependent manner. The conventional methods for modified proteins identification in complex mixtures are complicated and time consuming. Herein, we describe a highly selective, sensitive, simple, and fast strategy for quinoproteins identification. The suggested strategy exploited the unique redox-cycling capability of quinoproteins in presence of a reductant, dithiothreitol (DTT), to generate reactive oxygen species (ROS) that gave sufficient chemiluminescence (CL) when mixed with luminol. The CL approach is highly selective and sensitive to detect the quinoproteins in ten-fold molar excess of native proteins without adduct enrichment. The approach was also coupled with gel filtration chromatography (GFC) and used to identify adducts in complex mixture of proteins in vitro as well as in rat plasma after MQ administration. Albumin was identified as the main protein in human and rat plasma forming adduct with MQ. Overall, the identification of quinoproteins will encourage further studies of toxicological impact of quinones on human health. PMID:26044383

  7. Balancing selection at the prion protein gene consistent with prehistoric kurulike epidemics.

    PubMed

    Mead, Simon; Stumpf, Michael P H; Whitfield, Jerome; Beck, Jonathan A; Poulter, Mark; Campbell, Tracy; Uphill, James B; Goldstein, David; Alpers, Michael; Fisher, Elizabeth M C; Collinge, John

    2003-04-25

    Kuru is an acquired prion disease largely restricted to the Fore linguistic group of the Papua New Guinea Highlands, which was transmitted during endocannibalistic feasts. Heterozygosity for a common polymorphism in the human prion protein gene (PRNP) confers relative resistance to prion diseases. Elderly survivors of the kuru epidemic, who had multiple exposures at mortuary feasts, are, in marked contrast to younger unexposed Fore, predominantly PRNP 129 heterozygotes. Kuru imposed strong balancing selection on the Fore, essentially eliminating PRNP 129 homozygotes. Worldwide PRNP haplotype diversity and coding allele frequencies suggest that strong balancing selection at this locus occurred during the evolution of modern humans. PMID:12690204

  8. Investigating the performance of AIC in selecting phylogenetic models.

    PubMed

    Jhwueng, Dwueng-Chwuan; Huzurbazar, Snehalata; O'Meara, Brian C; Liu, Liang

    2014-08-01

    The popular likelihood-based model selection criterion, Akaike's Information Criterion (AIC), is a breakthrough mathematical result derived from information theory. AIC is an approximation to Kullback-Leibler (KL) divergence with the derivation relying on the assumption that the likelihood function has finite second derivatives. However, for phylogenetic estimation, given that tree space is discrete with respect to tree topology, the assumption of a continuous likelihood function with finite second derivatives is violated. In this paper, we investigate the relationship between the expected log likelihood of a candidate model, and the expected KL divergence in the context of phylogenetic tree estimation. We find that given the tree topology, AIC is an unbiased estimator of the expected KL divergence. However, when the tree topology is unknown, AIC tends to underestimate the expected KL divergence for phylogenetic models. Simulation results suggest that the degree of underestimation varies across phylogenetic models so that even for large sample sizes, the bias of AIC can result in selecting a wrong model. As the choice of phylogenetic models is essential for statistical phylogenetic inference, it is important to improve the accuracy of model selection criteria in the context of phylogenetics. PMID:24867284

  9. A model of selective masking in chromatic detection.

    PubMed

    Shepard, Timothy G; Swanson, Emily A; McCarthy, Comfrey L; Eskew, Rhea T

    2016-07-01

    Narrowly tuned, selective noise masking of chromatic detection has been taken as evidence for the existence of a large number of color mechanisms (i.e., higher order color mechanisms). Here we replicate earlier observations of selective masking of tests in the (L,M) plane of cone space when the noise is placed near the corners of the detection contour. We used unipolar Gaussian blob tests with three different noise color directions, and we show that there are substantial asymmetries in the detection contours-asymmetries that would have been missed with bipolar tests such as Gabor patches. We develop a new chromatic detection model, which is based on probability summation of linear cone combinations, and incorporates a linear contrast energy versus noise power relationship that predicts how the sensitivity of these mechanisms changes with noise contrast and chromaticity. With only six unipolar color mechanisms (the same number as the cardinal model), the new model accounts for the threshold contours across the different noise conditions, including the asymmetries and the selective effects of the noises. The key for producing selective noise masking in the (L,M) plane is having more than two mechanisms with opposed L- and M-cone inputs, in which case selective masking can be produced without large numbers of color mechanisms. PMID:27442723

  10. Lessons from making the Structural Classification of Proteins (SCOP) and their implications for protein structure modelling

    PubMed Central

    Andreeva, Antonina

    2016-01-01

    The Structural Classification of Proteins (SCOP) database has facilitated the development of many tools and algorithms and it has been successfully used in protein structure prediction and large-scale genome annotations. During the development of SCOP, numerous exceptions were found to topological rules, along with complex evolutionary scenarios and peculiarities in proteins including the ability to fold into alternative structures. This article reviews cases of structural variations observed for individual proteins and among groups of homologues, knowledge of which is essential for protein structure modelling. PMID:27284063

  11. A heterodimer-selective agonist shows in vivo relevance of G protein-coupled receptor dimers.

    PubMed

    Waldhoer, Maria; Fong, Jamie; Jones, Robert M; Lunzer, Mary M; Sharma, Shiv K; Kostenis, Evi; Portoghese, Philip S; Whistler, Jennifer L

    2005-06-21

    There has been much speculation regarding the functional relevance of G protein-coupled receptor heterodimers, primarily because demonstrating their existence in vivo has proven to be a considerable challenge. Here we show that the opioid agonist ligand 6'-guanidinonaltrindole (6'-GNTI) has the unique property of selectively activating only opioid receptor heterodimers but not homomers. Importantly, 6'-GNTI is an analgesic, thereby demonstrating that opioid receptor heterodimers are indeed functionally relevant in vivo. However, 6'-GNTI induces analgesia only when it is administered in the spinal cord but not in the brain, suggesting that the organization of heterodimers is tissue-specific. This study demonstrates a proof of concept for tissue-selective drug targeting based on G protein-coupled receptor heterodimerization. Importantly, targeting opioid heterodimers could provide an approach toward the design of analgesic drugs with reduced side effects.

  12. Selective secretion of annexin 1, a protein without a signal sequence, by the human prostate gland.

    PubMed

    Christmas, P; Callaway, J; Fallon, J; Jones, J; Haigler, H T

    1991-02-01

    Annexins are primarily intracellular proteins as would be predicted from their lack of hydrophobic signal sequences. However, we now report that the human prostate gland selectively secretes high concentrations of annexin 1 (also called lipocortin 1 and p35) and a proteolytic cleavage product, des1-29-annexin 1, into seminal plasma. Secreted annexin 1 had a blocked amino terminus and was structurally indistinguishable from intracellular annexin 1. Although annexin 1 and the structurally related protein, annexin 4, co-localized to many of the same cells of the ductal epithelium of the prostate, annexin 4 was not secreted. Thus, the secretion of annexin 1 appears to involve a highly selective mechanism that does not involve targeting to the endoplasmic reticulum by a hydrophobic signal sequence.

  13. Model selection methodology in supervised learning with evolutionary computation.

    PubMed

    Rowland, J J

    2003-11-01

    The expressive power, powerful search capability, and the explicit nature of the resulting models make evolutionary methods very attractive for supervised learning applications in bioinformatics. However, their characteristics also make them highly susceptible to overtraining or to discovering chance relationships in the data. Identification of appropriate criteria for terminating evolution and for selecting an appropriately validated model is vital. Some approaches that are commonly applied to other modelling methods are not necessarily applicable in a straightforward manner to evolutionary methods. An approach to model selection is presented that is not unduly computationally intensive. To illustrate the issues and the technique two bioinformatic datasets are used, one relating to metabolite determination and the other to disease prediction from gene expression data.

  14. Proteomic profiling of maize opaque endosperm mutants reveals selective accumulation of lysine-enriched proteins

    PubMed Central

    Morton, Kyla J.; Jia, Shangang; Zhang, Chi; Holding, David R.

    2016-01-01

    Reduced prolamin (zein) accumulation and defective endoplasmic reticulum (ER) body formation occurs in maize opaque endosperm mutants opaque2 (o2), floury2 (fl2), defective endosperm*B30 (DeB30), and Mucronate (Mc), whereas other opaque mutants such as opaque1 (o1) and floury1 (fl1) are normal in these regards. This suggests that other factors contribute to kernel texture. A liquid chromatography approach coupled with tandem mass spectrometry (LC-MS/MS) proteomics was used to compare non-zein proteins of nearly isogenic opaque endosperm mutants. In total, 2762 proteins were identified that were enriched for biological processes such as protein transport and folding, amino acid biosynthesis, and proteolysis. Principal component analysis and pathway enrichment suggested that the mutants partitioned into three groups: (i) Mc, DeB30, fl2 and o2; (ii) o1; and (iii) fl1. Indicator species analysis revealed mutant-specific proteins, and highlighted ER secretory pathway components that were enriched in selected groups of mutants. The most significantly changed proteins were related to stress or defense and zein partitioning into the soluble fraction for Mc, DeB30, o1, and fl1 specifically. In silico dissection of the most significantly changed proteins revealed novel qualitative changes in lysine abundance contributing to the overall lysine increase and the nutritional rebalancing of the o2 and fl2 endosperm. PMID:26712829

  15. Selective Constraint on Human Pre-mRNA Splicing by Protein Structural Properties

    PubMed Central

    de Brevern, Alexandre G.; Chuang, Trees-Juen; Chen, Feng-Chi

    2012-01-01

    Alternative splicing (AS) is a major mechanism of increasing proteome diversity in complex organisms. Different AS transcript isoforms may be translated into peptide sequences of significantly different lengths and amino acid compositions. One important question, then, is how AS is constrained by protein structural requirements while peptide sequences may be significantly changed in AS events. Here, we address this issue by examining whether the intactness of three-dimensional protein structural units (compact units in protein structures, namely protein units [PUs]) tends to be preserved in AS events in human. We show that PUs tend to occur in constitutively spliced exons and to overlap constitutive exon boundaries. Furthermore, when PUs are located at the boundaries between two alternatively spliced exons (ASEs), these neighboring ASEs tend to co-occur in different transcript isoforms. In addition, such PU-spanned ASE pairs tend to have a higher frequency of being included in transcript isoforms. ASE regions that overlap with PUs also have lower nonsynonymous-to-synonymous substitution rate ratios than those that do not overlap with PUs, indicating stronger negative selection pressure in PU-overlapped ASE regions. Of note, we show that PUs have protein domain- and structural orderness-independent effects on messenger RNA (mRNA) splicing. Overall, our results suggest that fine-scale protein structural requirements have significant influences on the splicing patterns of human mRNAs. PMID:22936073

  16. A rapid and selective mass spectrometric method for the identification of nitrated proteins.

    PubMed

    Amoresano, Angela; Chiappetta, Giovanni; Pucci, Piero; Marino, Gennaro

    2008-01-01

    The nitration of protein tyrosine residues represents an important posttranslational modification during development, oxidative stress, and biological aging. The major challenge in the proteomic analysis of nitroproteins is the need to discriminate modified proteins, usually occurring at substoichiometric levels, from the large amount of nonmodified proteins. Moreover, precise localization of the nitration site is often required to fully describe the biological process. Identification of the specific targets of protein oxidation was previously accomplished using immunoprecipitation techniques followed by immunochemical detection. Here, we report a totally new approach involving dansyl chloride labeling of the nitration sites which relies on the enormous potential of MS(n) analysis. The tryptic digest from the entire protein mixture is directly analyzed by MS on a linear ion trap mass spectrometer. Discrimination between nitro- and unmodified peptide is based on two selectivity criteria obtained by combining a precursor ion scan and a MS3 analysis. The novel labeling procedure was successfully applied to the identification of 3-nitrotyrosine residues in complex protein mixtures. PMID:19082935

  17. Multi-agent Reinforcement Learning Model for Effective Action Selection

    NASA Astrophysics Data System (ADS)

    Youk, Sang Jo; Lee, Bong Keun

    Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

  18. Model-based sensor location selection for helicopter gearbox monitoring

    NASA Technical Reports Server (NTRS)

    Jammu, Vinay B.; Wang, Keming; Danai, Kourosh; Lewicki, David G.

    1996-01-01

    A new methodology is introduced to quantify the significance of accelerometer locations for fault diagnosis of helicopter gearboxes. The basis for this methodology is an influence model which represents the effect of various component faults on accelerometer readings. Based on this model, a set of selection indices are defined to characterize the diagnosability of each component, the coverage of each accelerometer, and the relative redundancy between the accelerometers. The effectiveness of these indices is evaluated experimentally by measurement-fault data obtained from an OH-58A main rotor gearbox. These data are used to obtain a ranking of individual accelerometers according to their significance in diagnosis. Comparison between the experimentally obtained rankings and those obtained from the selection indices indicates that the proposed methodology offers a systematic means for accelerometer location selection.

  19. Evidence accumulation as a model for lexical selection.

    PubMed

    Anders, R; Riès, S; van Maanen, L; Alario, F X

    2015-11-01

    We propose and demonstrate evidence accumulation as a plausible theoretical and/or empirical model for the lexical selection process of lexical retrieval. A number of current psycholinguistic theories consider lexical selection as a process related to selecting a lexical target from a number of alternatives, which each have varying activations (or signal supports), that are largely resultant of an initial stimulus recognition. We thoroughly present a case for how such a process may be theoretically explained by the evidence accumulation paradigm, and we demonstrate how this paradigm can be directly related or combined with conventional psycholinguistic theory and their simulatory instantiations (generally, neural network models). Then with a demonstrative application on a large new real data set, we establish how the empirical evidence accumulation approach is able to provide parameter results that are informative to leading psycholinguistic theory, and that motivate future theoretical development. PMID:26375509

  20. MONNA, a Potent and Selective Blocker for Transmembrane Protein with Unknown Function 16/Anoctamin-1

    PubMed Central

    Oh, Soo-Jin; Hwang, Seok Jin; Jung, Jonghoon; Yu, Kuai; Kim, Jeongyeon; Choi, Jung Yoon; Hartzell, H. Criss

    2013-01-01

    Transmembrane protein with unknown function 16/anoctamin-1 (ANO1) is a protein widely expressed in mammalian tissues, and it has the properties of the classic calcium-activated chloride channel (CaCC). This protein has been implicated in numerous major physiological functions. However, the lack of effective and selective blockers has hindered a detailed study of the physiological functions of this channel. In this study, we have developed a potent and selective blocker for endogenous ANO1 in Xenopus laevis oocytes (xANO1) using a drug screening method we previously established (Oh et al., 2008). We have synthesized a number of anthranilic acid derivatives and have determined the correlation between biological activity and the nature and position of substituents in these derived compounds. A structure-activity relationship revealed novel chemical classes of xANO1 blockers. The derivatives contain a −NO2 group on position 5 of a naphthyl group-substituted anthranilic acid, and they fully blocked xANO1 chloride currents with an IC50 < 10 μM. The most potent blocker, N-((4-methoxy)-2-naphthyl)-5-nitroanthranilic acid (MONNA), had an IC50 of 0.08 μM for xANO1. Selectivity tests revealed that other chloride channels such as bestrophin-1, chloride channel protein 2, and cystic fibrosis transmembrane conductance regulator were not appreciably blocked by 10∼30 μM MONNA. The potent and selective blockers for ANO1 identified here should permit pharmacological dissection of ANO1/CaCC function and serve as potential candidates for drug therapy of related diseases such as hypertension, cystic fibrosis, bronchitis, asthma, and hyperalgesia. PMID:23997117

  1. Detecting the form of selection in the outer membrane protein C of Enterobacter aerogenes strains and Salmonella species.

    PubMed

    Padhi, Abinash; Verghese, Bindhu; Otta, Subhendu K

    2009-01-01

    The types of selective pressure operating on the outer membrane protein C (ompC) of Enterobacter aerogenes strains, the causative agent for nosocomial infections, and Salmonella sp., the hazardous pathogen are investigated using the maximum likelihood-based codon substitution models. Although the rate of amino acid replacement to the silent substitution (omega) across the entire codon sites of ompC of E. aerogenes (omega=0.3194) and Salmonella sp. (omega=0.2047) indicate that the gene is subjected to purifying selection (i.e. omega<1), approximately 3.7% of ompC codon sites in E. aerogenes (omega=21.52) are under the influence of positive Darwinian selection (i.e. omega>1). Such contrast in the intensity of selective pressures in both pathogens could be associated with the differential response to the adverse environmental changes. In E. aerogenes, majority of the positively selected sites are located in the hypervariable cell-surface-exposed domains whereas the trans-membrane domains are functionally highly constrained.

  2. Second-order model selection in mixture experiments

    SciTech Connect

    Redgate, P.E.; Piepel, G.F.; Hrma, P.R.

    1992-07-01

    Full second-order models for q-component mixture experiments contain q(q+l)/2 terms, which increases rapidly as q increases. Fitting full second-order models for larger q may involve problems with ill-conditioning and overfitting. These problems can be remedied by transforming the mixture components and/or fitting reduced forms of the full second-order mixture model. Various component transformation and model reduction approaches are discussed. Data from a 10-component nuclear waste glass study are used to illustrate ill-conditioning and overfitting problems that can be encountered when fitting a full second-order mixture model. Component transformation, model term selection, and model evaluation/validation techniques are discussed and illustrated for the waste glass example.

  3. Research and Development into a Comprehensive Media Selection Model.

    ERIC Educational Resources Information Center

    Cantor, Jeffrey A.

    1988-01-01

    Describes and discusses an instructional systems media selection model based on training effectiveness and cost effectiveness prediction techniques that were developed to support the U.S. Navy's training programs. Highlights include instructional delivery systems (IDS); decision making; trainee characteristics; training requirements analysis; an…

  4. A computational model of selection by consequences: log survivor plots.

    PubMed

    Kulubekova, Saule; McDowell, J J

    2008-06-01

    [McDowell, J.J, 2004. A computational model of selection by consequences. J. Exp. Anal. Behav. 81, 297-317] instantiated the principle of selection by consequences in a virtual organism with an evolving repertoire of possible behaviors undergoing selection, reproduction, and mutation over many generations. The process is based on the computational approach, which is non-deterministic and rules-based. The model proposes a causal account for operant behavior. McDowell found that the virtual organism consistently showed a hyperbolic relationship between response and reinforcement rates according to the quantitative law of effect. To continue validation of the computational model, the present study examined its behavior on the molecular level by comparing the virtual organism's IRT distributions in the form of log survivor plots to findings from live organisms. Log survivor plots did not show the "broken-stick" feature indicative of distinct bouts and pauses in responding, although the bend in slope of the plots became more defined at low reinforcement rates. The shape of the virtual organism's log survivor plots was more consistent with the data on reinforced responding in pigeons. These results suggest that log survivor plot patterns of the virtual organism were generally consistent with the findings from live organisms providing further support for the computational model of selection by consequences as a viable account of operant behavior.

  5. Control of selectivity via nanochemistry: monolithic capillary column containing hydroxyapatite nanoparticles for separation of proteins and enrichment of phosphopeptides.

    PubMed

    Krenkova, Jana; Lacher, Nathan A; Svec, Frantisek

    2010-10-01

    New monolithic capillary columns with embedded commercial hydroxyapatite nanoparticles have been developed and used for protein separation and selective enrichment of phosphopeptides. The rod-shaped hydroxyapatite nanoparticles were incorporated into the poly(2-hydroxyethyl methacrylate-co-ethylene dimethacrylate) monolith by simply admixing them in the polymerization mixture followed by in situ polymerization. The effect of percentages of monomers and hydroxyapatite nanoparticles in the polymerization mixture on the performance of the monolithic column was explored in detail. We found that the loading capacity of the monolith is on par with other hydroxyapatite separation media. However, the speed at which these columns can be used is higher due to the fast mass transport. The function of the monolithic columns was demonstrated with the separations of a model mixture of proteins including ovalbumin, myoglobin, lysozyme, and cytochrome c as well as a monoclonal antibody and its aggregates with protein A. Selective enrichment and MALDI/MS characterization of phosphopeptides fished-out from complex peptide mixtures of ovalbumin, α-casein, and β-casein digests were also achieved using the hydroxyapatite monolith.

  6. Accurate Model Selection of Relaxed Molecular Clocks in Bayesian Phylogenetics

    PubMed Central

    Baele, Guy; Li, Wai Lok Sibon; Drummond, Alexei J.; Suchard, Marc A.; Lemey, Philippe

    2013-01-01

    Recent implementations of path sampling (PS) and stepping-stone sampling (SS) have been shown to outperform the harmonic mean estimator (HME) and a posterior simulation-based analog of Akaike’s information criterion through Markov chain Monte Carlo (AICM), in Bayesian model selection of demographic and molecular clock models. Almost simultaneously, a Bayesian model averaging approach was developed that avoids conditioning on a single model but averages over a set of relaxed clock models. This approach returns estimates of the posterior probability of each clock model through which one can estimate the Bayes factor in favor of the maximum a posteriori (MAP) clock model; however, this Bayes factor estimate may suffer when the posterior probability of the MAP model approaches 1. Here, we compare these two recent developments with the HME, stabilized/smoothed HME (sHME), and AICM, using both synthetic and empirical data. Our comparison shows reassuringly that MAP identification and its Bayes factor provide similar performance to PS and SS and that these approaches considerably outperform HME, sHME, and AICM in selecting the correct underlying clock model. We also illustrate the importance of using proper priors on a large set of empirical data sets. PMID:23090976

  7. Parmodel: a web server for automated comparative modeling of proteins.

    PubMed

    Uchôa, Hugo Brandão; Jorge, Guilherme Eberhart; Freitas Da Silveira, Nelson José; Camera, João Carlos; Canduri, Fernanda; De Azevedo, Walter Filgueira

    2004-12-24

    Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models for a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at .

  8. Angiotensin converting enzyme inhibitory activity of soy prote