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Sample records for protein model selection

  1. Extension of the selection of protein chromatography and the rate model to affinity chromatography.

    PubMed

    Sandoval, G; Shene, C; Andrews, B A; Asenjo, J A

    2010-01-01

    The rational selection of optimal protein purification sequences, as well as mathematical models that simulate and allow optimization of chromatographic protein purification processes have been developed for purification procedures such as ion-exchange, hydrophobic interaction and gel filtration chromatography. This paper investigates the extension of such analysis to affinity chromatography both in the selection of chromatographic processes and in the use of the rate model for mathematical modelling and simulation. Two affinity systems were used: Blue Sepharose and Protein A. The extension of the theory developed previously for ion-exchange and HIC chromatography to affinity separations is analyzed in this paper. For the selection of operations two algorithms are used. In the first, the value of η, which corresponds to the efficiency (resolution) of the actual chromatography and, Σ, which determines the amount of a particular contaminant eliminated after each separation step, which determines the purity, have to be determined. It was found that the value of both these parameters is not generic for affinity separations but will depend on the type of affinity system used and will have to be determined on a case by case basis. With Blue Sepharose a salt gradient was used and with Protein A, a pH gradient. Parameters were determined with individual proteins and simulations of the protein mixtures were done. This approach allows investigation of chromatographic protein purification in a holistic manner that includes ion-exchange, HIC, gel filtration and affinity separations for the first time.

  2. 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 .

  3. Protein purification using chromatography: selection of type, modelling and optimization of operating conditions.

    PubMed

    Asenjo, J A; Andrews, B A

    2009-01-01

    To achieve a high level of purity in the purification of recombinant proteins for therapeutic or analytical application, it is necessary to use several chromatographic steps. There is a range of techniques available including anion and cation exchange, which can be carried out at different pHs, hydrophobic interaction chromatography, gel filtration and affinity chromatography. In the case of a complex mixture of partially unknown proteins or a clarified cell extract, there are many different routes one can take in order to choose the minimum and most efficient number of purification steps to achieve a desired level of purity (e.g. 98%, 99.5% or 99.9%). This review shows how an initial 'proteomic' characterization of the complex mixture of target protein and protein contaminants can be used to select the most efficient chromatographic separation steps in order to achieve a specific level of purity with a minimum number of steps. The chosen methodology was implemented in a computer- based Expert System. Two algorithms were developed, the first algorithm was used to select the most efficient purification method to separate a protein from its contaminants based on the physicochemical properties of the protein product and the protein contaminants and the second algorithm was used to predict the number and concentration of contaminants after each separation as well as protein product purity. The application of the Expert System approach was experimentally tested and validated with a mixture of four proteins and the experimental validation was also carried out with a supernatant of Bacillus subtilis producing a recombinant beta-1,3-glucanase. Once the type of chromatography is chosen, optimization of the operating conditions is essential. Chromatographic elution curves for a three-protein mixture (alpha-lactoalbumin, ovalbumin and beta-lactoglobulin), carried out under different flow rates and ionic strength conditions, were simulated using two different mathematical

  4. 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

  5. On morphological selection rule of noisy character applied to model (dis)orderly protein formations

    NASA Astrophysics Data System (ADS)

    Siódmiak, Jacek; Santamaría-Holek, Ivan; Gadomski, Adam

    2010-05-01

    We propose that the main mechanism controlling the selection rule of model (dis)orderly protein formations, such as non-Kossel crystal growth and aggregation of lysozyme from aqueous solution, is an ion-channeling filter having flicker-noise properties. This filter is originated at the interfaces between growing solidlike object and its external liquid-type phase, and it can be considered as a series of voltage gated ion subchannels. The dynamics of each channel is studied by using both simulation and analytic argumentation lines, and represents a novel thought on how to utilize the presence of constructive-noise sources in protein formation, a field of utmost experimental and technological interest.

  6. Selective Advantage of Recombination in Evolving Protein Populations:. a Lattice Model Study

    NASA Astrophysics Data System (ADS)

    Williams, Paul D.; Pollock, David D.; Goldstein, Richard A.

    Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population.

  7. Optimized parameter selection reveals trends in Markov state models for protein folding

    NASA Astrophysics Data System (ADS)

    Husic, Brooke E.; McGibbon, Robert T.; Sultan, Mohammad M.; Pande, Vijay S.

    2016-11-01

    As molecular dynamics simulations access increasingly longer time scales, complementary advances in the analysis of biomolecular time-series data are necessary. Markov state models offer a powerful framework for this analysis by describing a system's states and the transitions between them. A recently established variational theorem for Markov state models now enables modelers to systematically determine the best way to describe a system's dynamics. In the context of the variational theorem, we analyze ultra-long folding simulations for a canonical set of twelve proteins [K. Lindorff-Larsen et al., Science 334, 517 (2011)] by creating and evaluating many types of Markov state models. We present a set of guidelines for constructing Markov state models of protein folding; namely, we recommend the use of cross-validation and a kinetically motivated dimensionality reduction step for improved descriptions of folding dynamics. We also warn that precise kinetics predictions rely on the features chosen to describe the system and pose the description of kinetic uncertainty across ensembles of models as an open issue.

  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. Directional Darwinian Selection in proteins

    PubMed Central

    2013-01-01

    Background Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins. Methods Inferred amino acid replacements are viewed through the prism of a single physicochemical property to determine the amount and direction of change caused by each replacement. This allows the calculation of the probability that the mean change in the single property associated with the amino acid replacements is equal to zero (H0: μ = 0; i.e., no net change) using a simple two-tailed t-test. Results Example data from calanoid and cyclopoid copepod cytochrome oxidase subunit I sequence pairs are presented to demonstrate how directional selection may be linked to major shifts in adaptive zones, and that convergent evolution at the whole organism level may be the result of convergent protein adaptations. Conclusions Rather than replace previous methods, this new method further complements existing methods to provide a holistic glimpse of how natural selection shapes protein structure and function over evolutionary time. PMID:24267049

  10. Integrating Pharmacophore into Membrane Molecular Dynamics Simulations to Improve Homology Modeling of G Protein-coupled Receptors with Ligand Selectivity: A2A Adenosine Receptor as an Example.

    PubMed

    Zeng, Lingxiao; Guan, Mengxin; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren

    2015-12-01

    Homology modeling has been applied to fill in the gap in experimental G protein-coupled receptors structure determination. However, achievement of G protein-coupled receptors homology models with ligand selectivity remains challenging due to structural diversity of G protein-coupled receptors. In this work, we propose a novel strategy by integrating pharmacophore and membrane molecular dynamics (MD) simulations to improve homology modeling of G protein-coupled receptors with ligand selectivity. To validate this integrated strategy, the A2A adenosine receptor (A2A AR), whose structures in both active and inactive states have been established, has been chosen as an example. We performed blind predictions of the active-state A2A AR structure based on the inactive-state structure and compared the performance of different refinement strategies. The blind prediction model combined with the integrated strategy identified ligand-receptor interactions and conformational changes of key structural elements related to the activation of A2 A AR, including (i) the movements of intracellular ends of TM3 and TM5/TM6; (ii) the opening of ionic lock; (iii) the movements of binding site residues. The integrated strategy of pharmacophore with molecular dynamics simulations can aid in the optimization in the identification of side chain conformations in receptor models. This strategy can be further investigated in homology modeling and expand its applicability to other G protein-coupled receptor modeling, which should aid in the discovery of more effective and selective G protein-coupled receptor ligands.

  11. 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.

  12. Model selection for geostatistical models.

    PubMed

    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 often ignored in the selection of explanatory variables, and this can influence model selection results. For example, the importance 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 traditional approach of ignoring spatial correlation in the selection of explanatory variables. These ideas are further demonstrated via a model for lizard abundance. We also apply 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. R software to implement the geostatistical model selection methods described in this paper is available in the Supplement.

  13. 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.

  14. Succination is Increased on Select Proteins in the Brainstem of the NADH dehydrogenase (ubiquinone) Fe-S protein 4 (Ndufs4) Knockout Mouse, a Model of Leigh Syndrome*

    PubMed Central

    Piroli, Gerardo G.; Manuel, Allison M.; Clapper, Anna C.; Walla, Michael D.; Baatz, John E.; Palmiter, Richard D.; Quintana, Albert; Frizzell, Norma

    2016-01-01

    Elevated fumarate concentrations as a result of Krebs cycle inhibition lead to increases in protein succination, an irreversible post-translational modification that occurs when fumarate reacts with cysteine residues to generate S-(2-succino)cysteine (2SC). Metabolic events that reduce NADH re-oxidation can block Krebs cycle activity; therefore we hypothesized that oxidative phosphorylation deficiencies, such as those observed in some mitochondrial diseases, would also lead to increased protein succination. Using the Ndufs4 knockout (Ndufs4 KO) mouse, a model of Leigh syndrome, we demonstrate for the first time that protein succination is increased in the brainstem (BS), particularly in the vestibular nucleus. Importantly, the brainstem is the most affected region exhibiting neurodegeneration and astrocyte and microglial proliferation, and these mice typically die of respiratory failure attributed to vestibular nucleus pathology. In contrast, no increases in protein succination were observed in the skeletal muscle, corresponding with the lack of muscle pathology observed in this model. 2D SDS-PAGE followed by immunoblotting for succinated proteins and MS/MS analysis of BS proteins allowed us to identify the voltage-dependent anion channels 1 and 2 as specific targets of succination in the Ndufs4 knockout. Using targeted mass spectrometry, Cys77 and Cys48 were identified as endogenous sites of succination in voltage-dependent anion channels 2. Given the important role of voltage-dependent anion channels isoforms in the exchange of ADP/ATP between the cytosol and the mitochondria, and the already decreased capacity for ATP synthesis in the Ndufs4 KO mice, we propose that the increased protein succination observed in the BS of these animals would further decrease the already compromised mitochondrial function. These data suggest that fumarate is a novel biochemical link that may contribute to the progression of the neuropathology in this mitochondrial disease model

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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

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

    PubMed Central

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

    2010-01-01

    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. PMID:20921233

  1. Chemical site-selective prenylation of proteins.

    PubMed

    Gamblin, David P; van Kasteren, Sander; Bernardes, Gonçalo J L; Chalker, Justin M; Oldham, Neil J; Fairbanks, Antony J; Davis, Benjamin G

    2008-06-01

    A direct thionation procedure allows conversion of allylic alcohols into the corresponding thiols, the products of which are immediately compatible with one-pot site-selective selenenyl sulfide mediated protein conjugation.

  2. 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.

  3. Viral cystatin evolution and three-dimensional structure modelling: A case of directional selection acting on a viral protein involved in a host-parasitoid interaction

    PubMed Central

    Serbielle, Céline; Chowdhury, Shafinaz; Pichon, Samuel; Dupas, Stéphane; Lesobre, Jérôme; Purisima, Enrico O; Drezen, Jean-Michel; Huguet, Elisabeth

    2008-01-01

    Background In pathogens, certain genes encoding proteins that directly interact with host defences coevolve with their host and are subject to positive selection. In the lepidopteran host-wasp parasitoid system, one of the most original strategies developed by the wasps to defeat host defences is the injection of a symbiotic polydnavirus at the same time as the wasp eggs. The virus is essential for wasp parasitism success since viral gene expression alters the immune system and development of the host. As a wasp mutualist symbiont, the virus is expected to exhibit a reduction in genome complexity and evolve under wasp phyletic constraints. However, as a lepidopteran host pathogenic symbiont, the virus is likely undergoing strong selective pressures for the acquisition of new functions by gene acquisition or duplication. To understand the constraints imposed by this particular system on virus evolution, we studied a polydnavirus gene family encoding cyteine protease inhibitors of the cystatin superfamily. Results We show that cystatins are the first bracovirus genes proven to be subject to strong positive selection within a host-parasitoid system. A generated three-dimensional model of Cotesia congregata bracovirus cystatin 1 provides a powerful framework to position positively selected residues and reveal that they are concentrated in the vicinity of actives sites which interact with cysteine proteases directly. In addition, phylogenetic analyses reveal two different cystatin forms which evolved under different selective constraints and are characterized by independent adaptive duplication events. Conclusion Positive selection acts to maintain cystatin gene duplications and induces directional divergence presumably to ensure the presence of efficient and adapted cystatin forms. Directional selection has acted on key cystatin active sites, suggesting that cystatins coevolve with their host target. We can strongly suggest that cystatins constitute major virulence

  4. Charged ultrafiltration membranes increase the selectivity of whey protein separations.

    PubMed

    Bhushan, S; Etzel, M R

    2009-04-01

    Ultrafiltration is widely used to concentrate proteins, but fractionation of one protein from another is much less common. This study examined the use of positively charged membranes to increase the selectivity of ultrafiltration and allow the fractionation of proteins from cheese whey. By adding a positive charge to ultrafiltration membranes, and adjusting the solution pH, it was possible to permeate proteins having little or no charge, such as glycomacropeptide, and retain proteins having a positive charge. Placing a charge on the membrane increased the selectivity by over 600% compared to using an uncharged membrane. The data were fit using the stagnant film model that relates the observed sieving coefficient to membrane parameters such as the flux, mass transfer coefficient, and membrane Peclet number. The model was a useful tool for data analysis and for the scale up of membrane separations for whey protein fractionation.

  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. Protein Model Database

    SciTech Connect

    Fidelis, K; Adzhubej, A; Kryshtafovych, A; Daniluk, P

    2005-02-23

    The phenomenal success of the genome sequencing projects reveals the power of completeness in revolutionizing biological science. Currently it is possible to sequence entire organisms at a time, allowing for a systemic rather than fractional view of their organization and the various genome-encoded functions. There is an international plan to move towards a similar goal in the area of protein structure. This will not be achieved by experiment alone, but rather by a combination of efforts in crystallography, NMR spectroscopy, and computational modeling. Only a small fraction of structures are expected to be identified experimentally, the remainder to be modeled. Presently there is no organized infrastructure to critically evaluate and present these data to the biological community. The goal of the Protein Model Database project is to create such infrastructure, including (1) public database of theoretically derived protein structures; (2) reliable annotation of protein model quality, (3) novel structure analysis tools, and (4) access to the highest quality modeling techniques available.

  7. 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

  8. Cytosolic selection systems to study protein stability.

    PubMed

    Malik, Ajamaluddin; Mueller-Schickert, Antje; Bardwell, James C A

    2014-12-01

    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.

  9. TSTMP: target selection for structural genomics of human transmembrane proteins

    PubMed Central

    Varga, Julia; Dobson, László; Reményi, István; Tusnády, Gábor E.

    2017-01-01

    The TSTMP database is designed to help the target selection of human transmembrane proteins for structural genomics projects and structure modeling studies. Currently, there are only 60 known 3D structures among the polytopic human transmembrane proteins and about a further 600 could be modeled using existing structures. Although there are a great number of human transmembrane protein structures left to be determined, surprisingly only a small fraction of these proteins have ‘selected’ (or above) status according to the current version the TargetDB/TargetTrack database. This figure is even worse regarding those transmembrane proteins that would contribute the most to the structural coverage of the human transmembrane proteome. The database was built by sorting out proteins from the human transmembrane proteome with known structure and searching for suitable model structures for the remaining proteins by combining the results of a state-of-the-art transmembrane specific fold recognition algorithm and a sequence similarity search algorithm. Proteins were searched for homologues among the human transmembrane proteins in order to select targets whose successful structure determination would lead to the best structural coverage of the human transmembrane proteome. The pipeline constructed for creating the TSTMP database guarantees to keep the database up-to-date. The database is available at http://tstmp.enzim.ttk.mta.hu. PMID:27924015

  10. Protein pharmacophore selection using hydration-site analysis

    PubMed Central

    Hu, Bingjie; Lill, Markus A.

    2012-01-01

    Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751

  11. 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…

  12. Selective Target Protein Degradation via Phthalimide Conjugation

    PubMed Central

    Winter, Georg E.; Buckley, Dennis L.; Paulk, Joshiawa; Roberts, Justin M.; Souza, Amanda; Dhe-Paganon, Sirano; Bradner, James E.

    2016-01-01

    Small-molecule antagonists disable discrete biochemical properties of protein targets. For multi-domain protein targets, the pharmacologic consequence of drug action is limited by selective disruption of one domain-specific activity. More broadly, target inhibition is kinetically limited by the durability and degree of target engagement. These features of traditional drug molecules are challenging to the development of inhibitors targeting transcription factors and chromatin-associated epigenetic proteins, which function as multi-domain biomolecular scaffolds and generally feature rapid association and dissociation kinetics. We therefore devised a chemical strategy to prompt ligand-dependent target protein degradation, via chemical conjugation with derivatized phthalimides that hijack the function of the Cereblon E3 ubiquitin ligase complex. Using this approach, we converted an acetyl-lysine competitive antagonist that displaces BET bromodomains from chromatin (JQ1) to a phthalimide-conjugated ligand that prompts immediate Cereblon-dependent BET protein degradation (dBET1). Expression proteomics confirms high specificity for BET family members BRD2, BRD3 and BRD4 among 7429 proteins detected. Degradation of BET bromodomains is associated with a more rapid and robust apoptotic response compared to bromodomain inhibition in primary human leukemic blasts, and dBET1 exhibits in vivo efficacy in a human leukemia xenograft. The reach of this approach is illustrated by a second series of probes that degrade the cytosolic signaling protein, FKBP12. Together, these findings identify a facile and general new strategy to control target protein stability, with implications for approaching previously intractable protein targets. PMID:25999370

  13. Toward an Optimal Approach for Variable Selection in Counter-Propagation Neural Networks: Modeling Protein-Tyrosine Kinase Inhibitory of Flavanoids Using Substituent Electronic Descriptors.

    PubMed

    Hemmateenejad, Bahram; Mehdipour, Ahmadreza; Deeb, Omar; Sanchooli, Mahmood; Miri, Ramin

    2011-12-01

    Counter propagation neural network (CPNN) is one of the attractive tools of classification in QSAR studies. A major obstacle in classification by CPNN is finding the best subset of variables. In this study, the performance of some different feature selection algorithms including F score-based ranking, eigenvalue ranking of PCs obtained from data set, Non-Error-Rate (NER) ranking of both descriptors and PCs, and 3-way handling of data, Parallel Factor Analysis (PARAFAC), was evaluated in order to find the best classification model. The methods were applied for modeling protein-tyrosine kinase inhibitory of some flavonoid derivatives using substituent electronic descriptors (SED) as novel source of electronic descriptors. The results showed that the best performance was achieved by F-score ranking while the NER ranking of principal components (PCs) showed very fluctuate results and the worst performance was belonging to PARAFAC-CPNN. Furthermore, comparison of results of these nonlinear algorithms with linear discriminate analysis method revealed better predictions by the former.

  14. Individual influence on model selection.

    PubMed

    Sterba, Sonya K; Pek, Jolynn

    2012-12-01

    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 of a single model in isolation has been often studied, case influence on model selection results is greatly underappreciated in psychology. This article introduces the issue of case influence on model selection and proposes 3 influence diagnostics for commonly used selection indices: the chi-square difference test, Bayesian information criterion, and Akaike's information criterion. These 3 diagnostics can be obtained simply from the byproducts of full information maximum likelihood estimation without heavy computational burden. We provide practical information on the interpretation and behavior of these diagnostics for applied researchers and provide software code to facilitate their use. Simulated and empirical examples involving different kinds of model comparison scenarios encountered in cross-sectional, longitudinal, and multilevel research as well as involving different kinds of outcome distributions illustrate the generality of the proposed diagnostics. An awareness of how cases influence model selection results is shown to aid researchers in understanding how representative their sample level results are at the case level.

  15. 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

  16. The anti-TNF-α antibody infliximab inhibits the expression of fat-transporter-protein FAT/CD36 in a selective hepatic-radiation mouse model.

    PubMed

    Martius, Gesa; Cameron, Silke; Rave-Fränk, Margret; Hess, Clemens F; Wolff, Hendrik A; Malik, Ihtzaz A

    2015-03-02

    Previously, we reported a radiation-induced inflammation triggering fat-accumulation through fatty-acid-translocase/cluster of differentiation protein 36 (FAT/CD36) in rat liver. Furthermore, inhibition of radiation-induced FAT/CD36-expression by anti-tumor necrosis factor-α (anti-TNF-α) (infliximab) was shown in vitro. The current study investigates fat-accumulation in a mouse-model of single-dose liver-irradiation (25-Gray) and the effect of anti-TNF-α-therapy on FAT/CD36 gene-expression. Mice livers were selectively irradiated in vivo in presence or absence of infliximab. Serum- and hepatic-triglycerides, mRNA, and protein were analyzed by colorimetric assays, RT-PCR, Immunofluorescence and Western-Blot, respectively. Sudan-staining was used demonstrating fat-accumulation in tissue. In mice livers, early (1-3 h) induction of TNF-α-expression, a pro-inflammatory cytokine, was observed. It was followed by elevated hepatic-triglyceride level (6-12 h), compared to sham-irradiated controls. In contrast, serum-triglyceride level was decreased at these time points. Similar to triglyceride level in mice livers, Sudan staining of liver cryosections showed a quick (6-12 h) increase of fat-droplets after irradiation. Furthermore, expression of fat-transporter-protein FAT/CD36 was increased at protein level caused by radiation or TNF-α. TNF-α-blockage by anti-TNF-α showed an early inhibition of radiation-induced FAT/CD36 expression in mice livers. Immunohistochemistry showed basolateral and cytoplasmic expression of FAT/CD36 in hepatocytes. Moreover, co-localization of FAT/CD36 was detected with α-smooth muscle actin (α-SMA+) cells and F4/80+ macrophages. In summary, hepatic-radiation triggers fat-accumulation in mice livers, involving acute-phase-processes. Accordingly, anti-TNF-α-therapy prevented early radiation-induced expression of FAT/CD36 in vivo.

  17. Selective sweeps in Cryptocercus woodroach antifungal proteins.

    PubMed

    Velenovsky, Joseph F; Kalisch, Jessica; Bulmer, Mark S

    2016-10-01

    We identified the antifungal gene termicin in three species of Cryptocercus woodroaches. Cryptocercus represents the closest living cockroach lineage of termites, which suggests that the antifungal role of termicin evolved prior to the divergence of termites from other cockroaches. An analysis of Cryptocercus termicin and two β-1,3-glucanase genes (GNBP1 and GNBP2), which appear to work synergistically with termicin in termites, revealed evidence of selection in these proteins. We identified the signature of past selective sweeps within GNBP2 from Cryptocercus punctulatus and Cryptocercus wrighti. The signature of past selective sweeps was also found within termicin from Cryptocercus punctulatus and Cryptocercus darwini. Our analysis further suggests a phenotypically identical variant of GNBP2 was maintained within Cryptocercus punctulatus, Cryptocercus wrighti, and Cryptocercus darwini while synonymous sites diverged. Cryptocercus termicin and GNBP2 appear to have experienced similar selective pressure to that of their termite orthologues in Reticulitermes. This selective pressure may be a result of ubiquitous entomopathogenic fungal pathogens such as Metarhizium. This study further reveals the similarities between Cryptocercus woodroaches and termites.

  18. Protein minimization by random fragmentation and selection.

    PubMed

    Rudgers, G W; Palzkill, T

    2001-07-01

    Protein-protein interactions are involved in most biological processes and are important targets for drug design. Over the past decade, there has been increased interest in the design of small molecules that mimic functional epitopes of protein inhibitors. BLIP is a 165 amino acid protein that is a potent inhibitor of TEM-1 beta-lactamase (K(i) = 0.1 nM). To aid in the development of new inhibitors of beta-lactamase, the gene encoding BLIP was randomly fragmented and DNA segments encoding peptides that retain the ability to bind TEM-1 beta-lactamase were isolated using phage display. The selected peptides revealed a common, overlapping region that includes BLIP residues C30-D49. Synthesis and binding analysis of the C30-D49 peptide indicate that this peptide inhibits TEM-1 beta-lactamase. Therefore, a peptide derivative of BLIP that has been reduced in size by 88% compared with wild-type BLIP retains the ability to bind and inhibit beta-lactamase.

  19. 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.

  20. Multiscale modeling of proteins.

    PubMed

    Tozzini, Valentina

    2010-02-16

    The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficiency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was

  1. Electrostatic selectivity in protein-nanoparticle interactions.

    PubMed

    Chen, Kaimin; Xu, Yisheng; Rana, Subinoy; Miranda, Oscar R; Dubin, Paul L; Rotello, Vincent M; Sun, Lianhong; Guo, Xuhong

    2011-07-11

    The binding of bovine serum albumin (BSA) and β-lactoglobulin (BLG) to TTMA (a cationic gold nanoparticle coupled to 3,6,9,12-tetraoxatricosan-1-aminium, 23-mercapto-N,N,N-trimethyl) was studied by high-resolution turbidimetry (to observe a critical pH for binding), dynamic light scattering (to monitor particle growth), and isothermal titration calorimetry (to measure binding energetics), all as a function of pH and ionic strength. Distinctively higher affinities observed for BLG versus BSA, despite the lower pI of the latter, were explained in terms of their different charge anisotropies, namely, the negative charge patch of BLG. To confirm this effect, we studied two isoforms of BLG that differ in only two amino acids. Significantly stronger binding to BLGA could be attributed to the presence of the additional aspartates in the negative charge domain for the BLG dimer, best portrayed in DelPhi. This selectivity decreases at low ionic strength, at which both isoforms bind well below pI. Selectivity increases with ionic strength for BLG versus BSA, which binds above pI. This result points to the diminished role of long-range repulsions for binding above pI. Dynamic light scattering reveals a tendency for higher-order aggregation for TTMA-BSA at pH above the pI of BSA, due to its ability to bridge nanoparticles. In contrast, soluble BLG-TTMA complexes were stable over a range of pH because the charge anisotropy of this protein at makes it unable to bridge nanoparticles. Finally, isothermal titration calorimetry shows endoenthalpic binding for all proteins: the higher affinity of TTMA for BLGA versus BLGB comes from a difference in the dominant entropy term.

  2. 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.

  3. Selective Refinement and Molecular Dynamics Ranking Selection of Near-native Protein Structures

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    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 remain problematic. To address these issues, we have developed a selective refinement protocol (SRP), and a molecular dynamics (MD) simulation based ranking method (MDR). In SRP the refinement of structures is accomplished by using the relax mode of the Rosetta software package, subject to specific constraints determined by the type and complexity of the target. The final best models are selected 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 Mufold-MD, our fully automated protein structure prediction server. Mufold-MD was one of the top servers in the CASP10 competition.

  4. 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

  5. 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…

  6. 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…

  7. 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.

  8. Identification of physicochemical selective pressure on protein encoding nucleotide sequences

    PubMed Central

    Wong, Wendy SW; Sainudiin, Raazesh; Nielsen, Rasmus

    2006-01-01

    Background Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC) and from the abalone sperm lysine. Conclusion Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties. PMID:16542458

  9. Selection responses for clinical mastitis and protein yield in two Norwegian dairy cattle selection experiments.

    PubMed

    Heringstad, B; Klemetsdal, G; Steine, T

    2003-09-01

    Inferences from two dairy cattle selection experiments, in which sires were selected from external sources, were drawn by using an animal model to analyze data from the entire population. The first selection experiment was carried out in the period from 1978 to 1989 and included groups selected for high milk production (HMP) and low milk production (LMP). Each year, the highest ranking proven sires for milk production, from the most recent group of Norwegian Dairy Cattle (NRF) test bulls, were selected and mated to the cows in the HMP group. A group of sires with low milk production indices from progeny testing in 1978 and 1979 were used as sires in the LMP group during the entire experiment. The second selection experiment, which started in 1989, included one high protein yield (HPY) group and one low clinical mastitis (LCM) group. The highest ranking proven NRF sires for protein yield and mastitis resistance were selected each year from the most recent group of progeny tested bulls and used as sires in the HPY and LCM groups, respectively. Genetic trends for protein yield were positive (as expected) for HMP and HPY cows, and negative for LMP and LCM cows. Estimates of annual genetic trends for clinical mastitis were +0.23, -0.02, +0.04, and -0.91% per year for HMP, LMP, HPY, and LCM cows, respectively. The difference in genetic trend of clinical mastitis between HMP and HPY groups, both selected for increased milk production, reflects the gradual change in the NRF breeding objective towards more weight on health relative to milk over the last 20 yr. After four cow generations, the genetic difference in mastitis between HMP and LMP group cows was 3.1% clinical mastitis, a correlated response to selection for increased milk production. The genetic difference between LCM and HPY cows of 8.6% clinical mastitis after three cow generations is mainly a result of direct selection against clinical mastitis in the LCM group. In the NRF population, an approximately flat

  10. Protein structure and ionic selectivity in calcium channels: Selectivity filter size, not shape, matters

    PubMed Central

    Malasics, Attila; Gillespie, Dirk; Nonner, Wolfgang; Henderson, Douglas; Eisenberg, Bob; Boda, Dezső

    2009-01-01

    Calcium channels have highly charged selectivity filters (4 COO− groups) that attract cations in to balance this charge and minimize free energy, forcing the cations (Na+ and Ca2+) to compete for space in the filter. A reduced model was developed to better understand the mechanism of ion selectivity in calcium channels. The charge/space competition (CSC) mechanism implies that Ca2+ is more efficient in balancing the charge of the filter because it provides twice the charge as Na+ while occupying the same space. The CSC mechanism further implies that the main determinant of Ca2+ vs. Na+ selectivity is the density of charged particles in the selectivity filter, i.e., the volume of the filter (after fixing the number of charged groups in the filter). In this paper we test this hypothesis by changing filter length and/or radius (shape) of the cylindrical selectivity filter of our reduced model. We show that varying volume and shape together has substantially stronger effects than varying shape alone with volume fixed. Our simulations show the importance of depletion zones of ions in determining channel conductance calculated with the integrated Nernst-Planck equation. We show that confining the protein side chains with soft or hard walls does not influence selectivity. PMID:19818330

  11. The importance of protein in leaf selection of folivorous primates.

    PubMed

    Ganzhorn, Joerg U; Arrigo-Nelson, Summer J; Carrai, Valentina; Chalise, Mukesh K; Donati, Giuseppe; Droescher, Iris; Eppley, Timothy M; Irwin, Mitchell T; Koch, Flávia; Koenig, Andreas; Kowalewski, Martin M; Mowry, Christopher B; Patel, Erik R; Pichon, Claire; Ralison, Jose; Reisdorff, Christoph; Simmen, Bruno; Stalenberg, Eleanor; Starrs, Danswell; Terboven, Juana; Wright, Patricia C; Foley, William J

    2016-04-19

    Protein limitation has been considered a key factor in hypotheses on the evolution of life history and animal communities, suggesting that animals should prioritize protein in their food choice. This contrasts with the limited support that food selection studies have provided for such a priority in nonhuman primates, particularly for folivores. Here, we suggest that this discrepancy can be resolved if folivores only need to select for high protein leaves when average protein concentration in the habitat is low. To test the prediction, we applied meta-analyses to analyze published and unpublished results of food selection for protein and fiber concentrations from 24 studies (some with multiple species) of folivorous primates. To counter potential methodological flaws, we differentiated between methods analyzing total nitrogen and soluble protein concentrations. We used a meta-analysis to test for the effect of protein on food selection by primates and found a significant effect of soluble protein concentrations, but a non-significant effect for total nitrogen. Furthermore, selection for soluble protein was reinforced in forests where protein was less available. Selection for low fiber content was significant but unrelated to the fiber concentrations in representative leaf samples of a given forest. There was no relationship (either negative or positive) between the concentration of protein and fiber in the food or in representative samples of leaves. Overall our study suggests that protein selection is influenced by the protein availability in the environment, explaining the sometimes contradictory results in previous studies on protein selection. Am. J. Primatol. © 2016 Wiley Periodicals, Inc.

  12. 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.

  13. Model selection for modified gravity.

    PubMed

    Kitching, T D; Simpson, F; Heavens, A F; Taylor, A N

    2011-12-28

    In this article, we review model selection predictions for modified gravity scenarios as an explanation for the observed acceleration of the expansion history of the Universe. We present analytical procedures for calculating expected Bayesian evidence values in two cases: (i) that modified gravity is a simple parametrized extension of general relativity (GR; two nested models), such that a Bayes' factor can be calculated, and (ii) that we have a class of non-nested models where a rank-ordering of evidence values is required. We show that, in the case of a minimal modified gravity parametrization, we can expect large area photometric and spectroscopic surveys, using three-dimensional cosmic shear and baryonic acoustic oscillations, to 'decisively' distinguish modified gravity models over GR (or vice versa), with odds of ≫1:100. It is apparent that the potential discovery space for modified gravity models is large, even in a simple extension to gravity models, where Newton's constant G is allowed to vary as a function of time and length scale. On the time and length scales where dark energy dominates, it is only through large-scale cosmological experiments that we can hope to understand the nature of gravity.

  14. Model selection for pion photoproduction

    NASA Astrophysics Data System (ADS)

    Landay, J.; Döring, M.; Fernández-Ramírez, C.; Hu, B.; Molina, R.

    2017-01-01

    Partial-wave analysis of meson and photon-induced reactions is needed to enable the comparison of many theoretical approaches to data. In both energy-dependent and independent parametrizations of partial waves, the selection of the model amplitude is crucial. Principles of the S matrix are implemented to a different degree in different approaches; but a many times overlooked aspect concerns the selection of undetermined coefficients and functional forms for fitting, leading to a minimal yet sufficient parametrization. We present an analysis of low-energy neutral pion photoproduction using the least absolute shrinkage and selection operator (LASSO) in combination with criteria from information theory and K -fold cross validation. These methods are not yet widely known in the analysis of excited hadrons but will become relevant in the era of precision spectroscopy. The principle is first illustrated with synthetic data; then, its feasibility for real data is demonstrated by analyzing the latest available measurements of differential cross sections (d σ /d Ω ), photon-beam asymmetries (Σ ), and target asymmetry differential cross sections (d σT/d ≡T d σ /d Ω ) in the low-energy regime.

  15. Model selection for pion photoproduction

    DOE PAGES

    Landay, J.; Doring, M.; Fernandez-Ramirez, C.; ...

    2017-01-12

    Partial-wave analysis of meson and photon-induced reactions is needed to enable the comparison of many theoretical approaches to data. In both energy-dependent and independent parametrizations of partial waves, the selection of the model amplitude is crucial. Principles of the S matrix are implemented to a different degree in different approaches; but a many times overlooked aspect concerns the selection of undetermined coefficients and functional forms for fitting, leading to a minimal yet sufficient parametrization. We present an analysis of low-energy neutral pion photoproduction using the least absolute shrinkage and selection operator (LASSO) in combination with criteria from information theory andmore » K-fold cross validation. These methods are not yet widely known in the analysis of excited hadrons but will become relevant in the era of precision spectroscopy. As a result, the principle is first illustrated with synthetic data; then, its feasibility for real data is demonstrated by analyzing the latest available measurements of differential cross sections (dσ/dΩ), photon-beam asymmetries (Σ), and target asymmetry differential cross sections (dσT/d≡Tdσ/dΩ) in the low-energy regime.« less

  16. 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.

  17. Molecular modelling of protein-protein/protein-solvent interactions

    NASA Astrophysics Data System (ADS)

    Luchko, Tyler

    The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule

  18. 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.

  19. 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

  20. Selective incorporation of membrane proteins into proteoliposomes of different compositions.

    PubMed

    Eytan, G D; Racker, E

    1977-05-25

    1. Cytochrome oxidase was incorporated into preformed liposomes containing phosphatidylserine. When confronted with a mixture of liposomes, some containing phosphatidylserine and some without it, the enzyme was incorporated only into the phosphatidylserine-containing liposomes. 2. The hydrophobic proteins of the oligomycin-sensitive ATPase incubated in the presence of a mixture of liposomes with and without cytochrome oxidase were preferentially incorporated into cytochrome oxidase-containing liposomes. This selectivity was abolished by either cytochrome c or ascorbate. 3. Cytochrome oxidase incubated in the presence of a mixture of liposomes with and without the hydrophobic proteins of the ATPase was preferentially incorporated into liposomes that did not contain the hydrophobic proteins. 4. Cytochrome oxidase and the oligomycin-sensitive ATPase were preferentially incorporated into pure liposomes over bacteriorhodopsin-containing vesicles. 5. Reduced coenzyme Q (QH2)-cytochrome c reductase was incorporated randomly when incubated in the presence of a mixture of pure liposomes and liposomes containing the hydrophobic proteins of the ATPase complex. 6. The significance of the incorporation procedure as a model for membrane biogenesis is discussed.

  1. 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.

  2. 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.

  3. 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.

  4. Mitochondrial genomes are retained by selective constraints on protein targeting

    PubMed Central

    Björkholm, Patrik; Harish, Ajith; Hagström, Erik; Ernst, Andreas M.; Andersson, Siv G. E.

    2015-01-01

    Mitochondria are energy-producing organelles in eukaryotic cells considered to be of bacterial origin. The mitochondrial genome has evolved under selection for minimization of gene content, yet it is not known why not all mitochondrial genes have been transferred to the nuclear genome. Here, we predict that hydrophobic membrane proteins encoded by the mitochondrial genomes would be recognized by the signal recognition particle and targeted to the endoplasmic reticulum if they were nuclear-encoded and translated in the cytoplasm. Expression of the mitochondrially encoded proteins Cytochrome oxidase subunit 1, Apocytochrome b, and ATP synthase subunit 6 in the cytoplasm of HeLa cells confirms export to the endoplasmic reticulum. To examine the extent to which the mitochondrial proteome is driven by selective constraints within the eukaryotic cell, we investigated the occurrence of mitochondrial protein domains in bacteria and eukaryotes. The accessory protein domains of the oxidative phosphorylation system are unique to mitochondria, indicating the evolution of new protein folds. Most of the identified domains in the accessory proteins of the ribosome are also found in eukaryotic proteins of other functions and locations. Overall, one-third of the protein domains identified in mitochondrial proteins are only rarely found in bacteria. We conclude that the mitochondrial genome has been maintained to ensure the correct localization of highly hydrophobic membrane proteins. Taken together, the results suggest that selective constraints on the eukaryotic cell have played a major role in modulating the evolution of the mitochondrial genome and proteome. PMID:26195779

  5. Hierarchical modeling of protein interactions.

    PubMed

    Kurcinski, Mateusz; Kolinski, Andrzej

    2007-07-01

    A novel approach to hierarchical peptide-protein and protein-protein docking is described and evaluated. Modeling procedure starts from a reduced space representation of proteins and peptides. Polypeptide chains are represented by strings of alpha-carbon beads restricted to a fine-mesh cubic lattice. Side chains are represented by up to two centers of interactions, corresponding to beta-carbons and the centers of mass of the remaining portions of the side groups, respectively. Additional pseudoatoms are located in the centers of the virtual bonds connecting consecutive alpha carbons. These pseudoatoms support a model of main-chain hydrogen bonds. Docking starts from a collection of random configurations of modeled molecules. Interacting molecules are flexible; however, higher accuracy models are obtained when the conformational freedom of one (the larger one) of the assembling molecules is limited by a set of weak distance restraints extracted from the experimental (or theoretically predicted) structures. Sampling is done by means of Replica Exchange Monte Carlo method. Afterwards, the set of obtained structures is subject to a hierarchical clustering. Then, the centroids of the resulting clusters are used as scaffolds for the reconstruction of the atomic details. Finally, the all-atom models are energy minimized and scored using classical tools of molecular mechanics. The method is tested on a set of macromolecular assemblies consisting of proteins and peptides. It is demonstrated that the proposed approach to the flexible docking could be successfully applied to prediction of protein-peptide and protein-protein interactions. The obtained models are almost always qualitatively correct, although usually of relatively low (or moderate) resolution. In spite of this limitation, the proposed method opens new possibilities of computational studies of macromolecular recognition and mechanisms of assembly of macromolecular complexes.

  6. Selective sorting of alpha-granule proteins.

    PubMed

    Italiano, J E; Battinelli, E M

    2009-07-01

    One of the main functions of blood platelets is to secrete a variety of substances that can modify a developing thrombus, regulate the growth of the vasculature, promote wound repair, and contribute to cell-adhesive events. A majority of this vast array of secreted proteins are stored in alpha-granules. Until recently, it was assumed that platelets contained one homogeneous population of alpha-granules that undergo complete de-granulation during platelet activation. This review focuses on the mechanisms of alpha-granule biogenesis and secretion, with a particular emphasis on recent findings that clearly demonstrate that platelets contain distinct subpopulations of alpha-granules that undergo differential release during activation. We consider the implications of this new paradigm of platelet secretion, discuss mechanisms of alpha-granule biogenesis, and review the molecular basis of transport and delivery of alpha-granules to assembling platelets.

  7. 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...

  8. Protein purification by polyelectrolyte coacervation: influence of protein charge anisotropy on selectivity.

    PubMed

    Xu, Yisheng; Mazzawi, Malek; Chen, Kaimin; Sun, Lianhong; Dubin, Paul L

    2011-05-09

    The effect of polyelectrolyte binding affinity on selective coacervation of proteins with the cationic polyelectrolyte, poly(diallyldimethylammonium chloride) (PDADMAC), was investigated for bovine serum albumin/β-lactoglobulin (BSA/BLG) and for the isoforms BLG-A/BLG-B. High-sensitivity turbidimetric titrations were used to define conditions of complex formation and coacervation (pH(c) and pH(ϕ), respectively) as a function of ionic strength. The resultant phase boundaries, essential for the choice of conditions for selective coacervation for the chosen protein pairs, are nonmonotonic with respect to ionic strength, for both pH(c) and pH(ϕ). These results are explained in the context of short-range attraction/long-range repulsion governing initial protein binding "on the wrong side of pI" and also subsequent phase separation due to charge neutralization. The stronger binding of BLG despite its higher isoelectric point, inferred from lower pH(c), is shown to result from the negative "charge patch" on BLG, absent for BSA, as visualized via computer modeling (DelPhi). The higher affinity of BLG versus BSA was also confirmed by isothermal titration calorimetry (ITC). The relative values of pH(ϕ) for the two proteins show complex salt dependence so that the choice of ionic strength determines the order of coacervation, whereas the choice of pH controls the yield of the target protein. Coacervation at I = 100 mM, pH 7, of BLG from a 1:1 (w/w) mixture with BSA was shown by SEC to provide 90% purity of BLG with a 20-fold increase in concentration. Ultrafiltration was shown to remove effectively the polymer from the target protein. The relationship between protein charge anisotropy and binding affinity and between binding affinity and selective coacervation, inferred from the results for BLG/BSA, was tested using the isoforms of BLG. Substitution of glycine in BLG-B by aspartate in BLG-A lowers pH(c) by 0.2, as anticipated on the basis of DelPhi modeling. The stronger

  9. Mitotic apparatus: the selective extraction of protein with mild acid.

    PubMed

    Bibring, T; Baxandall, J

    1968-07-26

    The treatment of isolated mitotic apparatus with mild (pH 3) hydrochloric acid results in the extraction of less than 10 percent of its protein, accompanied by the selective morphological disappearance of the microtubules. The same extraction can be shown to dissolve outer doublet microtubules from sperm flagella. A protein with points of similarity to the flagellar microtubule protein is the major component of the extract from mitotic apparatus.

  10. Estimation of Absolute Protein Quantities of Unlabeled Samples by Selected Reaction Monitoring Mass Spectrometry*

    PubMed Central

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

    2012-01-01

    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 R2 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

  11. Selected Logistics Models and Techniques.

    DTIC Science & Technology

    1984-09-01

    Programmable Calculator LCC...Program 27 TI-59 Programmable Calculator LCC Model 30 Unmanned Spacecraft Cost Model 31 iv I: TABLE OF CONTENTS (CONT’D) (Subject Index) LOGISTICS...34"" - % - "° > - " ° .° - " .’ > -% > ]*° - LOGISTICS ANALYSIS MODEL/TECHNIQUE DATA MODEL/TECHNIQUE NAME: TI-59 Programmable Calculator LCC Model TYPE MODEL: Cost Estimating DEVELOPED BY:

  12. 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.

  13. A sliding selectivity scale for lipid binding to membrane proteins

    PubMed Central

    Landreh, Michael; Marty, Michael T.; Gault, Joseph; Robinson, Carol V.

    2017-01-01

    Biological membranes form barriers that are essential for cellular integrity and compartmentalisation. Proteins that reside in the membrane have co-evolved with their hydrophobic lipid environment which serves as a solvent for proteins with very diverse requirements. As a result, membrane protein-lipid interactions range from completely non-selective to highly discriminating. Mass spectrometry (MS), in combination with X-ray crystallography and molecular dynamics simulations, enables us to monitor how lipids interact with intact membrane protein complexes and assess their effects on structure and dynamics. Recent studies illustrate the ability to differentiate specific lipid binding, preferential interactions with lipid subsets, and nonselective annular contacts. In this review, we consider the biological implications of different lipid-binding scenarios and propose that binding occurs on a sliding selectivity scale, in line with the view of biological membranes as facilitators of dynamic protein and lipid organization. PMID:27155089

  14. SWISS-MODEL: an automated protein homology-modeling server

    PubMed Central

    Schwede, Torsten; Kopp, Jürgen; Guex, Nicolas; Peitsch, Manuel C.

    2003-01-01

    SWISS-MODEL (http://swissmodel.expasy.org) is a server for automated comparative modeling of three-dimensional (3D) protein structures. It pioneered the field of automated modeling starting in 1993 and is the most widely-used free web-based automated modeling facility today. In 2002 the server computed 120 000 user requests for 3D protein models. SWISS-MODEL provides several levels of user interaction through its World Wide Web interface: in the ‘first approach mode’ only an amino acid sequence of a protein is submitted to build a 3D model. Template selection, alignment and model building are done completely automated by the server. In the ‘alignment mode’, the modeling process is based on a user-defined target-template alignment. Complex modeling tasks can be handled with the ‘project mode’ using DeepView (Swiss-PdbViewer), an integrated sequence-to-structure workbench. All models are sent back via email with a detailed modeling report. WhatCheck analyses and ANOLEA evaluations are provided optionally. The reliability of SWISS-MODEL is continuously evaluated in the EVA-CM project. The SWISS-MODEL server is under constant development to improve the successful implementation of expert knowledge into an easy-to-use server. PMID:12824332

  15. 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.

  16. 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…

  17. 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.

  18. Variable Selection in Semiparametric Regression Modeling.

    PubMed

    Li, Runze; Liang, Hua

    2008-01-01

    In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and select significant variables for parametric portion. Thus, it is much more challenging than that for parametric models such as linear models and generalized linear models because traditional variable selection procedures including stepwise regression and the best subset selection require model selection to nonparametric components for each submodel. This leads to very heavy computational burden. In this paper, we propose a class of variable selection procedures for semiparametric regression models using nonconcave penalized likelihood. The newly proposed procedures are distinguished from the traditional ones in that they delete insignificant variables and estimate the coefficients of significant variables simultaneously. This allows us to establish the sampling properties of the resulting estimate. We first establish the rate of convergence of the resulting estimate. With proper choices of penalty functions and regularization parameters, we then establish the asymptotic normality of the resulting estimate, and further demonstrate that the proposed procedures perform as well as an oracle procedure. Semiparametric generalized likelihood ratio test is proposed to select significant variables in the nonparametric component. We investigate the asymptotic behavior of the proposed test and demonstrate its limiting null distribution follows a chi-squared distribution, which is independent of the nuisance parameters. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedures.

  19. 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.

  20. 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.

  1. MODEL SELECTION FOR SPECTROPOLARIMETRIC INVERSIONS

    SciTech Connect

    Asensio Ramos, A.; Manso Sainz, R.; Martinez Gonzalez, M. J.; Socas-Navarro, H.; Viticchie, B.

    2012-04-01

    Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an objective way of comparing models has, sometimes, led to opposing views of the solar magnetism because the inferred physical scenarios are essentially different. We present the first quantitative model comparison based on the computation of the Bayesian evidence ratios for spectropolarimetric observations. Our results show that there is not a single model appropriate for all profiles simultaneously. Data with moderate signal-to-noise ratios (S/Ns) favor models without gradients along the line of sight. If the observations show clear circular and linear polarization signals above the noise level, models with gradients along the line are preferred. As a general rule, observations with large S/Ns favor more complex models. We demonstrate that the evidence ratios correlate well with simple proxies. Therefore, we propose to calculate these proxies when carrying out standard least-squares inversions to allow for model comparison in the future.

  2. 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

  3. 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

    2015-11-30

    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.

  4. 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.

  5. An Economic Model for Selective Admissions

    ERIC Educational Resources Information Center

    Haglund, Alma

    1978-01-01

    The author presents an economic model for selective admissions to postsecondary nursing programs. Primary determinants of the admissions model are employment needs, availability of educational resources, and personal resources (ability and learning potential). As there are more applicants than resources, selective admission practices are…

  6. 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…

  7. Estimating the Distribution of Selection Coefficients from Phylogenetic Data Using Sitewise Mutation-Selection Models

    PubMed Central

    Tamuri, Asif U.; dos Reis, Mario; Goldstein, Richard A.

    2012-01-01

    Estimation of the distribution of selection coefficients of mutations is a long-standing issue in molecular evolution. In addition to population-based methods, the distribution can be estimated from DNA sequence data by phylogenetic-based models. Previous models have generally found unimodal distributions where the probability mass is concentrated between mildly deleterious and nearly neutral mutations. Here we use a sitewise mutation–selection phylogenetic model to estimate the distribution of selection coefficients among novel and fixed mutations (substitutions) in a data set of 244 mammalian mitochondrial genomes and a set of 401 PB2 proteins from influenza. We find a bimodal distribution of selection coefficients for novel mutations in both the mitochondrial data set and for the influenza protein evolving in its natural reservoir, birds. Most of the mutations are strongly deleterious with the rest of the probability mass concentrated around mildly deleterious to neutral mutations. The distribution of the coefficients among substitutions is unimodal and symmetrical around nearly neutral substitutions for both data sets at adaptive equilibrium. About 0.5% of the nonsynonymous mutations and 14% of the nonsynonymous substitutions in the mitochondrial proteins are advantageous, with 0.5% and 24% observed for the influenza protein. Following a host shift of influenza from birds to humans, however, we find among novel mutations in PB2 a trimodal distribution with a small mode of advantageous mutations. PMID:22209901

  8. Engineering A-kinase anchoring protein (AKAP)-selective regulatory subunits of protein kinase A (PKA) through structure-based phage selection.

    PubMed

    Gold, Matthew G; Fowler, Douglas M; Means, Christopher K; Pawson, Catherine T; Stephany, Jason J; Langeberg, Lorene K; Fields, Stanley; Scott, John D

    2013-06-14

    PKA is retained within distinct subcellular environments by the association of its regulatory type II (RII) subunits with A-kinase anchoring proteins (AKAPs). Conventional reagents that universally disrupt PKA anchoring are patterned after a conserved AKAP motif. We introduce a phage selection procedure that exploits high-resolution structural information to engineer RII mutants that are selective for a particular AKAP. Selective RII (RSelect) sequences were obtained for eight AKAPs following competitive selection screening. Biochemical and cell-based experiments validated the efficacy of RSelect proteins for AKAP2 and AKAP18. These engineered proteins represent a new class of reagents that can be used to dissect the contributions of different AKAP-targeted pools of PKA. Molecular modeling and high-throughput sequencing analyses revealed the molecular basis of AKAP-selective interactions and shed new light on native RII-AKAP interactions. We propose that this structure-directed evolution strategy might be generally applicable for the investigation of other protein interaction surfaces.

  9. Modeling HIV-1 Drug Resistance as Episodic Directional Selection

    PubMed Central

    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. PMID:22589711

  10. Estimation and Accuracy after Model Selection

    PubMed Central

    Efron, Bradley

    2013-01-01

    Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consider bootstrap methods for computing standard errors and confidence intervals that take model selection into account. The methodology involves bagging, also known as bootstrap smoothing, to tame the erratic discontinuities of selection-based estimators. A useful new formula for the accuracy of bagging then provides standard errors for the smoothed estimators. Two examples, nonparametric and parametric, are carried through in detail: a regression model where the choice of degree (linear, quadratic, cubic, …) is determined by the Cp criterion, and a Lasso-based estimation problem. PMID:25346558

  11. Environment-sensitive amphiphilic fluorophore for selective sensing of protein.

    PubMed

    Ojha, Bimlesh; Das, Gopal

    2011-04-01

    Here we report the selective sensing of BSA (bovine serum albumin) by 8-(alkoxy)quinoline-based fluorescent probes, via non-covalent interactions. The weak fluorescence of these probes in aqueous solution showed a dramatic increase in quantum yield and lifetime upon binding with BSA, while the responses to various other proteins/enzymes used were negligible under similar experimental conditions. The emission of the probe is affected by the interplay with BSA but not with tryptophan amino acid suggesting that the microenvironment created by the macromolecule induces some change in their excited-state properties. Binding site assignment by a known site-selective binding ligand enabled us to conclude that the compounds predominantly bind at site I of BSA. The changes in fluorescence intensity and the position of emission maxima of compounds in presence of BSA along with the increase in steady state anisotropy values well reflect the nature of binding and location of the probe inside the protein environment. Compounds interact with BSA efficiently and exhibit site selectivity and thus have the potentiality to serve as an efficient and selective sensor of protein.

  12. Analytical lessons learned from selected therapeutic protein drug comparability studies.

    PubMed

    Federici, Marcia; Lubiniecki, Anthony; Manikwar, Prakash; Volkin, David B

    2013-05-01

    The successful implementation of process and product changes for a therapeutic protein drug, both during clinical development and after commercialization, requires a detailed evaluation of their impact on the protein's structure and biological functionality. This analysis is called a comparability exercise and includes a data driven assessment of biochemical equivalence and biological characterization using a cadre of analytical methodologies. This review focuses on describing analytical results and lessons learned from selected published therapeutic protein comparability case studies both for bulk drug substance and final drug product. An overview of the currently available analytical methodologies typically used is presented as well as a discussion of new emerging analytical techniques. The potential utility of several novel analytical approaches to comparability studies is discussed including distribution and stability of protein drugs in vivo, and enhanced evaluation of higher-order protein structure in actual formulations using hydrogen/deuterium exchange mass spectrometry, two-dimensional nuclear magnetic resonance fingerprinting or empirical phase diagrams. In addition, new methods for detecting and characterizing protein aggregates and particles are presented as these degradants are of current industry-wide concern. The critical role that analytical methodologies play in elucidating the structure-function relationships for therapeutic protein products during the overall assessment of comparability is discussed.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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…

  18. Objective Bayesian model selection for Cox regression.

    PubMed

    Held, Leonhard; Gravestock, Isaac; Sabanés Bové, Daniel

    2016-12-20

    There is now a large literature on objective Bayesian model selection in the linear model based on the g-prior. The methodology has been recently extended to generalized linear models using test-based Bayes factors. In this paper, we show that test-based Bayes factors can also be applied to the Cox proportional hazards model. If the goal is to select a single model, then both the maximum a posteriori and the median probability model can be calculated. For clinical prediction of survival, we shrink the model-specific log hazard ratio estimates with subsequent calculation of the Breslow estimate of the cumulative baseline hazard function. A Bayesian model average can also be employed. We illustrate the proposed methodology with the analysis of survival data on primary biliary cirrhosis patients and the development of a clinical prediction model for future cardiovascular events based on data from the Second Manifestations of ARTerial disease (SMART) cohort study. Cross-validation is applied to compare the predictive performance with alternative model selection approaches based on Harrell's c-Index, the calibration slope and the integrated Brier score. Finally, a novel application of Bayesian variable selection to optimal conditional prediction via landmarking is described. Copyright © 2016 John Wiley & Sons, Ltd.

  19. Image Modeling and Enhancement via Structured Sparse Model Selection

    DTIC Science & Technology

    2010-01-01

    signal estimation is then calculated with the selected model. The model selection leads to a guaranteed near optimal denoising estimator. The degree...are adapted to the image of interest and are computed with a simple and fast procedure. State-of-the-art results are shown in image denoising ...deblurring, and inpainting. Index Terms— Model selection, structured sparsity, best basis, denoising , deblurring, inpainting 1. INTRODUCTION Image enhancement

  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. Screening of selective histone deacetylase inhibitors by proteochemometric modeling

    PubMed Central

    2012-01-01

    Background Histone deacetylase (HDAC) is a novel target for the treatment of cancer and it can be classified into three classes, i.e., classes I, II, and IV. The inhibitors selectively targeting individual HDAC have been proved to be the better candidate antitumor drugs. To screen selective HDAC inhibitors, several proteochemometric (PCM) models based on different combinations of three kinds of protein descriptors, two kinds of ligand descriptors and multiplication cross-terms were constructed in our study. Results The results show that structure similarity descriptors are better than sequence similarity descriptors and geometry descriptors in the leftacterization of HDACs. Furthermore, the predictive ability was not improved by introducing the cross-terms in our models. Finally, a best PCM model based on protein structure similarity descriptors and 32-dimensional general descriptors was derived (R2 = 0.9897, Qtest2 = 0.7542), which shows a powerful ability to screen selective HDAC inhibitors. Conclusions Our best model not only predict the activities of inhibitors for each HDAC isoform, but also screen and distinguish class-selective inhibitors and even more isoform-selective inhibitors, thus it provides a potential way to discover or design novel candidate antitumor drugs with reduced side effect. PMID:22913517

  2. Evolution of the folding ability of proteins through functional selection

    PubMed Central

    Saito, Seiji; Sasai, Masaki; Yomo, Tetsuya

    1997-01-01

    An evolutionary process is simulated with a simple spin-glass-like model of proteins to examine the origin of folding ability. At each generation, sequences are randomly mutated and subjected to a simulation of the folding process based on the model. According to the frequency of local configurations at the active sites, sequences are selected and passed to the next generation. After a few hundred generations, a sequence capable of folding globally into a native conformation emerges. Moreover, the selected sequence has a distinct energy minimum and an anisotropic funnel on the energy surface, which are the imperative features for fast folding of proteins. The proposed model reveals that the functional selection on the local configurations leads a sequence to fold globally into a conformation at a faster rate. PMID:9326608

  3. Structural basis of PROTAC cooperative recognition for selective protein degradation.

    PubMed

    Gadd, Morgan S; Testa, Andrea; Lucas, Xavier; Chan, Kwok-Ho; Chen, Wenzhang; Lamont, Douglas J; Zengerle, Michael; Ciulli, Alessio

    2017-03-13

    Inducing macromolecular interactions with small molecules to activate cellular signaling is a challenging goal. PROTACs (proteolysis-targeting chimeras) are bifunctional molecules that recruit a target protein in proximity to an E3 ubiquitin ligase to trigger protein degradation. Structural elucidation of the key ternary ligase-PROTAC-target species and its impact on target degradation selectivity remain elusive. We solved the crystal structure of Brd4 degrader MZ1 in complex with human VHL and the Brd4 bromodomain (Brd4(BD2)). The ligand folds into itself to allow formation of specific intermolecular interactions in the ternary complex. Isothermal titration calorimetry studies, supported by surface mutagenesis and proximity assays, are consistent with pronounced cooperative formation of ternary complexes with Brd4(BD2). Structure-based-designed compound AT1 exhibits highly selective depletion of Brd4 in cells. Our results elucidate how PROTAC-induced de novo contacts dictate preferential recruitment of a target protein into a stable and cooperative complex with an E3 ligase for selective degradation.

  4. Anti-idiotypic protein domains selected from protein A-based affibody libraries.

    PubMed

    Eklund, Malin; Axelsson, Lars; Uhlén, Mathias; Nygren, Per-Ake

    2002-08-15

    Three pairs of small protein domains showing binding behavior in analogy with anti-idiotypic antibodies have been selected using phage display technology. From an affibody protein library constructed by combinatorial variegation of the Fc binding surface of the 58 residue staphylococcal protein A (SPA)-derived domain Z, affibody variants have been selected to the parental SPA scaffold and to two earlier identified SPA-derived affibodies. One selected affibody (Z(SPA-1)) was shown to recognize each of the five domains of wild-type SPA with dissociation constants (K(D)) in the micromolar range. The binding of the Z(SPA-1) affibody to its parental structure was shown to involve the Fc binding site of SPA, while the Fab-binding site was not involved. Similarly, affibodies showing anti-idiotypic binding characteristics were also obtained when affibodies previously selected for binding to Taq DNA polymerase and human IgA, respectively, were used as targets for selections. The potential applications for these types of affinity pairs were exemplified by one-step protein recovery using affinity chromatography employing the specific interactions between the respective protein pair members. These experiments included the purification of the Z(SPA-1) affibody from a total Escherichia coli cell lysate using protein A-Sepharose, suggesting that this protein A/antiprotein A affinity pair could provide a basis for novel affinity gene fusion systems. The use of this type of small, robust, and easily expressed anti-idiotypic affibody pair for affinity technology applications, including self-assembled protein networks, is discussed.

  5. Two mechanisms of ion selectivity in protein binding sites.

    PubMed

    Yu, Haibo; Noskov, Sergei Yu; Roux, Benoît

    2010-11-23

    A theoretical framework is presented to clarify the molecular determinants of ion selectivity in protein binding sites. The relative free energy of a bound ion is expressed in terms of the main coordinating ligands coupled to an effective potential of mean force representing the influence of the rest of the protein. The latter is separated into two main contributions. The first includes all the forces keeping the ion and the coordinating ligands confined to a microscopic subvolume but does not prevent the ligands from adapting to a smaller or larger ion. The second regroups all the remaining forces that control the precise geometry of the coordinating ligands best adapted to a given ion. The theoretical framework makes it possible to delineate two important limiting cases. In the limit where the geometric forces are dominant (rigid binding site), ion selectivity is controlled by the ion-ligand interactions within the matching cavity size according to the familiar "snug-fit" mechanism of host-guest chemistry. In the limit where the geometric forces are negligible, the ion and ligands behave as a "confined microdroplet" that is free to fluctuate and adapt to ions of different sizes. In this case, ion selectivity is set by the interplay between ion-ligand and ligand-ligand interactions and is controlled by the number and the chemical type of ion-coordinating ligands. The framework is illustrated by considering the ion-selective binding sites in the KcsA channel and the LeuT transporter.

  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. Modelling with words: Narrative and natural selection.

    PubMed

    Dimech, Dominic K

    2017-02-18

    I argue that verbal models should be included in a philosophical account of the scientific practice of modelling. Weisberg (2013) has directly opposed this thesis on the grounds that verbal structures, if they are used in science, only merely describe models. I look at examples from Darwin's On the Origin of Species (1859) of verbally constructed narratives that I claim model the general phenomenon of evolution by natural selection. In each of the cases I look at, a particular scenario is described that involves at least some fictitious elements but represents the salient causal components of natural selection. I pronounce the importance of prioritising observation of scientific practice for the philosophy of modelling and I suggest that there are other likely model types that are excluded from philosophical accounts.

  8. 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…

  9. Surfaces for competitive selective bacterial capture from protein solutions.

    PubMed

    Fang, Bing; Gon, Saugata; Nüsslein, Klaus; Santore, Maria M

    2015-05-20

    Active surfaces that form the basis for bacterial sensors for threat detection, food safety, or certain diagnostic applications rely on bacterial adhesion. However, bacteria capture from complex fluids on the active surfaces can be reduced by the competing adsorption of proteins and other large molecules. Such adsorption can also interfere with device performance. As a result, multiple upstream processing steps are frequently employed to separate macromolecules from any cells, which remain in the buffer. Here, we present an economical approach to capture bacteria, without competitive adsorption by proteins, on engineered surfaces that do not employ biomolecular recognition, antibodies, or other molecules with engineered sequences. The surfaces are based on polyethylene glycol (PEG) brushes that, on their own, repel both proteins and bacteria. These PEG brushes backfill the surface around sparsely adsorbed cationic polymer coils (here, poly-L-lysine (PLL)). The PLL coils are effectively embedded within the brush and produce locally cationic nanoscale regions that attract negatively charged regions of proteins or cells against the steric background repulsion from the PEG brush. By carefully designing the surfaces to include just enough PLL to capture bacteria, but not enough to capture proteins, we achieve sharp selectivity where S. aureus is captured from albumin- or fibrinogen-containing solutions, but free albumin or fibrinogen molecules are rejected from the surface. Bacterial adhesion on these surfaces is not reduced by competitive protein adsorption, in contrast to performance of more uniformly cationic surfaces. Also, protein adsorption to the bacteria does not interfere with capture, at least for the case of S. aureus, to which fibrinogen binds through a specific receptor.

  10. 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.

  11. Site selectivity for protein tyrosine nitration: insights from features of structure and topological network.

    PubMed

    Cheng, Shangli; Lian, Baofeng; Liang, Juan; Shi, Ting; Xie, Lu; Zhao, Yi-Lei

    2013-11-01

    Tyrosine nitration is a covalent post-translational modification, which regulates protein functions such as hindering tyrosine phosphorylation and affecting essential signal transductions in cells. Based on up-to-date proteomics data, tyrosine nitration appears to be a highly selective process since not all tyrosine residues in proteins or all proteins are nitrated in vivo. Quite a few investigations included the protein structural information from the RCSB PDB database, where near 100,000 high-quality three-dimensional structures are available. In this work, we analyzed the local protein structures and amino acid topological networks of the nitrated and non-nitrated tyrosine sites in nitrated proteins, including neighboring atomic distribution, amino acid pair (AAP) and amino acid triangle (AAT). It has been found that aromatic and aliphatic residues, particularly with large volume, aromatic, aliphatic, or acidic side chains, are disfavored for the nitration. After integrating these structural features and topological network features with traditional sequence features, the predictive model achieves a sensitivity of 63.30% and a specificity of 92.24%, resulting in a much better accuracy compared to the previous models with only protein sequence information. Our investigation implies that the site selectivity may stem from a more open, hydrophilic and high-pH chemical environment around the tyrosine residue.

  12. 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.

  13. Bayesian variable selection for latent class models.

    PubMed

    Ghosh, Joyee; Herring, Amy H; Siega-Riz, Anna Maria

    2011-09-01

    In this article, we develop a latent class model with class probabilities that depend on subject-specific covariates. One of our major goals is to identify important predictors of latent classes. We consider methodology that allows estimation of latent classes while allowing for variable selection uncertainty. We propose a Bayesian variable selection approach and implement a stochastic search Gibbs sampler for posterior computation to obtain model-averaged estimates of quantities of interest such as marginal inclusion probabilities of predictors. Our methods are illustrated through simulation studies and application to data on weight gain during pregnancy, where it is of interest to identify important predictors of latent weight gain classes.

  14. The RNA-binding protein SERBP1 interacts selectively with the signaling protein RACK1.

    PubMed

    Bolger, Graeme B

    2017-03-04

    The RACK1 protein interacts with numerous proteins involved in signal transduction, the cytoskeleton, and mRNA splicing and translation. We used the 2-hybrid system to identify additional proteins interacting with RACK1 and isolated the RNA-binding protein SERBP1. SERPB1 shares amino acid sequence homology with HABP4 (also known as Ki-1/57), a component of the RNA spicing machinery that has been shown previously to interact with RACK1. Several different isoforms of SERBP1, generated by alternative mRNA splicing, interacted with RACK1 with indistinguishable interaction strength, as determined by a 2-hybrid beta-galactosidase assay. Analysis of deletion constructs of SERBP1 showed that the C-terminal third of the SERBP1 protein, which contains one of its two substrate sites for protein arginine N-methyltransferase 1 (PRMT1), is necessary and sufficient for it to interact with RACK1. Analysis of single amino acid substitutions in RACK1, identified in a reverse 2-hybrid screen, showed very substantial overlap with those implicated in the interaction of RACK1 with the cAMP-selective phosphodiesterase PDE4D5. These data are consistent with SERBP1 interacting selectively with RACK1, mediated by an extensive interaction surface on both proteins.

  15. 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.

  16. Residue-specific immobilization of protein molecules by size-selected clusters

    PubMed Central

    Prisco, Umberto; Leung, Carl; Xirouchaki, Chrisa; Jones, Celine H; Heath, John K; Palmer, Richard E

    2005-01-01

    The atomic force microscope (AFM), operating in contact mode, has been employed in buffer solution to study two proteins; (i) green fluorescent protein (GFP), from the hydromedusan jellyfish Aequorea victoria; and (ii) human oncostatin M (OSM), in the presence of size-selected gold nanoclusters pinned on to a highly oriented pyrolytic graphite substrate. The AFM images have revealed immobilization of single molecules of OSM, which are strongly bound to the gold nanoclusters. Conversely, no strong immobilization has been observed for the GFP, as these molecules were easily displaced by the scanning tip. The contrasting behaviour of the two proteins can be explained by the exposed molecular surface area of their cysteine residues as modelled on the basis of their respective X-ray crystallographic data structures. GFP contains two cysteine residues, but neither is readily available to chemisorb on the gold clusters, because the cysteines are largely inaccessible from the surface of the protein. In contrast, OSM has a total of five cysteine residues, with different degrees of accessibility, which make the protein amenable to anchoring on the nanoclusters. Statistical analysis of the height of the OSM molecules bound to the nanoclusters is in accordance with crystallographic data, and suggests various configurations of the proteins on the clusters, associated with the presence of different cysteine anchoring sites. These results suggest that the three-dimensional conformation of protein molecules is preserved when they are chemisorbed to size-selected gold clusters, thus opening a new route towards oriented immobilization of individual protein molecules. PMID:16849177

  17. Standard Codon Substitution Models Overestimate Purifying Selection for Nonstationary Data

    PubMed Central

    Yap, Von Bing; Huttley, Gavin A.

    2017-01-01

    Estimation of natural selection on protein-coding sequences is a key comparative genomics approach for de novo prediction of lineage-specific adaptations. Selective pressure is measured on a per-gene basis by comparing the rate of nonsynonymous substitutions to the rate of synonymous substitutions. All published codon substitution models have been time-reversible and thus assume that sequence composition does not change over time. We previously demonstrated that if time-reversible DNA substitution models are applied in the presence of changing sequence composition, the number of substitutions is systematically biased towards overestimation. We extend these findings to the case of codon substitution models and further demonstrate that the ratio of nonsynonymous to synonymous rates of substitution tends to be underestimated over three data sets of mammals, vertebrates, and insects. Our basis for comparison is a nonstationary codon substitution model that allows sequence composition to change. Goodness-of-fit results demonstrate that our new model tends to fit the data better. Direct measurement of nonstationarity shows that bias in estimates of natural selection and genetic distance increases with the degree of violation of the stationarity assumption. Additionally, inferences drawn under time-reversible models are systematically affected by compositional divergence. As genomic sequences accumulate at an accelerating rate, the importance of accurate de novo estimation of natural selection increases. Our results establish that our new model provides a more robust perspective on this fundamental quantity. PMID:28175284

  18. Synthetic silvestrol analogues as potent and selective protein synthesis inhibitors.

    PubMed

    Liu, Tao; Nair, Somarajan J; Lescarbeau, André; Belani, Jitendra; Peluso, Stéphane; Conley, James; Tillotson, Bonnie; O'Hearn, Patrick; Smith, Sherri; Slocum, Kelly; West, Kip; Helble, Joseph; Douglas, Mark; Bahadoor, Adilah; Ali, Janid; McGovern, Karen; Fritz, Christian; Palombella, Vito J; Wylie, Andrew; Castro, Alfredo C; Tremblay, Martin R

    2012-10-25

    Misregulation of protein translation plays a critical role in human cancer pathogenesis at many levels. Silvestrol, a cyclopenta[b]benzofuran natural product, blocks translation at the initiation step by interfering with assembly of the eIF4F translation complex. Silvestrol has a complex chemical structure whose functional group requirements have not been systematically investigated. Moreover, silvestrol has limited development potential due to poor druglike properties. Herein, we sought to develop a practical synthesis of key intermediates of silvestrol and explore structure-activity relationships around the C6 position. The ability of silvestrol and analogues to selectively inhibit the translation of proteins with high requirement on the translation-initiation machinery (i.e., complex 5'-untranslated region UTR) relative to simple 5'UTR was determined by a cellular reporter assay. Simplified analogues of silvestrol such as compounds 74 and 76 were shown to have similar cytotoxic potency and better ADME characteristics relative to those of silvestrol.

  19. Functionalized periodic mesoporous organosilicas for selective adsorption of proteins

    NASA Astrophysics Data System (ADS)

    Zhu, Ling; Liu, Xiaoyan; Chen, Tong; Xu, Zhigang; Yan, Wenfu; Zhang, Haixia

    2012-07-01

    The periodic mesoporous organosilicas (PMO) with an organobridged (sbnd CH2sbnd ) was synthesized and functionalized with amino or carboxylic groups by post-synthesis methods. The functionalized PMO by changing the hydrophilic/hydrophobic property and the net charge could be used to selectively adsorb and purify proteins with different shapes and different isoelectric points (pI). The experimental result showed that Bovine serum albumin (BSA) was adsorbed quicker than hemoglobin (Hb) on the materials, and lysozyme (Lys) could not be adsorbed on these PMO materials at all. The adsorption capacity of amino groups modified PMO (PMO-(NH2)2) for BSA was 44.67 mg/g and 300.0 mg/gfor Hb on carboxylic groups modified PMO (PMO-(COOH)2). The adsorption behavior of proteins was affected strongly by the interaction among different constituents in the mixture of proteins. In addition, it is found that the adsorption rate of (PMO-(NH2)2 for adsorption of proteins was much slower than PMO-(COOH)2.

  20. Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification.

    PubMed

    Manes, Nathan P; Mann, Jessica M; Nita-Lazar, Aleksandra

    2015-08-17

    Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of Gi2 (a heterotrimeric G-protein α-subunit) is described in detail.

  1. Bayesian model selection and isocurvature perturbations

    NASA Astrophysics Data System (ADS)

    Beltrán, María; García-Bellido, Juan; Lesgourgues, Julien; Liddle, Andrew R.; Slosar, Anže

    2005-03-01

    Present cosmological data are well explained assuming purely adiabatic perturbations, but an admixture of isocurvature perturbations is also permitted. We use a Bayesian framework to compare the performance of cosmological models including isocurvature modes with the purely adiabatic case; this framework automatically and consistently penalizes models which use more parameters to fit the data. We compute the Bayesian evidence for fits to a data set comprised of WMAP and other microwave anisotropy data, the galaxy power spectrum from 2dFGRS and SDSS, and Type Ia supernovae luminosity distances. We find that Bayesian model selection favors the purely adiabatic models, but so far only at low significance.

  2. Models of protein-ligand crystal structures: trust, but verify

    NASA Astrophysics Data System (ADS)

    Deller, Marc C.; Rupp, Bernhard

    2015-09-01

    X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

  3. 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.

  4. Positively selected sites in cetacean myoglobins contribute to protein stability.

    PubMed

    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.

  5. Regulation of cardiomyocyte signaling by RGS proteins: differential selectivity towards G proteins and susceptibility to regulation.

    PubMed

    Hao, Jianming; Michalek, Christina; Zhang, Wei; Zhu, Ming; Xu, Xiaomei; Mende, Ulrike

    2006-07-01

    Many signals that regulate cardiomyocyte growth, differentiation and function are mediated via heterotrimeric G proteins, which are under the control of RGS proteins (Regulators of G protein Signaling). Several RGS proteins are expressed in the heart, but so far little is known about their function and regulation. Using adenoviral gene transfer, we conducted the first comprehensive analysis of the capacity and selectivity of the major cardiac RGS proteins (RGS2-RGS5) to regulate central G protein-mediated signaling pathways in adult ventricular myocytes (AVM). All four RGS proteins potently inhibited Gq/11-mediated phospholipase C beta stimulation and cell growth (assessed in neonatal myocytes). Importantly, RGS2 selectively inhibited Gq/11 signaling, whereas RGS3, RGS4 and RGS5 had the capacity to regulate both Gq/11 and Gi/o signaling (carbachol-induced cAMP inhibition). Gs signaling was unaffected, and, contrary to reports in other cell lines, RGS2-RGS5 did not appear to regulate adenylate cyclase directly in AVM. Since RGS proteins can be highly regulated in their expression by many different stimuli, we also tested the hypothesis that RGS expression is subject to G protein-mediated regulation in AVM and determined the specificity with which enhanced G protein signaling alters endogenous RGS expression in AVM. RGS2 mRNA and protein were markedly but transiently up-regulated by enhanced Gq/11 signaling (alpha1-adrenergic stimulation or Galphaq* overexpression), possibly by a negative feedback mechanism. In contrast, the other negative regulators of Gq/11 signaling (RGS3-RGS5) were unchanged. Endogenous RGS2 (but not RGS3-RGS5) expression was also up-regulated in cells with enhanced AC signaling (beta-adrenergic or forskolin stimulation). Taken together, these findings suggest diverse roles of RGS proteins in regulating myocyte signaling. RGS2 emerged as the only selective and highly regulated inhibitor of Gq/11 signaling that could potentially become a promising

  6. 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.

  7. 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.

  8. The Critical Infrastructure Portfolio Selection Model

    DTIC Science & Technology

    2008-06-13

    Gregory Ehlers ties together two concepts that are fundamental to enabling a thorough understanding of the Critical Infrastructure Portfolio Selection...work of world-renowned economists, Paul Collier and Anke Hoeffler, and the econometric models that these scholars have developed in an effort to...

  9. Electronic Delivery Systems: A Selection Model.

    ERIC Educational Resources Information Center

    Pallesen, Peter J.; Haley, Paul; Jones, Edward S.; Moore, Bobbie; Widlake, Dina E.; Medsker, Karen L.

    1999-01-01

    Discussion of electronic learning delivery systems focuses on a delivery system selection model that is designed for use by performance improvement professionals who are choosing between satellite networks, teleconferencing, Internet/Intranet networks, desktop multimedia, electronic performance support systems, transportable audio/video, and the…

  10. A Theoretical Model for Selective Exposure Research.

    ERIC Educational Resources Information Center

    Roloff, Michael E.; Noland, Mark

    This study tests the basic assumptions underlying Fishbein's Model of Attitudes by correlating an individual's selective exposure to types of television programs (situation comedies, family drama, and action/adventure) with the attitudinal similarity between individual attitudes and attitudes characterized on the programs. Twenty-three college…

  11. A computational model of selection by consequences.

    PubMed Central

    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 computational experiments that arranged reinforcement according to random-interval (RI) schedules. The quantitative features of the model were varied over wide ranges in these experiments, and many of the qualitative features of the model also were varied. The digital organism consistently showed a hyperbolic relation between response and reinforcement rates, and this hyperbolic description of the data was consistently better than the description provided by other, similar, function forms. In addition, the parameters of the hyperbola varied systematically with the quantitative, and some of the qualitative, properties of the model in ways that were consistent with findings from biological organisms. These results suggest that the material events responsible for an organism's responding on RI schedules are computationally equivalent to Darwinian selection by consequences. They also suggest that the computational model developed here is worth pursuing further as a possible dynamic account of behavior. PMID:15357512

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

    DOE PAGES

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; ...

    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

  13. 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.

  14. 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

  15. 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

  16. SCAN: A Scalable Model of Attentional Selection.

    PubMed

    Hudson, Patrick T.W.; van den Herik, H Jaap; Postma, Eric O.

    1997-08-01

    This paper describes the SCAN (Signal Channelling Attentional Network) model, a scalable neural network model for attentional scanning. The building block of SCAN is a gating lattice, a sparsely-connected neural network defined as a special case of the Ising lattice from statistical mechanics. The process of spatial selection through covert attention is interpreted as a biological solution to the problem of translation-invariant pattern processing. In SCAN, a sequence of pattern translations combines active selection with translation-invariant processing. Selected patterns are channelled through a gating network, formed by a hierarchical fractal structure of gating lattices, and mapped onto an output window. We show how the incorporation of an expectation-generating classifier network (e.g. Carpenter and Grossberg's ART network) into SCAN allows attentional selection to be driven by expectation. Simulation studies show the SCAN model to be capable of attending and identifying object patterns that are part of a realistically sized natural image. Copyright 1997 Elsevier Science Ltd.

  17. Application of RGS box proteins to evaluate G-protein selectivity in receptor-promoted signaling.

    PubMed

    Hains, Melinda D; Siderovski, David P; Harden, T Kendall

    2004-01-01

    Regulator of G-protein signaling (RGS) domains bind directly to GTP-bound Galpha subunits and accelerate their intrinsic GTPase activity by up to several thousandfold. The selectivity of RGS proteins for individual Galpha subunits has been illustrated. Thus, the expression of RGS proteins can be used to inhibit signaling pathways activated by specific G protein-coupled receptors (GPCRs). This article describes the use of specific RGS domain constructs to discriminate among G(i/o), Gq-and G(12/13)-mediated activation of phospholipase C (PLC) isozymes in COS-7 cells. Overexpression of the N terminus of GRK2 (amino acids 45-178) or p115 RhoGEF (amino acids 1-240) elicited selective inhibition of Galphaq- or Galpha(12/13)-mediated signaling to PLC activation, respectively. In contrast, RGS2 overexpression was found to inhibit PLC activation by both G(i/o)- and Gq-coupled GPCRs. RGS4 exhibited dramatic receptor selectivity in its inhibitory actions; of the G(i/o)- and Gq-coupled GPCRs tested (LPA1, LPA2, P2Y1, S1P3), only the Gq-coupled lysophosphatidic acid-activated LPA2 receptor was found to be inhibited by RGS4 overexpression.

  18. On Model Selection Criteria in Multimodel Analysis

    NASA Astrophysics Data System (ADS)

    Meyer, P. D.; Ye, M.; Neuman, S. P.

    2007-12-01

    Hydrologic systems are open and complex, rendering them prone to multiple conceptualizations and mathematical descriptions. There has been a growing tendency to postulate several alternative hydrologic models for a site and use model selection criteria to (a) rank these models, (b) eliminate some of them and/or (c) weigh and average predictions and statistics generated by multiple models. This has led to some debate among hydrogeologists about the merits and demerits of common model selection (also known as model discrimination or information) criteria such as AIC, AICc, BIC, and KIC and some lack of clarity about the proper interpretation and mathematical representation of each criterion. In particular, whereas we [Neuman, 2003; Ye et al., 2004, 2005; Meyer et al., 2007] have based our approach to multimodel hydrologic ranking and inference on the Bayesian criterion KIC (which reduces asymptotically to BIC), Poeter and Anderson [2005] have voiced a strong preference for the information-theoretic criterion AICc (which reduces asymptotically to AIC). Their preference stems in part from a perception that KIC and BIC require a "true" or "quasi-true" model to be in the set of alternatives while AIC and AICc are free of such an unreasonable requirement. We examine the model selection literature to find that (a) all published rigorous derivations of AIC and AICc require that the (true) model having generated the observational data be in the set of candidate models; (b) though BIC and KIC were originally derived by assuming that such a model is in the set, BIC has been rederived by Cavanaugh and Neath [1999] without the need for such an assumption; (c) KIC reduces to BIC as the number of observations becomes large relative to the number of adjustable model parameters, implying that it likewise does not require the existence of a true model in the set of alternatives; (d) if a true model is in the set, BIC and KIC select with probability one the true model as sample size

  19. Development of a selective inhibitor of Protein Arginine Deiminase 2.

    PubMed

    Muth, Aaron; Subramanian, Venkataraman; Beaumont, Edward; Nagar, Mitesh; Kerry, Philip; McEwan, Paul; Srinath, Hema; Clancy, Kathleen Wanda; Parelkar, Sangram S; Thompson, Paul R

    2017-03-22

    Protein arginine deiminase 2 (PAD2) plays a key role in the onset and progression of multiple sclerosis, rheumatoid arthritis and breast cancer. To date, no PAD2-selective inhibitor has been developed. Such a compound will be critical for elucidating the biological roles of this isozyme and may ultimately be useful for treating specific diseases in which PAD2 activity is dysregulated. To achieve this goal, we synthesized a series of benzimidazole-based derivatives of Cl-amidine, hypothesizing that this scaffold would allow access to a series of PAD2-selective inhibitors with enhanced cellular efficacy. Herein, we demonstrate that substitutions at both the N-terminus and C-terminus of Cl-amidine result in >100-fold increases in PAD2 potency and selectivity (30a, 41a, and 49a) as well as cellular efficacy 30a. Notably, these compounds use the far less reactive fluoroacetamidine warhead. In total, we predict that 30a will be a critical tool for understanding cellular PAD2 function and sets the stage for treating diseases in which PAD2 activity is dysregulated.

  20. MODBASE, a database of annotated comparative protein structure models.

    PubMed

    Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C; Ilyin, Valentin A; Sali, Andrej

    2002-01-01

    MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10(-4)) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server.

  1. 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.

  2. 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.

  3. Bayesian Model Selection for Group Studies

    PubMed Central

    Stephan, Klaas Enno; Penny, Will D.; Daunizeau, Jean; Moran, Rosalyn J.; Friston, Karl J.

    2009-01-01

    Bayesian model selection (BMS) is a powerful method for determining the most likely among a set of competing hypotheses about the mechanisms that generated observed data. BMS has recently found widespread application in neuroimaging, particularly in the context of dynamic causal modelling (DCM). However, so far, combining BMS results from several subjects has relied on simple (fixed effects) metrics, e.g. the group Bayes factor (GBF), that do not account for group heterogeneity or outliers. In this paper, we compare the GBF with two random effects methods for BMS at the between-subject or group level. These methods provide inference on model-space using a classical and Bayesian perspective respectively. First, a classical (frequentist) approach uses the log model evidence as a subject-specific summary statistic. This enables one to use analysis of variance to test for differences in log-evidences over models, relative to inter-subject differences. We then consider the same problem in Bayesian terms and describe a novel hierarchical model, which is optimised to furnish a probability density on the models themselves. This new variational Bayes method rests on treating the model as a random variable and estimating the parameters of a Dirichlet distribution which describes the probabilities for all models considered. These probabilities then define a multinomial distribution over model space, allowing one to compute how likely it is that a specific model generated the data of a randomly chosen subject as well as the exceedance probability of one model being more likely than any other model. Using empirical and synthetic data, we show that optimising a conditional density of the model probabilities, given the log-evidences for each model over subjects, is more informative and appropriate than both the GBF and frequentist tests of the log-evidences. In particular, we found that the hierarchical Bayesian approach is considerably more robust than either of the other

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

    DOE PAGES

    Chowdhury, Chiranjit; Chun, Sunny; Pang, Allan; ...

    2015-02-23

    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. In this paper, 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 ofmore » 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. Finally and overall, these studies provide a basis for understanding a class of selectively permeable channels formed by nonmembrane proteins.« less

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

    SciTech Connect

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

    2015-02-23

    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. In this paper, 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. Finally and overall, these studies provide a basis for understanding a class of selectively permeable channels formed by nonmembrane proteins.

  6. 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/.

  7. Novel, potent and selective inhibitors of protein kinase C show oral anti-inflammatory activity.

    PubMed

    Nixon, J S; Bishop, J; Bradshaw, D; Davis, P D; Hill, C H; Elliott, L H; Kumar, H; Lawton, G; Lewis, E J; Mulqueen, M

    1991-01-01

    Clarification of the precise role of protein kinase C (PKC) in cellular functional responses has been hampered by a lack of potent, selective inhibitors. The structural lead provided by staurosporine, a potent but non-selective protein kinase (PK) inhibitor, was used to derive a series of bis(indolyl)maleimides of which the most potent, Ro 31-8425 (I50: PKC = 8 nM) showed 350-fold selectivity for PKC over cAMP-dependent protein kinase. Ro 31-8425 antagonised cellular processes triggered by phorbol esters (potent, specific PKC activators) and inhibited the allogeneic mixed lymphocyte reaction, suggesting a role for PKC in T-cell activation. Methylation of the primary amine in Ro 31-8425 produced an analogue. Ro 31-8830 which, when administered orally, produced a dose-dependent inhibition of a phorbol ester-induced paw oedema in mice (minimum effective dose = 15 mg/kg). Ro 31-8830 also selectively inhibited the secondary inflammation in a developing adjuvant arthritis model in the rat. The results presented here suggest that these selective inhibitors of PKC may have therapeutic value in the treatment of T-cell-mediated autoimmune diseases.

  8. 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

  9. 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'.

  10. Protein fragment reconstruction using various modeling techniques

    NASA Astrophysics Data System (ADS)

    Boniecki, Michal; Rotkiewicz, Piotr; Skolnick, Jeffrey; Kolinski, Andrzej

    2003-11-01

    Recently developed reduced models of proteins with knowledge-based force fields have been applied to a specific case of comparative modeling. From twenty high resolution protein structures of various structural classes, significant fragments of their chains have been removed and treated as unknown. The remaining portions of the structures were treated as fixed - i.e., as templates with an exact alignment. Then, the missed fragments were reconstructed using several modeling tools. These included three reduced types of protein models: the lattice SICHO (Side Chain Only) model, the lattice CABS (Cα + Cβ + Side group) model and an off-lattice model similar to the CABS model and called REFINER. The obtained reduced models were compared with more standard comparative modeling tools such as MODELLER and the SWISS-MODEL server. The reduced model results are qualitatively better for the higher resolution lattice models, clearly suggesting that these are now mature, competitive and complementary (in the range of sparse alignments) to the classical tools of comparative modeling. Comparison between the various reduced models strongly suggests that the essential ingredient for the sucessful and accurate modeling of protein structures is not the representation of conformational space (lattice, off-lattice, all-atom) but, rather, the specificity of the force fields used and, perhaps, the sampling techniques employed. These conclusions are encouraging for the future application of the fast reduced models in comparative modeling on a genomic scale.

  11. Computational protein design: the Proteus software and selected applications.

    PubMed

    Simonson, Thomas; Gaillard, Thomas; Mignon, David; Schmidt am Busch, Marcel; Lopes, Anne; Amara, Najette; Polydorides, Savvas; Sedano, Audrey; Druart, Karen; Archontis, Georgios

    2013-10-30

    We describe an automated procedure for protein design, implemented in a flexible software package, called Proteus. System setup and calculation of an energy matrix are done with the XPLOR modeling program and its sophisticated command language, supporting several force fields and solvent models. A second program provides algorithms to search sequence space. It allows a decomposition of the system into groups, which can be combined in different ways in the energy function, for both positive and negative design. The whole procedure can be controlled by editing 2-4 scripts. Two applications consider the tyrosyl-tRNA synthetase enzyme and its successful redesign to bind both O-methyl-tyrosine and D-tyrosine. For the latter, we present Monte Carlo simulations where the D-tyrosine concentration is gradually increased, displacing L-tyrosine from the binding pocket and yielding the binding free energy difference, in good agreement with experiment. Complete redesign of the Crk SH3 domain is presented. The top 10000 sequences are all assigned to the correct fold by the SUPERFAMILY library of Hidden Markov Models. Finally, we report the acid/base behavior of the SNase protein. Sidechain protonation is treated as a form of mutation; it is then straightforward to perform constant-pH Monte Carlo simulations, which yield good agreement with experiment. Overall, the software can be used for a wide range of application, producing not only native-like sequences but also thermodynamic properties with errors that appear comparable to other current software packages.

  12. Select host cell proteins coelute with monoclonal antibodies in protein A chromatography.

    PubMed

    Nogal, Bartek; Chhiba, Krishan; Emery, Jefferson C

    2012-01-01

    The most significant factor contributing to the presence of host cell protein (HCP) impurities in Protein A chromatography eluates is their association with the product monoclonal antibodies (mAbs) has been reported previously, and it has been suggested that more efficacious column washes may be developed by targeting the disruption of the mAbs-HCP interaction. However, characterization of this interaction is not straight forward as it is likely to involve multiple proteins and/or types of interaction. This work is an attempt to begin to understand the contribution of HCP subpopulations and/or mAb interaction propensity to the variability in HCP levels in the Protein A eluate. We performed a flowthrough (FT) recycling study with product respiking using two antibody molecules of apparently different HCP interaction propensities. In each case, the ELISA assay showed depletion of select subpopulations of HCP in Protein A eluates in subsequent column runs, while the feedstock HCP in the FTs remained unchanged from its native harvested cell culture fluid (HCCF) levels. In a separate study, the final FT from each molecule's recycling study was cross-spiked with various mAbs. In this case, Protein A eluate levels remained low for all but two molecules which were known as having high apparent HCP interaction propensity. The results of these studies suggest that mAbs may preferentially bind to select subsets of HCPs, and the degree of interaction and/or identity of the associated HCPs may vary depending on the mAb.

  13. 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

  14. 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.

  15. RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9

    PubMed Central

    CHENG, JIANLIN; EICKHOLT, JESSE; WANG, ZHENG; DENG, XIN

    2013-01-01

    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 signicantly 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

  16. Maximum-Likelihood Phylogenetic Inference with Selection on Protein Folding Stability.

    PubMed

    Arenas, Miguel; Sánchez-Cobos, Agustin; Bastolla, Ugo

    2015-08-01

    Despite intense work, incorporating constraints on protein native structures into the mathematical models of molecular evolution remains difficult, because most models and programs assume that protein sites evolve independently, whereas protein stability is maintained by interactions between sites. Here, we address this problem by developing a new mean-field substitution model that generates independent site-specific amino acid distributions with constraints on the stability of the native state against both unfolding and misfolding. The model depends on a background distribution of amino acids and one selection parameter that we fix maximizing the likelihood of the observed protein sequence. The analytic solution of the model shows that the main determinant of the site-specific distributions is the number of native contacts of the site and that the most variable sites are those with an intermediate number of native contacts. The mean-field models obtained, taking into account misfolded conformations, yield larger likelihood than models that only consider the native state, because their average hydrophobicity is more realistic, and they produce on the average stable sequences for most proteins. We evaluated the mean-field model with respect to empirical substitution models on 12 test data sets of different protein families. In all cases, the observed site-specific sequence profiles presented smaller Kullback-Leibler divergence from the mean-field distributions than from the empirical substitution model. Next, we obtained substitution rates combining the mean-field frequencies with an empirical substitution model. The resulting mean-field substitution model assigns larger likelihood than the empirical model to all studied families when we consider sequences with identity larger than 0.35, plausibly a condition that enforces conservation of the native structure across the family. We found that the mean-field model performs better than other structurally constrained

  17. Modeling chain folding in protein-constrained circular DNA.

    PubMed Central

    Martino, J A; Olson, W K

    1998-01-01

    An efficient method for sampling equilibrium configurations of DNA chains binding one or more DNA-bending proteins is presented. The technique is applied to obtain the tertiary structures of minimal bending energy for a selection of dinucleosomal minichromosomes that differ in degree of protein-DNA interaction, protein spacing along the DNA chain contour, and ring size. The protein-bound portions of the DNA chains are represented by tight, left-handed supercoils of fixed geometry. The protein-free regions are modeled individually as elastic rods. For each random spatial arrangement of the two nucleosomes assumed during a stochastic search for the global minimum, the paths of the flexible connecting DNA segments are determined through a numerical solution of the equations of equilibrium for torsionally relaxed elastic rods. The minimal energy forms reveal how protein binding and spacing and plasmid size differentially affect folding and offer new insights into experimental minichromosome systems. PMID:9591675

  18. Selective separation of the major whey proteins using ion exchange membranes.

    PubMed

    Goodall, S; Grandison, A S; Jauregi, P J; Price, J

    2008-01-01

    Synthetic microporous membranes with functional groups covalently attached were used to selectively separate beta-lactoglobulin, BSA, and alpha-lactalbumin from rennet whey. The selectivity and membrane performance of strong (quaternary ammonium) and weak (diethylamine) ion-exchange membranes were studied using breakthrough curves, measurement of binding capacity, and protein composition of the elution fraction to determine the binding behavior of each membrane. When the weak and strong anion exchange membranes were saturated with whey, they were both selective primarily for beta-lactoglobulin with less than 1% of the eluate consisting of alpha-lactalbumin or BSA. The binding capacity of a pure beta-lactoglobulin solution was in excess of 1.5 mg/cm2 of membrane. This binding capacity was reduced to approximately 1.2 mg/cm2 when using a rennet whey solution (pH 6.4). This reduction in protein binding capacity can be explained by both the competitive effects of other whey proteins and the effect of ions present in whey. Using binary solution breakthrough curves and rennet whey breakthrough curves, it was shown that alpha-lactalbumin and BSA were displaced from the strong and weak anion exchange membranes by beta-lactoglobulin. Finally, the effect of ionic strength on the binding capacity of individual proteins for each membrane was determined by comparing model protein solutions in milk permeate (pH 6.4) and a 10 mM sodium phosphate buffer (pH 6.4). Binding capacities of beta-lactoglobulin, alpha-lactalbumin, and BSA in milk permeate were reduced by as much as 50%. This reduction in capacity coupled with the low binding capacity of current ion exchange membranes are 2 serious considerations for selectively separating complex and concentrated protein solutions.

  19. 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.

  20. Inflation model selection meets dark radiation

    NASA Astrophysics Data System (ADS)

    Tram, Thomas; Vallance, Robert; Vennin, Vincent

    2017-01-01

    We investigate how inflation model selection is affected by the presence of additional free-streaming relativistic degrees of freedom, i.e. dark radiation. We perform a full Bayesian analysis of both inflation parameters and cosmological parameters taking reheating into account self-consistently. We compute the Bayesian evidence for a few representative inflation scenarios in both the standard ΛCDM model and an extension including dark radiation parametrised by its effective number of relativistic species Neff. Using a minimal dataset (Planck low-l polarisation, temperature power spectrum and lensing reconstruction), we find that the observational status of most inflationary models is unchanged. The exceptions are potentials such as power-law inflation that predict large values for the scalar spectral index that can only be realised when Neff is allowed to vary. Adding baryon acoustic oscillations data and the B-mode data from BICEP2/Keck makes power-law inflation disfavoured, while adding local measurements of the Hubble constant H0 makes power-law inflation slightly favoured compared to the best single-field plateau potentials. This illustrates how the dark radiation solution to the H0 tension would have deep consequences for inflation model selection.

  1. Model selection for radiochromic film dosimetry.

    PubMed

    Méndez, I

    2015-05-21

    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.

  2. Resampling methods for model fitting and model selection.

    PubMed

    Babu, G Jogesh

    2011-11-01

    Resampling procedures for fitting models and model selection are considered in this article. Nonparametric goodness-of-fit statistics are generally based on the empirical distribution function. The distribution-free property of these statistics does not hold in the multivariate case or when some of the parameters are estimated. Bootstrap methods to estimate the underlying distributions are discussed in such cases. The results hold not only in the case of one-dimensional parameter space, but also for the vector parameters. Bootstrap methods for inference, when the data is from an unknown distribution that may or may not belong to a specified family of distributions, are also considered. Most of the information criteria-based model selection procedures such as the Akaike information criterion, Bayesian information criterion, and minimum description length use estimation of bias. The bias, which is inevitable in model selection problems, arises mainly from estimating the distance between the "true" model and an estimated model. A jackknife type procedure for model selection is discussed, which instead of bias estimation is based on bias reduction.

  3. PPIcons: identification of protein-protein interaction sites in selected organisms.

    PubMed

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

    2013-09-01

    The physico-chemical properties of interaction interfaces have a crucial role in characterization of protein-protein interactions (PPI). In silico prediction of participating amino acids helps to identify interface residues for further experimental verification using mutational analysis, or inhibition studies by screening library of ligands against given protein. Given the unbound structure of a protein and the fact that it forms a complex with another known protein, the objective of this work is to identify the residues that are involved in the interaction. We attempt to predict interaction sites in protein complexes using local composition of amino acids together with their physico-chemical characteristics. The local sequence segments (LSS) are dissected from the protein sequences using a sliding window of 21 amino acids. The list of LSSs is passed to the support vector machine (SVM) predictor, which identifies interacting residue pairs considering their inter-atom distances. We have analyzed three different model organisms of Escherichia coli, Saccharomyces Cerevisiae and Homo sapiens, where the numbers of considered hetero-complexes are equal to 40, 123 and 33 respectively. Moreover, the unified multi-organism PPI meta-predictor is also developed under the current work by combining the training databases of above organisms. The PPIcons interface residues prediction method is measured by the area under ROC curve (AUC) equal to 0.82, 0.75, 0.72 and 0.76 for the aforementioned organisms and the meta-predictor respectively.

  4. 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.

  5. Appropriate model selection methods for nonstationary generalized extreme value models

    NASA Astrophysics Data System (ADS)

    Kim, Hanbeen; Kim, Sooyoung; Shin, Hongjoon; Heo, Jun-Haeng

    2017-04-01

    Several evidences of hydrologic data series being nonstationary in nature have been found to date. This has resulted in the conduct of many studies in the area of nonstationary frequency analysis. Nonstationary probability distribution models involve parameters that vary over time. Therefore, it is not a straightforward process to apply conventional goodness-of-fit tests to the selection of an appropriate nonstationary probability distribution model. Tests that are generally recommended for such a selection include the Akaike's information criterion (AIC), corrected Akaike's information criterion (AICc), Bayesian information criterion (BIC), and likelihood ratio test (LRT). In this study, the Monte Carlo simulation was performed to compare the performances of these four tests, with regard to nonstationary as well as stationary generalized extreme value (GEV) distributions. Proper model selection ratios and sample sizes were taken into account to evaluate the performances of all the four tests. The BIC demonstrated the best performance with regard to stationary GEV models. In case of nonstationary GEV models, the AIC proved to be better than the other three methods, when relatively small sample sizes were considered. With larger sample sizes, the AIC, BIC, and LRT presented the best performances for GEV models which have nonstationary location and/or scale parameters, respectively. Simulation results were then evaluated by applying all four tests to annual maximum rainfall data of selected sites, as observed by the Korea Meteorological Administration.

  6. 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

  7. Model Selection for Cox Models with Time-Varying Coefficients

    PubMed Central

    Yan, Jun; Huang, Jian

    2011-01-01

    Summary Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right censored failure times. Since not all covariate coefficients are time-varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time-varying coefficient from those with time-independent coefficient. We propose an adaptive group lasso method that not only selects important variables but also selects between time-independent and time-varying specifications of their presence in the model. Each covariate effect is partitioned into a time-independent part and a time-varying part, the latter of which is characterized by a group of coefficients of basis splines without intercept. Model selection and estimation are carried out through a fast, iterative group shooting algorithm. Our approach is shown to have good properties in a simulation study that mimics realistic situations with up to 20 variables. A real example illustrates the utility of the method. PMID:22506825

  8. Protein selectivity with immobilized metal ion-tacn sorbents: chromatographic studies with human serum proteins and several other globular proteins.

    PubMed

    Jiang, W; Graham, B; Spiccia, L; Hearn, M T

    1998-01-01

    The chromatographic selectivity of the immobilized chelate system, 1,4,7-triazocyclononane (tacn), complexed with the borderline metal ions Cu2+, Cr3+, Mn2+, Co2+, Zn2+, and Ni2+ has been investigated with hen egg white lysozyme, horse heart cytochrome c, and horse skeletal muscle myoglobin, as well as proteins present in partially fractionated preparations of human plasma. The effects of ionic strength and pH of the loading and elution buffers on protein selectivities of these new immobilized metal ion affinity chromatographic (IMAC) systems have been examined. The results confirm that immobilized Mn;pl-tacn sorbents exhibit a novel type of IMAC behavior with proteins. In particular, the chromatographic properties of these immobilized M(n+)-tacn ligand systems were significantly different compared to the IMAC behavior observed with other types of immobilized tri- and tetradentate chelating ligands, such as iminodiacetic acid, O-phosphoserine, or nitrilotriacetic acid, when complexed with borderline metal ions. The experimental results have consequently been evaluated in terms of the additional contributions to the interactive processes mediated by effects other than solely the conventional lone pair Lewis soft acid-Lewis soft base coordination interactions, typically found for the IMAC of proteins with borderline and soft metal ions, such as Cu2+ or Ni2+.

  9. 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.

  10. Deciphering Supramolecular Structures with Protein-Protein Interaction Network Modeling

    PubMed Central

    Tsuji, Toshiyuki; Yoda, Takao; Shirai, Tsuyoshi

    2015-01-01

    Many biological molecules are assembled into supramolecules that are essential to perform complicated functions in the cell. However, experimental information about the structures of supramolecules is not sufficient at this point. We developed a method of predicting and modeling the structures of supramolecules in a biological network by combining structural data of the Protein Data Bank (PDB) and interaction data in IntAct databases. Templates for binary complexes in IntAct were extracted from PDB. Modeling was attempted by assembling binary complexes with superposed shared subunits. A total of 3,197 models were constructed, and 1,306 (41% of the total) contained at least one subunit absent from experimental structures. The models also suggested 970 (25% of the total) experimentally undetected subunit interfaces, and 41 human disease-related amino acid variants were mapped onto these model-suggested interfaces. The models demonstrated that protein-protein interaction network modeling is useful to fill the information gap between biological networks and structures. PMID:26549015

  11. 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.

  12. Parallel cascade selection molecular dynamics for efficient conformational sampling and free energy calculation of proteins

    NASA Astrophysics Data System (ADS)

    Kitao, Akio; Harada, Ryuhei; Nishihara, Yasutaka; Tran, Duy Phuoc

    2016-12-01

    Parallel Cascade Selection Molecular Dynamics (PaCS-MD) was proposed as an efficient conformational sampling method to investigate conformational transition pathway of proteins. In PaCS-MD, cycles of (i) selection of initial structures for multiple independent MD simulations and (ii) conformational sampling by independent MD simulations are repeated until the convergence of the sampling. The selection is conducted so that protein conformation gradually approaches a target. The selection of snapshots is a key to enhance conformational changes by increasing the probability of rare event occurrence. Since the procedure of PaCS-MD is simple, no modification of MD programs is required; the selections of initial structures and the restart of the next cycle in the MD simulations can be handled with relatively simple scripts with straightforward implementation. Trajectories generated by PaCS-MD were further analyzed by the Markov state model (MSM), which enables calculation of free energy landscape. The combination of PaCS-MD and MSM is reported in this work.

  13. 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.

  14. 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

  15. A model of protein conformational substates

    PubMed Central

    Stein, D. L.

    1985-01-01

    Many proteins have been observed to exist in a large number of conformations that are believed to play an important role in their dynamics. A model of protein conformational substates that incorporates the ideas of frustration and disorder in analogy to glasses and spin glasses is proposed. Applications to x-ray diffraction, Mössbauer studies, and recombination experiments are discussed. PMID:16593568

  16. Modeling the paramyxovirus hemagglutinin-neuraminidase protein.

    PubMed

    Epa, V C

    1997-11-01

    The paramyxovirus hemagglutinin-neuraminidase (HN) protein exhibits neuraminidase activity and has an active site functionally similar to that in influenza neuraminidases. Earlier work identified conserved amino acids among HN sequences and proposed similarity between HN and influenza neuraminidase sequences. In this work we identify the three-dimensional fold and develop a more detailed model for the HN protein, in the process we examine a variety of protein structure prediction methods. We use the known structures of viral and bacterial neuraminidases as controls in testing the success of protein structure prediction and modeling methods, including knowledge-based threading, discrete three-dimensional environmental profiles, hidden Markov models, neural network secondary structure prediction, pattern matching, and hydropathy plots. The results from threading show that the HN protein sequence has a 6 beta-sheet propellor fold and enable us to assign the locations of the individual beta-strands. The three-dimensional environmental profile and hidden Markov model methods were not successful in this work. The model developed in this work helps to understand better the biological function of the HN protein and design inhibitors of the enzyme and serves as an assessment of some protein structure prediction methods, especially after the x-ray crystallographic solution of its structure.

  17. 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

  18. 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.

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

    PubMed

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

    2011-09-21

    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.

  20. Discrete and continuous models of protein sorting in the Golgi

    NASA Astrophysics Data System (ADS)

    Gong, Haijun; Schwartz, Russell

    2009-03-01

    The Golgi apparatus plays an important role in processing and sorting proteins and lipids. Golgi compartments constantly exchange material with each other and with other cellular components, allowing them to maintain and reform distinct identities despite dramatic changes in structure and size during cell division, development and osmotic stress. We have developed two minimal models of membrane and protein exchange in the Golgi --- a discrete, stochastic model [1] and a continuous ordinary differential equation (ODE) model --- both based on two fundamental mechanisms: vesicle-coat-mediated selective concentration of soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins during vesicle formation and SNARE-mediated selective fusion of vesicles. Both show similar ability to establish and maintain distinct identities over broad parameter ranges, but they diverge in extreme conditions where Golgi collapse and reassembly may be observed. By exploring where the models differ, we hope to better identify those features essential to minimal models of various Golgi behaviors. [1] H. Gong, D. Sengupta, A. D. Linstedt, R. Schwartz. Biophys J. 95: 1674-1688, 2008.

  1. Aromatic Functionality of Target Proteins Influences Monomer Selection for Creating Artificial Antibodies on Plasmonic Biosensors.

    PubMed

    Hu, Rong; Luan, Jingyi; Kharasch, Evan D; Singamaneni, Srikanth; Morrissey, Jeremiah J

    2017-01-11

    Natural antibodies used as biorecognition elements suffer from numerous shortcomings, such as limited chemical and environmental stability and cost. Artificial antibodies based on molecular imprinting are an attractive alternative to natural antibodies. We investigated the role of aromatic interactions in target recognition capabilities of artificial antibodies. Three proteins with different aromatic amino acid content were employed as model targets. Artificial antibodies were formed on nanostructures using combinations of silane monomers of varying aromatic functionality. We employed refractive index sensitivity of plasmonic nanostructures as a transduction platform for monitoring various steps in the imprinting process and to quantify the target recognition capabilities of the artificial antibodies. The sensitivity of the artificial antibodies with aromatic interactions exhibited a protein-dependent enhancement. Selectivity and sensitivity enhancement due to the presence of aromatic groups in imprinted polymer matrix was found to be higher for target proteins with higher aromatic amino acid content. Our results indicate that tailoring the monomer composition based on the amino acid content of the target protein can improve the sensitivity of plasmonic biosensors based on artificial antibodies without affecting the selectivity.

  2. A Photoactivatable GFP for Selective Photolabeling of Proteins and Cells

    NASA Astrophysics Data System (ADS)

    Patterson, George H.; Lippincott-Schwartz, Jennifer

    2002-09-01

    We report a photoactivatable variant of the Aequorea victoria green fluorescent protein (GFP) that, after intense irradiation with 413-nanometer light, increases fluorescence 100 times when excited by 488-nanometer light and remains stable for days under aerobic conditions. These characteristics offer a new tool for exploring intracellular protein dynamics by tracking photoactivated molecules that are the only visible GFPs in the cell. Here, we use the photoactivatable GFP both as a free protein to measure protein diffusion across the nuclear envelope and as a chimera with a lysosomal membrane protein to demonstrate rapid interlysosomal membrane exchange.

  3. A photoactivatable GFP for selective photolabeling of proteins and cells.

    PubMed

    Patterson, George H; Lippincott-Schwartz, Jennifer

    2002-09-13

    We report a photoactivatable variant of the Aequorea victoria green fluorescent protein (GFP) that, after intense irradiation with 413-nanometer light, increases fluorescence 100 times when excited by 488-nanometer light and remains stable for days under aerobic conditions. These characteristics offer a new tool for exploring intracellular protein dynamics by tracking photoactivated molecules that are the only visible GFPs in the cell. Here, we use the photoactivatable GFP both as a free protein to measure protein diffusion across the nuclear envelope and as a chimera with a lysosomal membrane protein to demonstrate rapid interlysosomal membrane exchange.

  4. Selective Pressure to Increase Charge in Immunodominant Epitopes of the H3 Hemagglutinin Influenza Protein

    PubMed Central

    Pan, Keyao; Long, Jinxue; Sun, Haoxin; Tobin, Gregory J.; Nara, Peter L.

    2010-01-01

    The evolutionary speed and the consequent immune escape of H3N2 influenza A virus make it an interesting evolutionary system. Charged amino acid residues are often significant contributors to the free energy of binding for protein–protein interactions, including antibody–antigen binding and ligand–receptor binding. We used Markov chain theory and maximum likelihood estimation to model the evolution of the number of charged amino acids on the dominant epitope in the hemagglutinin protein of circulating H3N2 virus strains. The number of charged amino acids increased in the dominant epitope B of the H3N2 virus since introduction in humans in 1968. When epitope A became dominant in 1989, the number of charged amino acids increased in epitope A and decreased in epitope B. Interestingly, the number of charged residues in the dominant epitope of the dominant circulating strain is never fewer than that in the vaccine strain. We propose these results indicate selective pressure for charged amino acids that increase the affinity of the virus epitope for water and decrease the affinity for host antibodies. The standard PAM model of generic protein evolution is unable to capture these trends. The reduced alphabet Markov model (RAMM) model we introduce captures the increased selective pressure for charged amino acids in the dominant epitope of hemagglutinin of H3N2 influenza (R2 > 0.98 between 1968 and 1988). The RAMM model calibrated to historical H3N2 influenza virus evolution in humans fit well to the H3N2/Wyoming virus evolution data from Guinea pig animal model studies. Electronic supplementary material The online version of this article (doi:10.1007/s00239-010-9405-4) contains supplementary material, which is available to authorized users. PMID:21086120

  5. A Selective Review of Group Selection in High-Dimensional Models.

    PubMed

    Huang, Jian; Breheny, Patrick; Ma, Shuangge

    2012-01-01

    Grouping structures arise naturally in many statistical modeling problems. Several methods have been proposed for variable selection that respect grouping structure in variables. Examples include the group LASSO and several concave group selection methods. In this article, we give a selective review of group selection concerning methodological developments, theoretical properties and computational algorithms. We pay particular attention to group selection methods involving concave penalties. We address both group selection and bi-level selection methods. We describe several applications of these methods in nonparametric additive models, semiparametric regression, seemingly unrelated regressions, genomic data analysis and genome wide association studies. We also highlight some issues that require further study.

  6. Learning generative models for protein fold families.

    PubMed

    Balakrishnan, Sivaraman; Kamisetty, Hetunandan; Carbonell, Jaime G; Lee, Su-In; Langmead, Christopher James

    2011-04-01

    We introduce a new approach to learning statistical models from multiple sequence alignments (MSA) of proteins. Our method, called GREMLIN (Generative REgularized ModeLs of proteINs), learns an undirected probabilistic graphical model of the amino acid composition within the MSA. The resulting model encodes both the position-specific conservation statistics and the correlated mutation statistics between sequential and long-range pairs of residues. Existing techniques for learning graphical models from MSA either make strong, and often inappropriate assumptions about the conditional independencies within the MSA (e.g., Hidden Markov Models), or else use suboptimal algorithms to learn the parameters of the model. In contrast, GREMLIN makes no a priori assumptions about the conditional independencies within the MSA. We formulate and solve a convex optimization problem, thus guaranteeing that we find a globally optimal model at convergence. The resulting model is also generative, allowing for the design of new protein sequences that have the same statistical properties as those in the MSA. We perform a detailed analysis of covariation statistics on the extensively studied WW and PDZ domains and show that our method out-performs an existing algorithm for learning undirected probabilistic graphical models from MSA. We then apply our approach to 71 additional families from the PFAM database and demonstrate that the resulting models significantly out-perform Hidden Markov Models in terms of predictive accuracy.

  7. Growth rate modeling for selective tungsten LPCVD

    NASA Astrophysics Data System (ADS)

    Wolf, H.; Streiter, R.; Schulz, S. E.; Gessner, T.

    1995-10-01

    Selective chemical vapor deposition of tungsten plugs on sputtered tungsten was performed in a single-wafer cold-wall reactor using silane (SiH 4) and tungsten hexafluoride (WF 6). Extensive SEM measurements of film thickness were carried out to study the dependence of growth rates on various process conditions, wafer loading, and via dimensions. The results have been interpreted by numerical calculations based on a simulation model which is also presented. Both continuum fluid dynamics and the ballistic line-of-sight approach are used for transport modeling. The reaction rate is described by an empirical rate expression using coefficients fitted from experimental data. In the range 0.2 < p( SiH 4) /p( WF 6) < 0.75 , the reaction order was determined as 1.55 and -0.55 with respect to SiH 4 and WF 6, respectively. For higher partial pressure ratios the second-order rate dependence on p(SiH 4) and the minus first-order dependence on p(WF 6) were confirmed.

  8. 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

    2009-09-09

    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.

  9. A multi-template combination algorithm for protein comparative modeling

    PubMed Central

    Cheng, Jianlin

    2008-01-01

    Background Multiple protein templates are commonly used in manual protein structure prediction. However, few automated algorithms of selecting and combining multiple templates are available. Results Here we develop an effective multi-template combination algorithm for protein comparative modeling. The algorithm selects templates according to the similarity significance of the alignments between template and target proteins. It combines the whole template-target alignments whose similarity significance score is close to that of the top template-target alignment within a threshold, whereas it only takes alignment fragments from a less similar template-target alignment that align with a sizable uncovered region of the target. We compare the algorithm with the traditional method of using a single top template on the 45 comparative modeling targets (i.e. easy template-based modeling targets) used in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7). The multi-template combination algorithm improves the GDT-TS scores of predicted models by 6.8% on average. The statistical analysis shows that the improvement is significant (p-value < 10-4). Compared with the ideal approach that always uses the best template, the multi-template approach yields only slightly better performance. During the CASP7 experiment, the preliminary implementation of the multi-template combination algorithm (FOLDpro) was ranked second among 67 servers in the category of high-accuracy structure prediction in terms of GDT-TS measure. Conclusion We have developed a novel multi-template algorithm to improve protein comparative modeling. PMID:18366648

  10. 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

  11. 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.

  12. Selective release from cultured mammalian cells of heat-shock (stress) proteins that resemble glia-axon transfer proteins.

    PubMed

    Hightower, L E; Guidon, P T

    1989-02-01

    Cultured rat embryo cells were stimulated to rapidly release a small group of proteins that included several heat-shock proteins (hsp110, hsp71, hscp73) and nonmuscle actin. The extracellular proteins were analyzed by two-dimensional polyacrylamide gel electrophoresis. Heat-shocked cells released the same set of proteins as control cells with the addition of the stress-inducible hsp110 and hsp71. Release of these proteins was not blocked by either monensin or colchicine, inhibitors of the common secretory pathway. A small amount of the glucose-regulated protein grp78 was externalized by this pathway. The extracellular accumulation of these proteins was inhibited after they were synthesized in the presence of the lysine analogue aminoethyl cysteine. It is likely that the analogue-substituted proteins were misfolded and could not be released from cells, supporting our conclusion that a selective release mechanism is involved. Remarkably, actin and the squid heat-shock proteins homologous to rat hsp71 and hsp110 are also among a select group of proteins transferred from glial cells to the squid giant axon, where they have been implicated in neuronal stress responses (Tytell et al.: Brain Res., 363:161-164, 1986). Based in part on the similarities between these two sets of proteins, we hypothesized that these proteins were released from labile cortical regions of animal cells in response to perturbations of homeostasis in cells as evolutionarily distinct as cultured rat embryo cells and squid glial cells.

  13. Oxyanion selectivity in sulfate and molybdate transport proteins: an ab initio/CDM study.

    PubMed

    Dudev, Todor; Lim, Carmay

    2004-08-25

    A striking feature of sulfate (SO(4)(2-)) and molybdate (MoO(4)(2-)) transport proteins, such as SBP and ModA, which specifically bind SO(4)(2-) and MoO(4)(2-), respectively, is their ability to discriminate very similar anions with the same net charge, geometry, and hydrogen-bonding properties. Here, we determine to what extent (1) oxyanion-solvent interactions, (2) oxyanion-amino acid interactions, and (3) the anion-binding pocket sizes of the cognate protein contribute to the anion selectivity process in SO(4)(2-) and MoO(4)(2-) transport proteins by computing the free energies for replacing SO(4)(2-) with MoO(4)(2)(-)/WO(4)(2-) in model SO(4)(2-)-binding sites of varying degrees of solvent exposure using a combined quantum mechanical/continuum dielectric approach. The calculations reveal that MoO(4)(2-) transport proteins, such as ModA, specifically bind MoO(4)(2-)/WO(4)(2-) but not SO(4)(2-), mainly because the desolvation penalty of MoO(4)(2-)/WO(4)(2-) is significantly less than that of SO(4)(2-) and, to a lesser extent, because the large and rigid cavity in these proteins attenuates ligand interactions with SO(4)(2-), as compared to MoO(4)(2-). On the other hand, SO(4)(2-) transport proteins prefer SO(4)(2-) to MoO(4)(2-)/WO(4)(2-) because the small anion-binding pocket characteristic of these proteins inhibits binding of the larger MoO(4)(2-) and WO(4)(2-) anions. The calculations also help to explain the absence of positively charged Lys/Arg side chains in the anion-binding sites of SBP and ModA. During evolution, these transport proteins may have excluded cationic ligands from their binding sites because, on one hand, Lys/Arg do not contribute to the selectivity of the binding pocket and, on the other, they substantially stabilize the complex between the oxyanion and protein ligands, which in turn would prohibit the rapid release of the bound oxyanion at a certain stage during the transport process.

  14. 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.

  15. Selective detection of target proteins by peptide-enabled graphene biosensor.

    PubMed

    Khatayevich, Dmitriy; Page, Tamon; Gresswell, Carolyn; Hayamizu, Yuhei; Grady, William; Sarikaya, Mehmet

    2014-04-24

    Direct molecular detection of biomarkers is a promising approach for diagnosis and monitoring of numerous diseases, as well as a cornerstone of modern molecular medicine and drug discovery. Currently, clinical applications of biomarkers are limited by the sensitivity, complexity and low selectivity of available indirect detection methods. Electronic 1D and 2D nano-materials such as carbon nanotubes and graphene, respectively, offer unique advantages as sensing substrates for simple, fast and ultrasensitive detection of biomolecular binding. Versatile methods, however, have yet to be developed for simultaneous functionalization and passivation of the sensor surface to allow for enhanced detection and selectivity of the device. Herein, we demonstrate selective detection of a model protein against a background of serum protein using a graphene sensor functionalized via self-assembling multifunctional short peptides. The two peptides are engineered to bind to graphene and undergo co-assembly in the form of an ordered monomolecular film on the substrate. While the probe peptide displays the bioactive molecule, the passivating peptide prevents non-specific protein adsorption onto the device surface, ensuring target selectivity. In particular, we demonstrate a graphene field effect transistor (gFET) biosensor which can detect streptavidin against a background of serum bovine albumin at less than 50 ng/ml. Our nano-sensor design, allows us to restore the graphene surface and utilize each sensor in multiple experiments. The peptide-enabled gFET device has great potential to address a variety of bio-sensing problems, such as studying ligand-receptor interactions, or detection of biomarkers in a clinical setting.

  16. Model study of protein unfolding by interfaces

    NASA Astrophysics Data System (ADS)

    Chakarova, S. D.; Carlsson, A. E.

    2004-02-01

    We study interface-induced protein unfolding on hydrophobic and polar interfaces by means of a two-dimensional lattice model and an exhaustive enumeration ground-state structure search, for a set of model proteins of length 20 residues. We compare the effects of the two types of interfaces, and search for criteria that influence the retention of a protein’s native-state structure upon adsorption. We find that the unfolding proceeds by a large, sudden loss of native contacts. The unfolding at polar interfaces exhibits similar behavior to that at hydrophobic interfaces but with a much weaker interface coupling strength. Further, we find that the resistance of proteins to unfolding in our model is positively correlated with the magnitude of the folding energy in the native-state structure, the thermal stability (or energy gap) for that structure, and the interface energy for native-state adsorption. We find these factors to be of roughly equal importance.

  17. Characterization and modeling of protein protein interaction networks

    NASA Astrophysics Data System (ADS)

    Colizza, Vittoria; Flammini, Alessandro; Maritan, Amos; Vespignani, Alessandro

    2005-07-01

    The recent availability of high-throughput gene expression and proteomics techniques has created an unprecedented opportunity for a comprehensive study of the structure and dynamics of many biological networks. Global proteomic interaction data, in particular, are synthetically represented as undirected networks exhibiting features far from the random paradigm which has dominated past effort in network theory. This evidence, along with the advances in the theory of complex networks, has triggered an intense research activity aimed at exploiting the evolutionary and biological significance of the resulting network's topology. Here we present a review of the results obtained in the characterization and modeling of the yeast Saccharomyces Cerevisiae protein interaction networks obtained with different experimental techniques. We provide a comparative assessment of the topological properties and discuss possible biases in interaction networks obtained with different techniques. We report on dynamical models based on duplication mechanisms that cast the protein interaction networks in the family of dynamically growing complex networks. Finally, we discuss various results and analysis correlating the networks’ topology with the biological function of proteins.

  18. Selectable sets of novel proteins: catalytic and other properties. Final report, 1 July-30 September 1988

    SciTech Connect

    Kauffman, S.A.

    1989-05-08

    This proposal aimed at the development of mathematical, computer, recombinant DNA, selection and screening procedures to attain adaptive evolution of entirely novel peptides or fusion proteins with useful catalytic, ligand binding, structural, or other features. Potential uses range from industrial catalysis to production of new drugs and vaccines. A broad purpose of the experimental effort is to obtain novel peptides that can mimic the biological effects of almost arbitrary signal molecules such as hormones, growth factors, even pathogenic antigens. Mathematical models were developed to explore rugged 'adaptive landscapes' associated with protein evolution. The fundamental importance of this work includes analysis of the distribution of function in peptide space and opening the way towards a technology of applied molecular evolution.

  19. 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.

  20. Principles Governing Metal Ion Selectivity in Ion Channel Proteins

    NASA Astrophysics Data System (ADS)

    Lim, Carmay

    2014-03-01

    Our research interests are to (i) unravel the principles governing biological processes and use them to identify novel drug targets and guide drug design, and (ii) develop new methods for studying macromolecular interactions. This talk will provide an overview of our work in these two areas and an example of how our studies have helped to unravel the principles underlying the conversion of Ca2+-selective to Na+-selective channels. Ion selectivity of four-domain voltage-gated Ca2+(Cav) and sodium (Nav) channels, which is controlled by the selectivity filter (SF, the narrowest region of an open pore), is crucial for electrical signaling. Over billions of years of evolution, mutation of the Glu from domain II/III in the EEEE/DEEA SF of Ca2+-selective Cav channels to Lys made these channels Na+-selective. This talk will delineate the physical principles why Lys is sufficient for Na+/Ca2+selectivity and why the DEKA SF is more Na+-selective than the DKEA one.

  1. Selective extraction of isolated mitotic apparatus. Evidence that typical microtubule protein is extracted by organic mercurial.

    PubMed

    Bibring, T; Baxandall, J

    1971-02-01

    Mitotic apparatus isolated from sea urchin eggs has been treated with meralluride sodium under conditions otherwise resembling those of its isolation. The treatment causes a selective morphological disappearance of microtubules while extracting a major protein fraction, probably consisting of two closely related proteins, which constitutes about 10% of mitotic apparatus protein. Extraction of other cell particulates under similar conditions yields much less of this protein. The extracted protein closely resembles outer doublet microtubule protein from sea urchin sperm tail in properties considered typical of microtubule proteins: precipitation by calcium ion and vinblastine, electrophoretic mobility in both acid and basic polyacrylamide gels, sedimentation coefficient, molecular weight, and, according to a preliminary determination, amino acid composition. An antiserum against a preparation of sperm tail outer doublet microtubules cross-reacts with the extract from mitotic apparatus. On the basis of these findings it appears that microtubule protein is selectively extracted from isolated mitotic apparatus by treatment with meralluride, and is a typical microtubule protein.

  2. The Ebola virus matrix protein VP40 selectively induces vesiculation from phosphatidylserine-enriched membranes.

    PubMed

    Soni, Smita P; Stahelin, Robert V

    2014-11-28

    Ebola virus is from the Filoviridae family of viruses and is one of the most virulent pathogens known with ∼ 60% clinical fatality. The Ebola virus negative sense RNA genome encodes seven proteins including viral matrix protein 40 (VP40), which is the most abundant protein found in the virions. Within infected cells VP40 localizes at the inner leaflet of the plasma membrane (PM), binds lipids, and regulates formation of new virus particles. Expression of VP40 in mammalian cells is sufficient to form virus-like particles that are nearly indistinguishable from the authentic virions. However, how VP40 interacts with the PM and forms virus-like particles is for the most part unknown. To investigate VP40 lipid specificity in a model of viral egress we employed giant unilamellar vesicles with different lipid compositions. The results demonstrate VP40 selectively induces vesiculation from membranes containing phosphatidylserine (PS) at concentrations of PS that are representative of the PM inner leaflet content. The formation of intraluminal vesicles was not significantly detected in the presence of other important PM lipids including cholesterol and polyvalent phosphoinositides, further demonstrating PS selectivity. Taken together, these studies suggest that PM phosphatidylserine may be an important component of Ebola virus budding and that VP40 may be able to mediate PM scission.

  3. The initiation of eukaryotic and prokaryotic protein synthesis: a selective accessibility and multisubstrate enzyme reaction.

    PubMed

    Nakamoto, Tokumasa

    2007-11-15

    An extension of our unique accessibility hypothesis for the initiation of protein synthesis is proposed following a review of the initiation of protein synthesis. The E. coli model initiation sequence generated by computer from 68 initiation sequences and the eukaryotic consensus initiation sequence derived by non-computer analysis of 211 initiation sequences do not contain a specific base in any position; they are only assigned preferred bases. The initiation site, in other words, is a varied sequence of preferred bases and its sequence is non-unique. This indicates that the ribosomal recognition of the initiation site may be the result of multiple interactions that are cooperative and cumulative and typical of multisubstrate enzymes. Because of this characteristic, the model of multisubstrate enzymes with broad substrate specificity is proposed as a paradigm for the initiation of protein synthesis. As predicted by this model, changes in the leader and downstream sequences that improve the agreement with the preferred base sequence do indeed enhance the rate of protein synthesis. The eukaryotic/prokaryotic hybrid studies show a considerable overlap in the specificities of the two groups of ribosomes. The scanning of the mRNA from the 5'-end postulated by the scanning hypothesis is not a necessary step since eukaryotic ribosomes are able to bind to internal mRNA sites and initiate synthesis. Our unique accessibility hypothesis, which is extended by coupling cooperative and cumulative specificity in ribosomal function, is referred to for brevity as the cumulative specificity hypothesis. The hypothesis actually postulates a selective accessibility and cooperative-cumulative specificity mechanism; it is able to account for the behavior of both eukaryotic and prokaryotic initiation of protein synthesis. From another perspective, the hypothesis can be regarded as providing a mechanism that enables ribosomes to recognize the IS in the absence of a unique initiation

  4. Selective loss of fine tuning of Gq/11 signaling by RGS2 protein exacerbates cardiomyocyte hypertrophy.

    PubMed

    Zhang, Wei; Anger, Thomas; Su, Jialin; Hao, Jianming; Xu, Xiaomei; Zhu, Ming; Gach, Agnieszka; Cui, Lei; Liao, Ronglih; Mende, Ulrike

    2006-03-03

    Alterations in cardiac G protein-mediated signaling, most prominently G(q/11) signaling, are centrally involved in hypertrophy and heart failure development. Several RGS proteins that can act as negative regulators of G protein signaling are expressed in the heart, but their functional roles are still poorly understood. RGS expression changes have been described in hypertrophic and failing hearts. In this study, we report a marked decrease in RGS2 (but not other major cardiac RGS proteins (RGS3-RGS5)) that occurs prior to hypertrophy development in different models with enhanced G(q/11) signaling (transgenic expression of activated Galpha(q)(*) and pressure overload due to aortic constriction). To assess functional consequences of selective down-regulation of endogenous RGS2, we identified targeting sequences for effective RGS2 RNA interference and used lipid-based transfection to achieve uptake of fluorescently labeled RGS2 small interfering RNA in >90% of neonatal and adult ventricular myocytes. Endogenous RGS2 expression was dose-dependently suppressed (up to 90%) with no major change in RGS3-RGS5. RGS2 knockdown increased phenylephrine- and endothelin-1-induced phospholipase Cbeta stimulation in both cell types and exacerbated the hypertrophic effect (increase in cell size and radiolabeled protein) in neonatal myocytes, with no major change in G(q/11)-mediated ERK1/2, p38, or JNK activation. Taken together, this study demonstrates that endogenous RGS2 exerts functionally important inhibitory restraint on G(q/11)-mediated phospholipase Cbeta activation and hypertrophy in ventricular myocytes. Our findings point toward a potential pathophysiological role of loss of fine tuning due to selective RGS2 down-regulation in G(q/11)-mediated remodeling. Furthermore, this study shows the feasibility of effective RNA interference in cardiomyocytes using lipid-based small interfering RNA transfection.

  5. Unraveling protein misfolding diseases using model systems

    PubMed Central

    Peffer, Sara; Cope, Kimberly; Morano, Kevin A

    2015-01-01

    Experimental model systems have long been used to probe the causes, consequences and mechanisms of pathology leading to human disease. Ideally, such information can be exploited to inform the development of therapeutic strategies or treatments to combat disease progression. In the case of protein misfolding diseases, a wide range of model systems have been developed to investigate different aspects of disorders including Huntington's disease, Parkinson's disease, Alzheimer's disease as well as amyotrophic lateral sclerosis. Utility of these systems broadly correlates with evolutionary complexity: small animal models such as rodents and the fruit fly are appropriate for pharmacological modeling and cognitive/behavioral assessment, the roundworm Caenorhabditis elegans allows analysis of tissue-specific disease features, and unicellular organisms such as the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli are ideal for molecular studies. In this chapter, we highlight key advances in our understanding of protein misfolding/unfolding disease provided by model systems. PMID:28031870

  6. Antibody orientation enhanced by selective polymer-protein noncovalent interactions.

    PubMed

    Clarizia, Lisa-Jo A; Sok, Davin; Wei, Ming; Mead, Joey; Barry, Carol; McDonald, Melisenda J

    2009-03-01

    A unique interaction has been found between protein G' (a truncated recombinant bacterial "alphabet" protein which aligns by noncovalent attachment to the antibody stem) and poly(methyl methacrylate), a thermoplastic polymer substrate, which can be easily fabricated using high-rate processes. Significantly improved orientation efficiency with traditional passive adsorption for this system (termed ALYGNSA) has been achieved as compared to the same assay performed on a polystyrene substrate with protein G'. Results were consistent with an average alignment of 80% of the human immunoglobulin G capture antibody which translated into a 30% to 50% improved alignment over an array of industry standards tested. Laser scanning confocal microscopy confirmed the immunological results. Studies of additional poly(methyl methacrylate) polymer derivatives and protein biolinker (A and AG) combinations have been conducted and have revealed different degrees of antibody alignment. These findings may lead to additional novel noncovalent methods of antibody orientation and greater sensitivity in immunological assays.

  7. Protein scaffolds for selective enrichment of metal ions

    SciTech Connect

    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.

  8. Site-Selective Modification of Proteins with Oxetanes.

    PubMed

    Boutureira, Omar; Martínez-Sáez, Nuria; Brindle, Kevin M; Neves, André A; Corzana, Francisco; Bernardes, Gonçalo J L

    2017-03-05

    Oxetanes are four-membered ring oxygen heterocycles that are advantageously used in medicinal chemistry as modulators of physicochemical properties of small molecules. Herein, we present a simple method for the incorporation of oxetanes into proteins through chemoselective alkylation of cysteine. We demonstrate a broad substrate scope by reacting proteins used as apoptotic markers and in drug formulation, and a therapeutic antibody with a series of 3-oxetane bromides, enabling the identification of novel handles (S-to-S/N rigid, non-aromatic, and soluble linker) and reactivity modes (temporary cysteine protecting group), while maintaining their intrinsic activity. The possibility to conjugate oxetane motifs into full-length proteins has potential to identify novel drug candidates as the next-generation of peptide/protein therapeutics with improved physicochemical and biological properties.

  9. 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

  10. 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

  11. DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues

    PubMed Central

    Guo, Jing; Sun, Xiao

    2016-01-01

    DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/. PMID:27907159

  12. 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.

  13. Tungsten exposure causes a selective loss of histone demethylase protein.

    PubMed

    Laulicht-Glick, Freda; Wu, Feng; Zhang, Xiaoru; Jordan, Ashley; Brocato, Jason; Kluz, Thomas; Sun, Hong; Costa, Max

    2017-02-20

    In the course of our investigations into the toxicity of tungstate, we discovered that cellular exposure resulted in the loss of the histone demethylase protein. We specifically investigated the loss of two histone demethylase dioxygenases, JARID1A and JMJD1A. Both of these proteins were degraded in the presence of tungstate and this resulted in increased global levels of H3K4me3 and H3K9me2, the substrates of JARID1A and JMJD1A, respectively. Treatment with MG132 completely inhibited the loss of the demethylase proteins induced by tungstate treatment, suggesting that tungstate activated the proteasomal degradation of these proteins. The changes in global histone marks and loss of histone demethylase protein persisted for at least 48 h after removing sodium tungstate from the culture. The increase in global histone methylation remained when cells were cultured in methionine-free media, indicating that the increased histone methylation did not depend upon any de novo methylation process, but rather was due to the loss of the demethylase protein. Similar increases of H3K4me3 and H3K9me2 were observed in the livers of the mice that were acutely exposed to tungstate via their drinking water. Taken together, our results indicated that tungstate exposure specifically reduced histone demethylase JARID1A and JMJD1A via proteasomal degradation, leading to increased histone methylation.

  14. Mining flexible-receptor docking experiments to select promising protein receptor snapshots

    PubMed Central

    2010-01-01

    Background Molecular docking simulation is the Rational Drug Design (RDD) step that investigates the affinity between protein receptors and ligands. Typically, molecular docking algorithms consider receptors as rigid bodies. Receptors are, however, intrinsically flexible in the cellular environment. The use of a time series of receptor conformations is an approach to explore its flexibility in molecular docking computer simulations, but it is extensively time-consuming. Hence, selection of the most promising conformations can accelerate docking experiments and, consequently, the RDD efforts. Results We previously docked four ligands (NADH, TCL, PIF and ETH) to 3,100 conformations of the InhA receptor from M. tuberculosis. Based on the receptor residues-ligand distances we preprocessed all docking results to generate appropriate input to mine data. Data preprocessing was done by calculating the shortest interatomic distances between the ligand and the receptor’s residues for each docking result. They were the predictive attributes. The target attribute was the estimated free-energy of binding (FEB) value calculated by the AutodDock3.0.5 software. The mining inputs were submitted to the M5P model tree algorithm. It resulted in short and understandable trees. On the basis of the correlation values, for NADH, TCL and PIF we obtained more than 95% correlation while for ETH, only about 60%. Post processing the generated model trees for each of its linear models (LMs), we calculated the average FEB for their associated instances. From these values we considered a LM as representative if its average FEB was smaller than or equal the average FEB of the test set. The instances in the selected LMs were considered the most promising snapshots. It totalized 1,521, 1,780, 2,085 and 902 snapshots, for NADH, TCL, PIF and ETH respectively. Conclusions By post processing the generated model trees we were able to propose a criterion of selection of linear models which, in turn, is

  15. 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.

  16. 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.

  17. An in vitro selected binding protein (affibody) shows conformation-dependent recognition of the respiratory syncytial virus (RSV) G protein.

    PubMed

    Hansson, M; Ringdahl, J; Robert, A; Power, U; Goetsch, L; Nguyen, T N; Uhlén, M; Ståhl, S; Nygren, P A

    1999-03-01

    Using phage-display technology, a novel binding protein (Z-affibody) showing selective binding to the RSV (Long strain) G protein was selected from a combinatorial library of a small alpha-helical protein domain (Z), derived from staphylococcal protein A (SPA). Biopanning of the Z-library against a recombinant fusion protein comprising amino acids 130-230 of the G protein from RSV-subgroup A, resulted in the selection of a Z-affibody (Z(RSV1)) which showed G protein specific binding. Using biosensor technology, the affinity (K(D)) between Z(RSV1) and the recombinant protein was determined to be in the micromolar range (10(-6) M). Interestingly, the Z(RSV1) affibody was demonstrated to also recognize the partially (54%) homologous G protein of RSV subgroup B with similar affinity. Using different recombinant RSV G protein derived fragments, the binding was found to be dependent on the presence of the cysteinyl residues proposed to be involved in the formation of an intramolecular disulfide-constrained loop structure, indicating a conformation-dependent binding. Results from epitope mapping studies, employing a panel of monoclonal antibodies directed to different RSV G protein subfragments, suggest that the Z(RSV1) affibody binding site is located within the region of amino acids 164-186 of the G protein. This region contains a 13 amino acid residue sequence which is totally conserved between subgroups A and B of RSV and extends into the cystein loop region (amino acids 173-186). The potential use of the RSV G protein-specific Z(RSV1) affibody in diagnostic and therapeutic applications is discussed.

  18. 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...

  19. Investigating protein haptenation mechanisms of skin sensitisers using human serum albumin as a model protein.

    PubMed

    Aleksic, Maja; Pease, Camilla K; Basketter, David A; Panico, Maria; Morris, Howard R; Dell, Anne

    2007-06-01

    Covalent modification of skin proteins by electrophiles is a key event in the induction of skin sensitisation but not skin irritation although the exact nature of the binding mechanisms has not been determined empirically for the vast majority of sensitisers. It is also unknown whether immunologically relevant protein targets exist in the skin contributing to effecting skin sensitisation. To determine the haptenation mechanism(s) and spectra of amino acid reactivity in an intact protein for two sensitisers expected to react by different mechanisms, human serum albumin (HSA) was chosen as a model protein. The aim of this work was also to verify for selected non-sensitisers and irritants that no protein haptenation occurs even under forcing conditions. HSA was incubated with chemicals and the resulting complexes were digested with trypsin and analysed deploying matrix-assisted laser desorption/ionization mass spectrometry, reverse phase high performance liquid chromatography and nano-electrospray tandem mass spectrometry. The data confirmed that different residues (lysine, cysteine, histidine and tyrosine) are covalently modified in a highly selective and differential manner by the sensitisers 2,4-dinitro-1-chlorobenzene and phenyl salicylate. Additionally, non-sensitisers 2,4-dichloro-1-nitrobenzene, butyl paraben and benzaldehyde and irritants benzalkonium chloride and sodium dodecyl sulphate did not covalently modify HSA under any conditions. The data indicate that covalent haptenation is a prerequisite of skin sensitisation but not irritation. The data also suggest that protein modifications are targeted to certain amino acids residing in chemical microenvironments conducive to reactivity within an intact protein. Deriving such information is relevant to our understanding of antigen formation in the immunobiology of skin sensitisation and in the development of in vitro protein haptenation assays.

  20. Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches.

    PubMed

    Yugandhar, K; Gromiha, M Michael

    2014-09-01

    Protein-protein interactions are intrinsic to virtually every cellular process. Predicting the binding affinity of protein-protein complexes is one of the challenging problems in computational and molecular biology. In this work, we related sequence features of protein-protein complexes with their binding affinities using machine learning approaches. We set up a database of 185 protein-protein complexes for which the interacting pairs are heterodimers and their experimental binding affinities are available. On the other hand, we have developed a set of 610 features from the sequences of protein complexes and utilized Ranker search method, which is the combination of Attribute evaluator and Ranker method for selecting specific features. We have analyzed several machine learning algorithms to discriminate protein-protein complexes into high and low affinity groups based on their Kd values. Our results showed a 10-fold cross-validation accuracy of 76.1% with the combination of nine features using support vector machines. Further, we observed accuracy of 83.3% on an independent test set of 30 complexes. We suggest that our method would serve as an effective tool for identifying the interacting partners in protein-protein interaction networks and human-pathogen interactions based on the strength of interactions.

  1. 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

  2. Analyzing models for interactions of aptamers to proteins

    NASA Astrophysics Data System (ADS)

    Silva, Dilson; Missailidis, Sotiris

    2014-10-01

    We have devised an experimental and theoretical model, based on fluorescent spectroscopy and molecular modelling, to describe the interaction of aptamer (selected against various protein targets) with proteins and albumins in particular. This model, described in this work, has allowed us to decipher the nature of the interactions between aptamers and albumins, the binding site of the aptamers to albumins, the potential role of primer binding to the albumin and expand to the ability of albumin to carry aptamers in the bloodstream, providing data to better understand the level of free aptamer for target binding. We are presenting the study of a variety of aptamers, including those against the MUC1 tumour marker, heparanase and human kallikrein 6 with bovine and human serum albumins and the effect these interactions may have on the bioavailability of the aptamer for target-specific binding and therapeutic activity.

  3. Fold assessment for comparative protein structure modeling

    PubMed Central

    Melo, Francisco; Sali, Andrej

    2007-01-01

    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. PMID:17905832

  4. 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.

  5. Positive Darwinian selection drives the evolution of several female reproductive proteins in mammals

    PubMed Central

    Swanson, Willie J.; Yang, Ziheng; Wolfner, Mariana F.; Aquadro, Charles F.

    2001-01-01

    Rapid evolution driven by positive Darwinian selection is a recurrent theme in male reproductive protein evolution. In contrast, positive selection has never been demonstrated for female reproductive proteins. Here, we perform phylogeny-based tests on three female mammalian fertilization proteins and demonstrate positive selection promoting their divergence. Two of these female fertilization proteins, the zona pellucida glycoproteins ZP2 and ZP3, are part of the mammalian egg coat. Several sites identified in ZP3 as likely to be under positive selection are located in a region previously demonstrated to be involved in species-specific sperm-egg interaction, suggesting the selective pressure is related to male-female interaction. The results provide long-sought evidence for two evolutionary hypotheses: sperm competition and sexual conflict. PMID:11226269

  6. Model for personal computer system selection.

    PubMed

    Blide, L

    1987-12-01

    Successful computer software and hardware selection is best accomplished by following an organized approach such as the one described in this article. The first step is to decide what you want to be able to do with the computer. Secondly, select software that is user friendly, well documented, bug free, and that does what you want done. Next, you select the computer, printer and other needed equipment from the group of machines on which the software will run. Key factors here are reliability and compatibility with other microcomputers in your facility. Lastly, you select a reliable vendor who will provide good, dependable service in a reasonable time. The ability to correctly select computer software and hardware is a key skill needed by medical record professionals today and in the future. Professionals can make quality computer decisions by selecting software and systems that are compatible with other computers in their facility, allow for future net-working, ease of use, and adaptability for expansion as new applications are identified. The key to success is to not only provide for your present needs, but to be prepared for future rapid expansion and change in your computer usage as technology and your skills grow.

  7. Detection of peptides, proteins, and drugs that selectively interact with protein targets.

    PubMed

    Serebriiskii, Ilya G; Mitina, Olga; Pugacheva, Elena N; Benevolenskaya, Elizaveta; Kotova, Elena; Toby, Garabet G; Khazak, Vladimir; Kaelin, William G; Chernoff, Jonathan; Golemis, Erica A

    2002-11-01

    Genome sequencing has been completed for multiple organisms, and pilot proteomic analyses reported for yeast and higher eukaryotes. This work has emphasized the facts that proteins are frequently engaged in multiple interactions, and that governance of protein interaction specificity is a primary means of regulating biological systems. In particular, the ability to deconvolute complex protein interaction networks to identify which interactions govern specific signaling pathways requires the generation of biological tools that allow the distinction of critical from noncritical interactions. We report the application of an enhanced Dual Bait two-hybrid system to allow detection and manipulation of highly specific protein-protein interactions. We summarize the use of this system to detect proteins and peptides that target well-defined specific motifs in larger protein structures, to facilitate rapid identification of specific interactors from a pool of putative interacting proteins obtained in a library screen, and to score specific drug-mediated disruption of protein-protein interaction.

  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. 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. Expression Trend of Selected Ribosomal Protein Genes in Nasopharyngeal Carcinoma

    PubMed Central

    Ma, Xiang-Ru; Sim, Edmund Ui-Hang; Ling, Teck-Yee; Tiong, Thung-Sing; Subramaniam, Selva Kumar; Khoo, Alan Soo-Beng

    2012-01-01

    Background: Ribosomal proteins are traditionally associated with protein biosynthesis until recent studies that implicated their extraribosomal functions in human diseases and cancers. Our previous studies using GeneFishing™ DEG method and microarray revealed underexpression of three ribosomal protein genes, RPS26, RPS27, and RPL32 in cancer of the nasopharynx. Herein, we investigated the expression pattern and nucleotide sequence integrity of these genes in nasopharyngeal carcinoma to further delineate their involvement in tumourigenesis. The relationship of expression level with clinicopathologic factors was also statistically studied. Methods: Quantitative Polymerase Chain Reaction was performed on nasopharyngeal carcinoma and their paired normal tissues. Expression and sequence of these three genes were analysed. Results: All three ribosomal protein genes showed no significant difference in transcript expressions and no association could be established with clinicopathologic factors studied. No nucleotide aberrancy was detected in the coding regions of these genes. Conclusion: There is no early evidence to substantiate possible involvement of RPS26, RPS27, and RPL32 genes in NPC tumourigenesis. PMID:23613646

  11. Modeling and minimizing CAPRI round 30 symmetrical protein complexes from CASP-11 structural models.

    PubMed

    El Houasli, Marwa; Maigret, Bernard; Devignes, Marie-Dominique; Ghoorah, Anisah W; Grudinin, Sergei; Ritchie, David W

    2017-03-01

    Many of the modeling targets in the blind CASP-11/CAPRI-30 experiment were protein homo-dimers and homo-tetramers. Here, we perform a retrospective docking-based analysis of the perfectly symmetrical CAPRI Round 30 targets whose crystal structures have been published. Starting from the CASP "stage-2" fold prediction models, we show that using our recently developed "SAM" polar Fourier symmetry docking algorithm combined with NAMD energy minimization often gives acceptable or better 3D models of the target complexes. We also use SAM to analyze the overall quality of all CASP structural models for the selected targets from a docking-based perspective. We demonstrate that docking only CASP "center" structures for the selected targets provides a fruitful and economical docking strategy. Furthermore, our results show that many of the CASP models are dockable in the sense that they can lead to acceptable or better models of symmetrical complexes. Even though SAM is very fast, using docking and NAMD energy minimization to pull out acceptable docking models from a large ensemble of docked CASP models is computationally expensive. Nonetheless, thanks to our SAM docking algorithm, we expect that applying our docking protocol on a modern computer cluster will give us the ability to routinely model 3D structures of symmetrical protein complexes from CASP-quality models. Proteins 2017; 85:463-469. © 2016 Wiley Periodicals, Inc.

  12. Positive selection neighboring functionally essential sites and disease-implicated regions of mammalian reproductive proteins

    PubMed Central

    2010-01-01

    Background Reproductive proteins are central to the continuation of all mammalian species. The evolution of these proteins has been greatly influenced by environmental pressures induced by pathogens, rival sperm, sexual selection and sexual conflict. Positive selection has been demonstrated in many of these proteins with particular focus on primate lineages. However, the mammalia are a diverse group in terms of mating habits, population sizes and germ line generation times. We have examined the selective pressures at work on a number of novel reproductive proteins across a wide variety of mammalia. Results We show that selective pressures on reproductive proteins are highly varied. Of the 10 genes analyzed in detail, all contain signatures of positive selection either across specific sites or in specific lineages or a combination of both. Our analysis of SP56 and Col1a1 are entirely novel and the results show positively selected sites present in each gene. Our findings for the Col1a1 gene are suggestive of a link between positive selection and severe disease type. We find evidence in our dataset to suggest that interacting proteins are evolving in symphony: most likely to maintain interacting functionality. Conclusion Our in silico analyses show positively selected sites are occurring near catalytically important regions suggesting selective pressure to maximize efficient fertilization. In those cases where a mechanism of protein function is not fully understood, the sites presented here represent ideal candidates for mutational study. This work has highlighted the widespread rate heterogeneity in mutational rates across the mammalia and specifically has shown that the evolution of reproductive proteins is highly varied depending on the species and interacting partners. We have shown that positive selection and disease are closely linked in the Col1a1 gene. PMID:20149245

  13. 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.

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

    PubMed Central

    Rodrigue, Nicolas; Philippe, Hervé; Lartillot, Nicolas

    2010-01-01

    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

  15. Proteomics reveals selective regulation of proteins in response to memory-related serotonin stimulation in Aplysia californica ganglia.

    PubMed

    Monje, Francisco J; Birner-Gruenberger, Ruth; Darnhofer, Barbara; Divisch, Isabella; Pollak, Daniela D; Lubec, Gert

    2012-02-01

    The marine mollusk Aplysia californica (Aplysia) is a powerful model for learning and memory due to its minimalistic nervous system. Key proteins, identified to be regulated by the neurotransmitter serotonin in Aplysia, have been successfully translated to mammalian models of learning and memory. Based upon a recently published large-scale analysis of Aplysia proteomic data, the current study investigated the regulation of protein levels 24 and 48 h after treatment with serotonin in Aplysia ganglia using a 2-D gel electrophoresis approach. Protein spots were quantified and protein-level changes of selected proteins were verified by Western blotting. Among those were Rab GDP dissociation inhibitor alpha (RabGDIα), synaptotagmin-1 and deleted in azoospermia-associated protein (DAZAP-1) in cerebral ganglia, calreticulin, RabGDIα, DAZAP-1, heterogeneous nuclear ribonucleoprotein F (hnRNPF), RACK-1 and actin-depolymerizing factor (ADF) in pleural ganglia and DAZAP-1, hnRNPF and ADF in pedal ganglia. Protein identity of the majority of spots was confirmed by a gel-based mass spectrometrical method (FT-MS). Taken together, protein-level changes induced by the learning-related neurotransmitter serotonin in Aplysia ganglia are described and a role for the abovementioned proteins in synaptic plasticity is proposed.

  16. 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.

  17. Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins.

    PubMed

    Nagarajan, R; Ahmad, Shandar; Gromiha, M Michael

    2013-09-01

    Protein-DNA complexes play vital roles in many cellular processes by the interactions of amino acids with DNA. Several computational methods have been developed for predicting the interacting residues in DNA-binding proteins using sequence and/or structural information. These methods showed different levels of accuracies, which may depend on the choice of data sets used in training, the feature sets selected for developing a predictive model, the ability of the models to capture information useful for prediction or a combination of these factors. In many cases, different methods are likely to produce similar results, whereas in others, the predictors may return contradictory predictions. In this situation, a priori estimates of prediction performance applicable to the system being investigated would be helpful for biologists to choose the best method for designing their experiments. In this work, we have constructed unbiased, stringent and diverse data sets for DNA-binding proteins based on various biologically relevant considerations: (i) seven structural classes, (ii) 86 folds, (iii) 106 superfamilies, (iv) 194 families, (v) 15 binding motifs, (vi) single/double-stranded DNA, (vii) DNA conformation (A, B, Z, etc.), (viii) three functions and (ix) disordered regions. These data sets were culled as non-redundant with sequence identities of 25 and 40% and used to evaluate the performance of 11 different methods in which online services or standalone programs are available. We observed that the best performing methods for each of the data sets showed significant biases toward the data sets selected for their benchmark. Our analysis revealed important data set features, which could be used to estimate these context-specific biases and hence suggest the best method to be used for a given problem. We have developed a web server, which considers these features on demand and displays the best method that the investigator should use. The web server is freely available at

  18. Light scattering evidence of selective protein fouling on biocompatible block copolymer micelles

    NASA Astrophysics Data System (ADS)

    Giacomelli, Fernando C.; Stepánek, Petr; Schmidt, Vanessa; Jäger, Eliézer; Jäger, Alessandro; Giacomelli, Cristiano

    2012-07-01

    Selective protein fouling on block copolymer micelles with well-known potential for tumour-targeting drug delivery was evidenced by using dynamic light scattering measurements. The stability and interaction of block copolymer micelles with model proteins (BSA, IgG, lysozyme and CytC) is reported for systems featuring a hydrophobic (poly[2-(diisopropylamino)-ethyl methacrylate]) (PDPA) core and hydrophilic coronas comprising poly(ethylene oxide)/poly(glycerol monomethacrylate) (PEO-b-PG2MA) or poly[2-(methacryloyloxy)ethyl phosphorylcholine] (PMPC). The results revealed that protein size and hydrophilic chain density play important roles in the observed interactions. The PEO113-b-PG2MA30-b-PDPA50 nanoparticles are stable and protein adsorption is prevented at all investigated protein environments. The successful protein-repellent characteristic of these nanoparticles is attributed to a high hydrophilic surface chain density (>0.1 chains per nm2) and to the length of the hydrophilic chains. On the other hand, although PMPC also has protein-repellent characteristics, the low surface chain density of the hydrophilic shell is supposed to enable interactions with small proteins. The PMPC40-b-PDPA70 micelles are stable in BSA and IgG environments due to weak repulsion forces between PMPC and the proteins, to the hydration layer, and particularly to a size-effect where the large BSA (RH = 4.2 nm) and IgG (RH = 7.0 nm) do not easily diffuse within the PMPC shell. Conversely, a clear interaction was observed with the 2.1 nm radius lysozyme. The lysozyme protein can diffuse within the PMPC micellar shell towards the PDPA hydrophobic core in a process favored by its smaller size and the low hydrophilic PMPC surface chain density (~0.049 chains per nm2) as compared to PEO-b-PG2MA (~0.110 chains per nm2). The same behavior was not evidenced with the 2.3 nm radius positively charged CytC, probably due to its higher surface hydrophilicity and the consequent chemical

  19. 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

  20. Monoclonal antibody selection for interleukin-4 quantification using suspension arrays and forward-phase protein microarrays.

    PubMed

    Wang, L; Cole, K D; Peterson, A; He, Hua-Jun; Gaigalas, A K; Zong, Y

    2007-12-01

    A recombinant mouse interleukin-4 (IL-4) and three different purified rat antimouse IL-4 monoclonal antibodies (Mab) with different clonalities were employed as a model system. This system was used to examine monoclonal antibody effectiveness using both conventional and high-throughput measurement techniques to select antibodies for attaining the most sensitive detection of the recombinant IL-4 through the "sandwich-type" immunoassays. Surface plasmon resonance (SPR) measurements and two high-throughput methods, suspension arrays (also called multiplexed bead arrays) and forward-phase protein microarrays, predicted the same capture (BVD4-1D11) and detection (BVD6-24G2) antibody pair for the most sensitive detection of the recombinant cytokine. By using this antibody pair, we were able to detect as low as 2 pg/mL of IL-4 in buffer solution and 13.5 pg/mL of IL-4 spiked in 100% normal mouse serum with the multiplexed bead arrays. Due to the large amount of material required for SPR measurements, the study suggests that the multiplexed bead arrays and protein microarrays are both suited for the selection of numerous antibodies against the same analyte of interest to meet the need in the areas of systems biology and reproducible clinical diagnostics for better patient care.

  1. 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

    2014-02-07

    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.

  2. Modeling of chemical inhibition from amyloid protein aggregation kinetics

    PubMed Central

    2014-01-01

    Backgrounds The process of amyloid proteins aggregation causes several human neuropathologies. In some cases, e.g. fibrillar deposits of insulin, the problems are generated in the processes of production and purification of protein and in the pump devices or injectable preparations for diabetics. Experimental kinetics and adequate modelling of chemical inhibition from amyloid aggregation are of practical importance in order to study the viable processing, formulation and storage as well as to predict and optimize the best conditions to reduce the effect of protein nucleation. Results In this manuscript, experimental data of insulin, Aβ42 amyloid protein and apomyoglobin fibrillation from recent bibliography were selected to evaluate the capability of a bivariate sigmoid equation to model them. The mathematical functions (logistic combined with Weibull equation) were used in reparameterized form and the effect of inhibitor concentrations on kinetic parameters from logistic equation were perfectly defined and explained. The surfaces of data were accurately described by proposed model and the presented analysis characterized the inhibitory influence on the protein aggregation by several chemicals. Discrimination between true and apparent inhibitors was also confirmed by the bivariate equation. EGCG for insulin (working at pH = 7.4/T = 37°C) and taiwaniaflavone for Aβ42 were the compounds studied that shown the greatest inhibition capacity. Conclusions An accurate, simple and effective model to investigate the inhibition of chemicals on amyloid protein aggregation has been developed. The equation could be useful for the clear quantification of inhibitor potential of chemicals and rigorous comparison among them. PMID:24572069

  3. Optimizing the selective recognition of protein isoforms through tuning of nanoparticle hydrophobicity†

    PubMed Central

    Moyano, Daniel F.; Xu, Yisheng; Rotello, Vincent M.

    2014-01-01

    We demonstrate that ligand hydrophobicity can be used to increase affinity and selectivity of binding between monolayer-protected cationic gold nanoparticles and β– lactoglobulin protein isoforms containing two amino acid mutations. PMID:24838611

  4. 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

  5. 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

  6. Coupling between protein level selection and codon usage optimization in the evolution of bacteria and archaea.

    PubMed

    Ran, Wenqi; Kristensen, David M; Koonin, Eugene V

    2014-03-25

    The relationship between the selection affecting codon usage and selection on protein sequences of orthologous genes in diverse groups of bacteria and archaea was examined by using the Alignable Tight Genome Clusters database of prokaryote genomes. The codon usage bias is generally low, with 57.5% of the gene-specific optimal codon frequencies (Fopt) being below 0.55. This apparent weak selection on codon usage contrasts with the strong purifying selection on amino acid sequences, with 65.8% of the gene-specific dN/dS ratios being below 0.1. For most of the genomes compared, a limited but statistically significant negative correlation between Fopt and dN/dS was observed, which is indicative of a link between selection on protein sequence and selection on codon usage. The strength of the coupling between the protein level selection and codon usage bias showed a strong positive correlation with the genomic GC content. Combined with previous observations on the selection for GC-rich codons in bacteria and archaea with GC-rich genomes, these findings suggest that selection for translational fine-tuning could be an important factor in microbial evolution that drives the evolution of genome GC content away from mutational equilibrium. This type of selection is particularly pronounced in slowly evolving, "high-status" genes. A significantly stronger link between the two aspects of selection is observed in free-living bacteria than in parasitic bacteria and in genes encoding metabolic enzymes and transporters than in informational genes. These differences might reflect the special importance of translational fine-tuning for the adaptability of gene expression to environmental changes. The results of this work establish the coupling between protein level selection and selection for translational optimization as a distinct and potentially important factor in microbial evolution. IMPORTANCE Selection affects the evolution of microbial genomes at many levels, including both

  7. 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.

  8. Large-scale identification of putative exported proteins in Candida albicans by genetic selection.

    PubMed

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

    2002-08-01

    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.

  9. 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

  10. Comparison of descriptors for predicting selectivity of protein-imprinted polymers.

    PubMed

    Raim, Vladimir; Zadok, Israel; Srebnik, Simcha

    2016-08-01

    Molecular imprinting is a technique that is used to create artificial receptors by the formation of a polymer network around a template molecule, creating a molecularly imprinted polymer. These artificial receptors may be used in applications that require molecular recognition, such as enantioseparations, biosensors, artificial catalysis, drug delivery and others. Small molecules, such as drugs, have been imprinted with high efficiency and, combined with the low cost of preparation, molecularly imprinted polymers have acquired commercial usage. While attempts at imprinting proteins have been significantly less successful, the great potential of protein-imprinted polymers (PIPs) in medicine and industry attracted much research. Multifunctionality, conformational flexibility, large size of the proteins, and aqueous polymerization environment are some of the obstacles faced by protein imprinting. We explore the relation between PIP selectivity and the properties of the template and competitor proteins. A comprehensive statistical analysis of published studies reveals a statistically significant correlation between four protein descriptors and the corresponding selectivity of PIPs. Namely, a PIP will generally be more selective against large competitor proteins with a smooth surface, whose isoelectric point and aspect ratio are significantly different than those of the template protein. The size of the protein, as measured by its molecular weight, appears to be independent of the template protein characteristics. Copyright © 2016 John Wiley & Sons, Ltd.

  11. 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

  12. Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization.

    PubMed

    Cao, Junzhe; Liu, Wenqi; He, Jianjun; Gu, Hong

    2013-01-01

    Subcellular localization of a protein is important to understand proteins' functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the "value" of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers.

  13. Fabrication of nanometer-sized protein patterns using atomic force microscopy and selective immobilization.

    PubMed Central

    Wadu-Mesthrige, K; Amro, N A; Garno, J C; Xu, S; Liu , G

    2001-01-01

    A new methodology is introduced to produce nanometer-sized protein patterns. The approach includes two main steps, nanopatterning of self-assembled monolayers using atomic force microscopy (AFM)-based nanolithography and subsequent selective immobilization of proteins on the patterned monolayers. The resulting templates and protein patterns are characterized in situ using AFM. Compared with conventional protein fabrication methods, this approach is able to produce smaller patterns with higher spatial precision. In addition, fabrication and characterization are completed in near physiological conditions. The adsorption configuration and bioreactivity of the proteins within the nanopatterns are also studied in situ. PMID:11259301

  14. Kainic acid inhibits protein amino acid incorporation in select rat brain regions.

    PubMed

    Planas, A M; Soriano, M A; Ferrer, I; Rodríguez-Farré, E

    1994-11-21

    Regional incorporation of labelled methionine into proteins was studied with quantitative autoradiography in different regions of the rat brain 2.5 h following systemic kainic acid administration. Labelled protein concentration was found reduced to approximately 40% of control values in the pyramidal cell layer of hippocampus, piriform, entorhinal and perirhinal cortices, ventral lateral septum and mediodorsal thalamic nucleus. These regions showed increased levels of label not incorporated into proteins, indicating that free labelled methionine was available for protein synthesis. Reduction of protein amino acid incorporation in those brain regions selectively affected by kainic acid may be involved in subsequent tissue damage.

  15. Model Selection for Monitoring CO2 Plume during Sequestration

    SciTech Connect

    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 of 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.

  16. 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…

  17. Discovery of Sulfonamidebenzamides as Selective Apoptotic CHOP Pathway Activators of the Unfolded Protein Response

    PubMed Central

    2014-01-01

    Cellular proteins that fail to fold properly result in inactive or disfunctional proteins that can have toxic functions. The unfolded protein response (UPR) is a two-tiered cellular mechanism initiated by eukaryotic cells that have accumulated misfolded proteins within the endoplasmic reticulum (ER). An adaptive pathway facilitates the clearance of the undesired proteins; however, if overwhelmed, cells trigger apoptosis by upregulating transcription factors such as C/EBP-homologous protein (CHOP). A high throughput screen was performed directed at identifying compounds that selectively upregulate the apoptotic CHOP pathway while avoiding adaptive signaling cascades, resulting in a sulfonamidebenzamide chemotype that was optimized. These efforts produced a potent and selective CHOP inducer (AC50 = 0.8 μM; XBP1 > 80 μM), which was efficacious in both mouse embryonic fibroblast cells and a human oral squamous cell cancer cell line, and demonstrated antiproliferative effects for multiple cancer cell lines in the NCI-60 panel. PMID:25530830

  18. 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

  19. 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.

  20. Simple model of membrane proteins including solvent.

    PubMed

    Pagan, D L; Shiryayev, A; Connor, T P; Gunton, J D

    2006-05-14

    We report a numerical simulation for the phase diagram of a simple two-dimensional model, similar to the one proposed by Noro and Frenkel [J. Chem. Phys. 114, 2477 (2001)] for membrane proteins, but one that includes the role of the solvent. We first use Gibbs ensemble Monte Carlo simulations to determine the phase behavior of particles interacting via a square-well potential in two dimensions for various values of the interaction range. A phenomenological model for the solute-solvent interactions is then studied to understand how the fluid-fluid coexistence curve is modified by solute-solvent interactions. It is shown that such a model can yield systems with liquid-liquid phase separation curves that have both upper and lower critical points, as well as closed loop phase diagrams, as is the case with the corresponding three-dimensional model.

  1. Animal models of protein allergenicity: potential benefits, pitfalls and challenges.

    PubMed

    Dearman, R J; Kimber, I

    2009-04-01

    Food allergy is an important health issue. With an increasing interest in novel foods derived from transgenic crop plants, there is a growing need for the development of approaches suitable for the characterization of the allergenic potential of proteins. There are methods available currently (such as homology searches and serological testing) that are very effective at identifying proteins that are likely to cross-react with known allergens. However, animal models may play a role in the identification of truly novel proteins, such as bacterial or fungal proteins, that have not been experienced previously in the diet. We consider here the potential benefits, pitfalls and challenges of the selection of various animal models, including the mouse, the rat, the dog and the neonatal swine. The advantages and disadvantages of various experimental end-points are discussed, including the measurement of specific IgE by ELISA, Western blotting or functional tests such as the passive cutaneous anaphylaxis assay, and the assessment of challenge-induced clinical symptoms in previously sensitized animals. The experimental variables of route of exposure to test proteins and the incorporation of adjuvant to increase the sensitivity of the responses are considered also. It is important to emphasize that currently none of these approaches has been validated for the purposes of hazard identification in the context of a safety assessment. However, the available evidence suggests that the judicious use of an accurate and robust animal model could provide important additional data that would contribute significantly to the assessment of the potential allergenicity of novel proteins.

  2. 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.

  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. Truly Absorbed Microbial Protein Synthesis, Rumen Bypass Protein, Endogenous Protein, and Total Metabolizable Protein from Starchy and Protein-Rich Raw Materials: Model Comparison and Predictions.

    PubMed

    Parand, Ehsan; Vakili, Alireza; Mesgaran, Mohsen Danesh; van Duinkerken, Gert; Yu, Peiqiang

    2015-07-29

    This study was carried out to measure truly absorbed microbial protein synthesis, rumen bypass protein, and endogenous protein loss, as well as total metabolizable protein, from starchy and protein-rich raw feed materials with model comparisons. Predictions by the DVE2010 system as a more mechanistic model were compared with those of two other models, DVE1994 and NRC-2001, that are frequently used in common international feeding practice. DVE1994 predictions for intestinally digestible rumen undegradable protein (ARUP) for starchy concentrates were higher (27 vs 18 g/kg DM, p < 0.05, SEM = 1.2) than predictions by the NRC-2001, whereas there was no difference in predictions for ARUP from protein concentrates among the three models. DVE2010 and NRC-2001 had highest estimations of intestinally digestible microbial protein for starchy (92 g/kg DM in DVE2010 vs 46 g/kg DM in NRC-2001 and 67 g/kg DM in DVE1994, p < 0.05 SEM = 4) and protein concentrates (69 g/kg DM in NRC-2001 vs 31 g/kg DM in DVE1994 and 49 g/kg DM in DVE2010, p < 0.05 SEM = 4), respectively. Potential protein supplies predicted by tested models from starchy and protein concentrates are widely different, and comparable direct measurements are needed to evaluate the actual ability of different models to predict the potential protein supply to dairy cows from different feedstuffs.

  6. Selection of soluble protein expression constructs: the experimental determination of protein domain boundaries.

    PubMed

    Dyson, Michael R

    2010-08-01

    Proteins can contain multiple domains each of which is capable of possessing a separate independent function and three-dimensional structure. It is often useful to clone and express individual protein domains to study their biochemical properties and for structure determination. However, the annotated domain boundaries in databases such as Pfam or SMART are not always accurate. The present review summarizes various strategies for the experimental determination of protein domain boundaries.

  7. 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

  8. Nonmathematical Models for Evolution of Altruism, and for Group Selection

    PubMed Central

    Darlington, P. J.

    1972-01-01

    Mathematical biologists have failed to produce a satisfactory general model for evolution of altruism, i.e., of behaviors by which “altruists” benefit other individuals but not themselves; kin selection does not seem to be a sufficient explanation of nonreciprocal altruism. Nonmathematical (but mathematically acceptable) models are now proposed for evolution of negative altruism in dual-determinant and of positive altruism in tri-determinant systems. Peck orders, territorial systems, and an ant society are analyzed as examples. In all models, evolution is primarily by individual selection, probably supplemented by group selection. Group selection is differential extinction of populations. It can act only on populations preformed by selection at the individual level, but can either cancel individual selective trends (effecting evolutionary homeostasis) or supplement them; its supplementary effect is probably increasingly important in the evolution of increasingly organized populations. PMID:4501113

  9. 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

  10. Selection of DNA aptamers against VEGF165 using a protein competitor and the aptamer blotting method.

    PubMed

    Hasegawa, Hijiri; Sode, Koji; Ikebukuro, Kazunori

    2008-05-01

    Two DNA aptamers against a tumor marker protein, human vascular endothelial growth factor (VEGF(165)) were identified. In the screening process, another protein was used as the competitor to isolate those aptamers that have high specificity for the target. In addition, we evaluated the affinities of the enriched library by means of aptamer blotting. The isolated aptamers bound to VEGF(165) with a K(d) value in the range of a few hundred nanomoles, and did not bind to the competitor. This selection method enabled us to efficiently select the specific aptamers against the target protein. These specific aptamers would be useful sensor elements for cancer diagnosis.

  11. Development of SPAWM: selection program for available watershed models.

    PubMed

    Cho, Yongdeok; Roesner, Larry A

    2014-01-01

    A selection program for available watershed models (also known as SPAWM) was developed. Thirty-three commonly used watershed models were analyzed in depth and classified in accordance to their attributes. These attributes consist of: (1) land use; (2) event or continuous; (3) time steps; (4) water quality; (5) distributed or lumped; (6) subsurface; (7) overland sediment; and (8) best management practices. Each of these attributes was further classified into sub-attributes. Based on user selected sub-attributes, the most appropriate watershed model is selected from the library of watershed models. SPAWM is implemented using Excel Visual Basic and is designed for use by novices as well as by experts on watershed modeling. It ensures that the necessary sub-attributes required by the user are captured and made available in the selected watershed model.

  12. 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.

  13. The expanded octarepeat domain selectively binds prions and disrupts homomeric prion protein interactions.

    PubMed

    Leliveld, Sirik Rutger; Dame, Remus Thei; Wuite, Gijs J L; Stitz, Lothar; Korth, Carsten

    2006-02-10

    Insertion of additional octarepeats into the prion protein gene has been genetically linked to familial Creutzfeldt Jakob disease and hence to de novo generation of infectious prions. The pivotal event during prion formation is the conversion of the normal prion protein (PrPC) into the pathogenic conformer PrPSc, which subsequently induces further conversion in an autocatalytic manner. Apparently, an expanded octarepeat domain directs folding of PrP toward the PrPSc conformation and initiates a self-replicating conversion process. Here, based on three main observations, we have provided a model on how altered molecular interactions between wild-type and mutant PrP set the stage for familial Creutzfeldt Jakob disease with octarepeat insertions. First, we showed that wild-type octarepeat domains interact in a copper-dependent and reversible manner, a "copper switch." This interaction becomes irreversible upon domain expansion, possibly reflecting a loss of function. Second, expanded octarepeat domains of increasing length gradually form homogenous globular multimers of 11-21 nm in the absence of copper ions when expressed as soluble glutathione S-transferase fusion proteins. Third, octarepeat domain expansion causes a gain of function with at least 10 repeats selectively binding PrPSc in a denaturant-resistant complex in the absence of copper ions. Thus, the combination of both a loss and gain of function profoundly influences homomeric interaction behavior of PrP with an expanded octarepeat domain. A multimeric cluster of prion proteins carrying expanded octarepeat domains may therefore capture and incorporate spontaneously arising short-lived PrPSc-like conformers, thereby providing a matrix for their conversion.

  14. The genealogy of samples in models with selection.

    PubMed

    Neuhauser, C; Krone, S M

    1997-02-01

    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.

  15. 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

  16. Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization

    PubMed Central

    Cao, Junzhe; Liu, Wenqi; He, Jianjun; Gu, Hong

    2013-01-01

    Subcellular localization of a protein is important to understand proteins’ functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the “value” of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers. PMID:23840667

  17. 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

  18. 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

  19. Detection of Peptides, Proteins, and Drugs That Selectively Interact With Protein Targets

    PubMed Central

    Serebriiskii, Ilya G.; Mitina, Olga; Pugacheva, Elena N.; Benevolenskaya, Elizaveta; Kotova, Elena; Toby, Garabet G.; Khazak, Vladimir; Kaelin, William G.; Chernoff, Jonathan; Golemis, Erica A.

    2002-01-01

    Genome sequencing has been completed for multiple organisms, and pilot proteomic analyses reported for yeast and higher eukaryotes. This work has emphasized the facts that proteins are frequently engaged in multiple interactions, and that governance of protein interaction specificity is a primary means of regulating biological systems. In particular, the ability to deconvolute complex protein interaction networks to identify which interactions govern specific signaling pathways requires the generation of biological tools that allow the distinction of critical from noncritical interactions. We report the application of an enhanced Dual Bait two-hybrid system to allow detection and manipulation of highly specific protein–protein interactions. We summarize the use of this system to detect proteins and peptides that target well-defined specific motifs in larger protein structures, to facilitate rapid identification of specific interactors from a pool of putative interacting proteins obtained in a library screen, and to score specific drug-mediated disruption of protein–protein interaction. [Supplemental material is available online at http://www.genome.org. The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: A. Taliana, M. Russell, M. Berman, and R. Finley.] PMID:12421766

  20. Isolation of calcium-binding proteins on selective adsorbents. Application to purification of bovine calmodulin.

    PubMed

    Chaga, G S; Ersson, B; Porath, J O

    1996-05-03

    We report the fractionation of calcium-binding proteins using immobilized metal ion affinity chromatography (IMAC) with hard metal ions. Various hard metal ions (Mn2+, La3+, Nd3+, Eu(3 were immobilized on cross-linked agarose substituted with Tris(carboxymethyl)ethylenediamine (TED) and used as an adsorbent. After systematic studies, europium was selected for further work on the fractionation of calcium-binding proteins. It was found that the presence of Ca2+ in the sample and the solvent strongly promoted the adsorption and selectivity. Selective elution was accomplished in stepwise mode by the addition of calcium chelators such as malonate, citrate and phosphate. Calmodulin of high purity was isolated from a crude extract. Similar behavior of other calcium-binding proteins indicates that the reported chromatographic procedure can be generally applied to such proteins.

  1. Structural elements of metal selectivity in metal sensor proteins.

    PubMed

    Pennella, Mario A; Shokes, Jacob E; Cosper, Nathaniel J; Scott, Robert A; Giedroc, David P

    2003-04-01

    Staphylococcus aureus CzrA and Mycobacterium tuberculosis NmtR are homologous zinccobalt-responsive and nickelcobalt-responsive transcriptional repressors in vivo, respectively, and members of the ArsRSmtB superfamily of prokaryotic metal sensor proteins. We show here that Zn(II) is the most potent negative allosteric regulator of czr operatorpromoter binding in vitro with the trend Zn(II)>Co(II)Ni(II), whereas the opposite holds for the binding of NmtR to the nmt operatorpromoter, Ni(II)>Co(II)>Zn(II). Characterization of the metal coordination complexes of CzrA and NmtR by UVvisible and x-ray absorption spectroscopies reveals that metals that form four-coordinate tetrahedral complexes with CzrA [Zn(II) and Co(II)] are potent regulators of DNA binding, whereas metals that form five- or six-coordinate complexes with NmtR [Ni(II) and Co(II)] are the strongest allosteric regulators in this system. Strikingly, the Zn(II) coordination complexes of CzrA and NmtR cannot be distinguished from one another by x-ray absorption spectroscopy, with the best fit a His-3-carboxylate complex in both cases. Inspection of the primary structures of CzrA and NmtR, coupled with previous functional data, suggests that three conserved His and one Asp from the C-terminal alpha5 helix donate ligands to create a four-coordinate complex in both CzrA and NmtR, with NmtR uniquely capable of expanding its coordination number in the Ni(II) and Co(II) complexes by recruiting additional His ligands from a C-terminal extension of the alpha5 helix.

  2. Model selection in systems biology depends on experimental design.

    PubMed

    Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Stumpf, Michael P H

    2014-06-01

    Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis.

  3. Model Selection in Systems Biology Depends on Experimental Design

    PubMed Central

    Silk, Daniel; Kirk, Paul D. W.; Barnes, Chris P.; Toni, Tina; Stumpf, Michael P. H.

    2014-01-01

    Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis. PMID:24922483

  4. Remedial action selection using groundwater modeling

    SciTech Connect

    Haddad, B.I.; Parish, G.B.; Hauge, L.

    1996-12-31

    An environmental investigation uncovered petroleum contamination at a gasoline station in southern Wisconsin. The site was located in part of the ancestral Rock River valley in Rock County, Wisconsin where the valley is filled with sands and gravels. Groundwater pump tests were conducted for determination of aquifer properties needed to plan a remediation system; the results were indicative of a very high hydraulic conductivity. The site hydrogeology was modeled using the U.S. Geological Survey`s groundwater model, Modflow. The calibrated model was used to determine the number, pumping rate, and configuration of recovery wells to remediate the site. The most effective configuration was three wells pumping at 303 liters per minute (1/m) (80 gallons per minute (gpm)), producing a total pumping rate of 908 l/m (240 gpm). Treating 908 l/min (240 gpm) or 1,308,240 liters per day (345,600 gallons per day) constituted a significant volume to be treated and discharged. It was estimated that pumping for the two year remediation would cost $375,000 while the air sparging would cost $200,000. The recommended remedial system consisted of eight air sparging wells and four vapor recovery laterals. The Wisconsin Department of Natural Resources (WDNR) approved the remedial action plan in March, 1993. After 11 months of effective operation the concentrations of removed VOCs had decreased by 94 percent and groundwater sampling indicated no detectable concentrations of gasoline contaminants. Groundwater modeling was an effective technique to determine the economic feasibility of a groundwater remedial alternative.

  5. 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

  6. CHull: a generic convex-hull-based model selection method.

    PubMed

    Wilderjans, Tom F; Ceulemans, Eva; Meers, Kristof

    2013-03-01

    When analyzing data, researchers are often confronted with a model selection problem (e.g., determining the number of components/factors in principal components analysis [PCA]/factor analysis or identifying the most important predictors in a regression analysis). To tackle such a problem, researchers may apply some objective procedure, like parallel analysis in PCA/factor analysis or stepwise selection methods in regression analysis. A drawback of these procedures is that they can only be applied to the model selection problem at hand. An interesting alternative is the CHull model selection procedure, which was originally developed for multiway analysis (e.g., multimode partitioning). However, the key idea behind the CHull procedure--identifying a model that optimally balances model goodness of fit/misfit and model complexity--is quite generic. Therefore, the procedure may also be used when applying many other analysis techniques. The aim of this article is twofold. First, we demonstrate the wide applicability of the CHull method by showing how it can be used to solve various model selection problems in the context of PCA, reduced K-means, best-subset regression, and partial least squares regression. Moreover, a comparison of CHull with standard model selection methods for these problems is performed. Second, we present the CHULL software, which may be downloaded from http://ppw.kuleuven.be/okp/software/CHULL/, to assist the user in applying the CHull procedure.

  7. Model Selection and Accounting for Model Uncertainty in Graphical Models Using OCCAM’s Window

    DTIC Science & Technology

    1991-07-22

    There are also approaches based on information criteria and discrepancy measures (Gokhale and Kullback, 1978; Sakamoto, 1984; Linhart and Zucchini , 1986...Statistical Society (Series B), 50,157-224. Linhart, H. and Zucchini , W. (1986) Model Selection. New York: Wiley. Miller, A.J. (1984) Selection of

  8. A mixed model reduction method for preserving selected physical information

    NASA Astrophysics Data System (ADS)

    Zhang, Jing; Zheng, Gangtie

    2017-03-01

    A new model reduction method in the frequency domain is presented. By mixedly using the model reduction techniques from both the time domain and the frequency domain, the dynamic model is condensed to selected physical coordinates, and the contribution of slave degrees of freedom is taken as a modification to the model in the form of effective modal mass of virtually constrained modes. The reduced model can preserve the physical information related to the selected physical coordinates such as physical parameters and physical space positions of corresponding structure components. For the cases of non-classical damping, the method is extended to the model reduction in the state space but still only contains the selected physical coordinates. Numerical results are presented to validate the method and show the effectiveness of the model reduction.

  9. Model selection in cognitive science as an inverse problem

    NASA Astrophysics Data System (ADS)

    Myung, Jay I.; Pitt, Mark A.; Navarro, Daniel J.

    2005-03-01

    How should we decide among competing explanations (models) of a cognitive phenomenon? This problem of model selection is at the heart of the scientific enterprise. Ideally, we would like to identify the model that actually generated the data at hand. However, this is an un-achievable goal as it is fundamentally ill-posed. Information in a finite data sample is seldom sufficient to point to a single model. Multiple models may provide equally good descriptions of the data, a problem that is exacerbated by the presence of random error in the data. In fact, model selection bears a striking similarity to perception, in that both require solving an inverse problem. Just as perceptual ambiguity can be addressed only by introducing external constraints on the interpretation of visual images, the ill-posedness of the model selection problem requires us to introduce external constraints on the choice of the most appropriate model. Model selection methods differ in how these external constraints are conceptualized and formalized. In this review we discuss the development of the various approaches, the differences between them, and why the methods perform as they do. An application example of selection methods in cognitive modeling is also discussed.

  10. In vivo protein quality of selected cereal-based staple foods enriched with soybean proteins

    PubMed Central

    Acevedo-Pacheco, Laura; Serna-Saldívar, Sergio O.

    2016-01-01

    Background One way to diminish protein malnutrition in children is by enriching cereal-based flours for the manufacturing of maize tortillas, wheat flour tortillas, and yeast-leavened breads, which are widely consumed among low socio-economic groups. Objective The aim was to determine and compare the essential amino acid (EAA) scores, protein digestibility corrected amino acid scores (PDCAAS), and in vivo protein quality (protein digestibility, protein efficiency ratio (PER), biological values (BV), and net protein utilization (NPU) values) of regular versus soybean-fortified maize tortillas, yeast-leavened bread, and wheat flour tortillas. Design To comparatively assess differences in protein quality among maize tortillas, wheat flour tortillas, and yeast-leavened breads, EAA compositions and in vivo studies with weanling rats were performed. The experimental diets based on regular or soybean-fortified food products were compared with a casein-based diet. Food intake, weight gains, PER, dry matter and protein digestibility, BV, NPU, and PDCAAS were assessed. The soybean-fortified tortillas contained 6% of defatted soybean flour, whereas the yeast-leavened bread flour contained 4.5% of soybean concentrate. Results The soybean-fortified tortillas and bread contained higher amounts of lysine and tryptophan, which improved their EAA scores and PDCAAS. Rats fed diets based on soybean-fortified maize or wheat tortillas gained considerably more weight and had better BV and NPU values compared with counterparts fed with respective regular products. As a result, fortified maize tortillas and wheat flour tortillas improved PER from 0.73 to 1.64 and 0.69 to 1.77, respectively. The PER improvement was not as evident in rats fed the enriched yeast-leavened bread because the formulation contained sugar that decreased lysine availability possibly to Maillard reactions. Conclusions The proposed enrichment of cereal-based foods with soybean proteins greatly improved PDCAAS, animal

  11. Joint Bayesian variable and graph selection for regression models with network-structured predictors.

    PubMed

    Peterson, Christine B; Stingo, Francesco C; Vannucci, Marina

    2016-03-30

    In this work, we develop a Bayesian approach to perform selection of predictors that are linked within a network. We achieve this by combining a sparse regression model relating the predictors to a response variable with a graphical model describing conditional dependencies among the predictors. The proposed method is well-suited for genomic applications because it allows the identification of pathways of functionally related genes or proteins that impact an outcome of interest. In contrast to previous approaches for network-guided variable selection, we infer the network among predictors using a Gaussian graphical model and do not assume that network information is available a priori. We demonstrate that our method outperforms existing methods in identifying network-structured predictors in simulation settings and illustrate our proposed model with an application to inference of proteins relevant to glioblastoma survival.

  12. 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

  13. 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

    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.

  14. Selection and characterization of Her2 binding-designed ankyrin repeat proteins.

    PubMed

    Zahnd, Christian; Pecorari, Frédéric; Straumann, Nadine; Wyler, Emanuel; Plückthun, Andreas

    2006-11-17

    Designed ankyrin repeat proteins (DARPins) are a novel class of binding proteins that bind their target protein with high affinity and specificity and have very favorable expression and stability properties. We describe here the in vitro selection of DARPins against human epidermal growth factor receptor 2 (Her2), an important target for cancer therapy and diagnosis. Several DARPins bind to the same epitope as trastuzumab (Herceptin), but none were selected that bind to the epitope of pertuzumab (Omnitarg). Some of the selected DARPins bind with low nanomolar affinity (Kd=7.3 nm) to the target. Further analysis revealed that all DARPins are highly specific and do not cross-react with epidermal growth factor receptor I (EGFR1) or any other investigated protein. The selected DARPins specifically bind to strongly Her2-overexpressing cell lines such as SKBR-3 but also recognize small amounts of Her2 on weakly expressing cell lines such as MCF-7. Furthermore, the DARPins also lead to a highly specific and strong staining of plasma membranes of paraffinated sections of human mamma-carcinoma tissue. Thus, the selected DARPins might be used for the development of diagnostic tests for the status of Her2 overexpression in different adenocarcinomas, and they may be further evaluated for their potential in targeted therapy since their favorable expression properties make the construction of fusion proteins very convenient.

  15. Evidence of positive selection at codon sites localized in extracellular domains of mammalian CC motif chemokine receptor proteins

    PubMed Central

    2010-01-01

    Background CC chemokine receptor proteins (CCR1 through CCR10) are seven-transmembrane G-protein coupled receptors whose signaling pathways are known for their important roles coordinating immune system responses through targeted trafficking of white blood cells. In addition, some of these receptors have been identified as fusion proteins for viral pathogens: for example, HIV-1 strains utilize CCR5, CCR2 and CCR3 proteins to obtain cellular entry in humans. The extracellular domains of these receptor proteins are involved in ligand-binding specificity as well as pathogen recognition interactions. In mammals, the majority of chemokine receptor genes are clustered together; in humans, seven of the ten genes are clustered in the 3p21-24 chromosome region. Gene conversion events, or exchange of DNA sequence between genes, have been reported in chemokine receptor paralogs in various mammalian lineages, especially between the cytogenetically closely located pairs CCR2/5 and CCR1/3. Datasets of mammalian orthologs for each gene were analyzed separately to minimize the potential confounding impact of analyzing highly similar sequences resulting from gene conversion events. Molecular evolution approaches and the software package Phylogenetic Analyses by Maximum Likelihood (PAML) were utilized to investigate the signature of selection that has acted on the mammalian CC chemokine receptor (CCR) gene family. The results of neutral vs. adaptive evolution (positive selection) hypothesis testing using Site Models are reported. In general, positive selection is defined by a ratio of nonsynonymous/synonymous nucleotide changes (dN/dS, or ω) >1. Results Of the ten mammalian CC motif chemokine receptor sequence datasets analyzed, only CCR2 and CCR3 contain amino acid codon sites that exhibit evidence of positive selection using site based hypothesis testing in PAML. Nineteen of the twenty codon sites putatively indentified as likely to be under positive selection code for amino acid

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

    PubMed

    Buksa, Krzysztof

    2016-09-05

    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.

  17. Selective precipitation and purification of monovalent proteins using oligovalent ligands and ammonium sulfate.

    PubMed

    Mirica, Katherine A; Lockett, Matthew R; Snyder, Phillip W; Shapiro, Nathan D; Mack, Eric T; Nam, Sarah; Whitesides, George M

    2012-02-15

    This paper describes a method for the selective precipitation and purification of a monovalent protein (carbonic anhydrase is used as a demonstration) from cellular lysate using ammonium sulfate and oligovalent ligands. The oligovalent ligands induce the formation of protein-ligand aggregates, and at an appropriate concentration of dissolved ammonium sulfate, these complexes precipitate. The purification involves three steps: (i) the removal of high-molecular-weight impurities through the addition of ammonium sulfate to the crude cell lysate; (ii) the introduction of an oligovalent ligand and the selective precipitation of the target protein-ligand aggregates from solution; and (iii) the removal of the oligovalent ligand from the precipitate by dialysis to release the target protein. The increase of mass and volume of the proteins upon aggregate formation reduces their solubility, and results in the selective precipitation of these aggregates. We recovered human carbonic anhydrase, from crude cellular lysate, in 82% yield and 95% purity with a trivalent benzene sulfonamide ligand. This method provides a chromatography-free strategy of purifying monovalent proteins--for which appropriate oligovalent ligands can be synthesized--and combines the selectivity of affinity-based purification with the convenience of salt-induced precipitation.

  18. Optimal sequence selection in proteins of known structure by simulated evolution.

    PubMed Central

    Hellinga, H W; Richards, F M

    1994-01-01

    Rational design of protein structure requires the identification of optimal sequences to carry out a particular function within a given backbone structure. A general solution to this problem requires that a potential function describing the energy of the system as a function of its atomic coordinates be minimized simultaneously over all available sequences and their three-dimensional atomic configurations. Here we present a method that explicitly minimizes a semiempirical potential function simultaneously in these two spaces, using a simulated annealing approach. The method takes the fixed three-dimensional coordinates of a protein backbone and stochastically generates possible sequences through the introduction of random mutations. The corresponding three-dimensional coordinates are constructed for each sequence by "redecorating" the backbone coordinates of the original structure with the corresponding side chains. These are then allowed to vary in their structure by random rotations around free torsional angles to generate a stochastic walk in configurational space. We have named this method protein simulated evolution, because, in loose analogy with natural selection, it randomly selects for allowed solutions in the sequence of a protein subject to the "selective pressure" of a potential function. Energies predicted by this method for sequences of a small group of residues in the hydrophobic core of the phage lambda cI repressor correlate well with experimentally determined biological activities. This "genetic selection by computer" approach has potential applications in protein engineering, rational protein design, and structure-based drug discovery. PMID:8016069

  19. 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)

  20. 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…

  1. 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…

  2. 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…

  3. Minimalist models for proteins: a comparative analysis.

    PubMed

    Tozzini, Valentina

    2010-08-01

    The last decade has witnessed a renewed interest in the coarse-grained (CG) models for biopolymers, also stimulated by the needs of modern molecular biology, dealing with nano- to micro-sized bio-molecular systems and larger than microsecond timescale. This combination of size and timescale is, in fact, hard to access by atomic-based simulations. Coarse graining the system is a route to be followed to overcome these limits, but the ways of practically implementing it are many and different, making the landscape of CG models very vast and complex. In this paper, the CG models are reviewed and their features, applications and performances compared. This analysis, restricted to proteins, focuses on the minimalist models, namely those reducing at minimum the number of degrees of freedom without losing the possibility of explicitly describing the secondary structures. This class includes models using a single or a few interacting centers (beads) for each amino acid. From this analysis several issues emerge. The difficulty in building these models resides in the need for combining transferability/predictive power with the capability of accurately reproducing the structures. It is shown that these aspects could be optimized by accurately choosing the force field (FF) terms and functional forms, and combining different parameterization procedures. In addition, in spite of the variety of the minimalist models, regularities can be found in the parameters values and in FF terms. These are outlined and schematically presented with the aid of a generic phase diagram of the polypeptide in the parameter space and, hopefully, could serve as guidelines for the development of minimalist models incorporating the maximum possible level of predictive power and structural accuracy.

  4. Cholinergic dysregulation produced by selective inactivation of the dystonia-associated protein torsinA.

    PubMed

    Sciamanna, Giuseppe; Hollis, Robert; Ball, Chelsea; Martella, Giuseppina; Tassone, Annalisa; Marshall, Andrea; Parsons, Dee; Li, Xinru; Yokoi, Fumiaki; Zhang, Lin; Li, Yuqing; Pisani, Antonio; Standaert, David G

    2012-09-01

    DYT1 dystonia, a common and severe primary dystonia, is caused by a 3-bp deletion in TOR1A which encodes torsinA, a protein found in the endoplasmic reticulum. Several cellular functions are altered by the mutant protein, but at a systems level the link between these and the symptoms of the disease is unclear. The most effective known therapy for DYT1 dystonia is the use of anticholinergic drugs. Previous studies have revealed that in mice, transgenic expression of human mutant torsinA under a non-selective promoter leads to abnormal function of striatal cholinergic neurons. To investigate what pathological role torsinA plays in cholinergic neurons, we created a mouse model in which the Dyt1 gene, the mouse homolog of TOR1A, is selectively deleted in cholinergic neurons (ChKO animals). These animals do not have overt dystonia, but do have subtle motor abnormalities. There is no change in the number or size of striatal cholinergic cells or striatal acetylcholine content, uptake, synthesis, or release in ChKO mice. There are, however, striking functional abnormalities of striatal cholinergic cells, with paradoxical excitation in response to D2 receptor activation and loss of muscarinic M2/M4 receptor inhibitory function. These effects are specific for cholinergic interneurons, as recordings from nigral dopaminergic neurons revealed normal responses. Amphetamine stimulated dopamine release was also unaltered. These results demonstrate a cell-autonomous effect of Dyt1 deletion on striatal cholinergic function. Therapies directed at modifying the function of cholinergic neurons may prove useful in the treatment of the human disorder.

  5. 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

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

    PubMed

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

    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.

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

    PubMed Central

    Beck, Emily A.; Llopart, Ana

    2015-01-01

    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. PMID:26603658

  8. 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.

  9. mRNA and DNA selection via protein multimerization: YB-1 as a case study

    PubMed Central

    Kretov, Dmitry A.; Curmi, Patrick A.; Hamon, Loic; Abrakhi, Sanae; Desforges, Bénédicte; Ovchinnikov, Lev P.; Pastré, David

    2015-01-01

    Translation is tightly regulated in cells for keeping adequate protein levels, this task being notably accomplished by dedicated mRNA-binding proteins recognizing a specific set of mRNAs to repress or facilitate their translation. To select specific mRNAs, mRNA-binding proteins can strongly bind to specific mRNA sequences/structures. However, many mRNA-binding proteins rather display a weak specificity to short and redundant sequences. Here we examined an alternative mechanism by which mRNA-binding proteins could inhibit the translation of specific mRNAs, using YB-1, a major translation regulator, as a case study. Based on a cooperative binding, YB-1 forms stable homo-multimers on some mRNAs while avoiding other mRNAs. Via such inhomogeneous distribution, YB-1 can selectively inhibit translation of mRNAs on which it has formed stable multimers. This novel mechanistic view on mRNA selection may be shared by other proteins considering the elevated occurrence of multimerization among mRNA-binding proteins. Interestingly, we also demonstrate how, by using the same mechanism, YB-1 can form multimers on specific DNA structures, which could provide novel insights into YB-1 nuclear functions in DNA repair and multi-drug resistance. PMID:26271991

  10. 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.

  11. 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.

  12. 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.

  13. Amino acid-selective isotope labeling of proteins for nuclear magnetic resonance study: proteins secreted by Brevibacillus choshinensis.

    PubMed

    Tanio, Michikazu; Tanaka, Rikou; Tanaka, Takeshi; Kohno, Toshiyuki

    2009-03-15

    Here we report the first application of amino acid-type selective (AATS) isotope labeling of a recombinant protein secreted by Brevibacillus choshinensis for a nuclear magnetic resonance (NMR) study. To prepare the 15N-AATS-labeled protein, the transformed B. choshinensis was cultured in 15N-labeled amino acid-containing C.H.L. medium, which is commonly used in the Escherichia coli expression system. The analyses of the 1H-15N heteronuclear single quantum coherence (HSQC) spectra of the secreted proteins with a 15N-labeled amino acid demonstrated that alanine, arginine, asparagine, cysteine, glutamine, histidine, lysine, methionine, and valine are suitable for selective labeling, although acidic and aromatic amino acids are not suitable. The 15N labeling for glycine, isoleucine, leucine, serine, and threonine resulted in scrambling to specific amino acids. These results indicate that the B. choshinensis expression system is an alternative tool for AATS labeling of recombinant proteins, especially secretory proteins, for NMR analyses.

  14. Major membrane surface proteins of Mycoplasma hyopneumoniae selectively modified by covalently bound lipid

    SciTech Connect

    Wise K.S.; Kim, M.F.

    1987-12-01

    Surface protein antigens of Mycoplasma hyopneumoniae were identified by direct antibody-surface binding or by radioimmunoprecipitation of surface /sup 125/I-labeled proteins with a series of monoclonal antibodies (MAbs). Radioimmunoprecipitation of TX-114-phase proteins from cells labeled with (/sup 35/S) methionine, /sup 14/C-amino acids, or (/sup 3/H) palmitic acid showed that proteins p65, p50, and p44 were abundant and (with one other hydrophobic protein, p60) were selectively labeled with lipid. Alkaline hydroxylamine treatment of labeled proteins indicated linkage of lipids by amide or stable O-linked ester bonds. Proteins p65, p50, and p44 were highly immunogenic in the natural host as measured by immunoblots of TX-114-phase proteins with antisera from swine inoculated with whole organisms. These proteins were antigenically and structurally unrelated, since hyperimmune mouse antibodies to individual gel-purified proteins were monospecific and gave distinct proteolytic epitope maps. Intraspecies size variants of one surface antigen of M. hyopneumoniae were revealed by a MAb to p70 (defined in strain J, ATCC 25934), which recognized a large p73 component on strain VPP11 (ATCC 25617). In addition, MAb to internal, aqueous-phase protein p82 of strain J failed to bind an analogous antigen in strain VPP11.

  15. Construction and genetic selection of small transmembrane proteins that activate the human erythropoietin receptor.

    PubMed

    Cammett, Tobin J; Jun, Susan J; Cohen, Emily B; Barrera, Francisco N; Engelman, Donald M; Dimaio, Daniel

    2010-02-23

    This work describes a genetic approach to isolate small, artificial transmembrane (TM) proteins with biological activity. The bovine papillomavirus E5 protein is a dimeric, 44-amino acid TM protein that transforms cells by specifically binding and activating the platelet-derived growth factor beta receptor (PDGFbetaR). We used the E5 protein as a scaffold to construct a retrovirus library expressing approximately 500,000 unique 44-amino acid proteins with randomized TM domains. We screened this library to select small, dimeric TM proteins that were structurally unrelated to erythropoietin (EPO), but specifically activated the human EPO receptor (hEPOR). These proteins did not activate the murine EPOR or the PDGFbetaR. Genetic studies with one of these activators suggested that it interacted with the TM domain of the hEPOR. Furthermore, this TM activator supported erythroid differentiation of primary human hematopoietic progenitor cells in vitro in the absence of EPO. Thus, we have changed the specificity of a protein so that it no longer recognizes its natural target but, instead, modulates an entirely different protein. This represents a novel strategy to isolate small artificial proteins that affect diverse membrane proteins. We suggest the word "traptamer" for these transmembrane aptamers.

  16. Models to predict intestinal absorption of therapeutic peptides and proteins.

    PubMed

    Antunes, Filipa; Andrade, Fernanda; Ferreira, Domingos; Nielsen, Hanne Morck; Sarmento, Bruno

    2013-01-01

    Prediction of human intestinal absorption is a major goal in the design, optimization, and selection of drugs intended for oral delivery, in particular proteins, which possess intrinsic poor transport across intestinal epithelium. There are various techniques currently employed to evaluate the extension of protein absorption in the different phases of drug discovery and development. Screening protocols to evaluate protein absorption include a range of preclinical methodologies like in silico, in vitro, in situ, ex vivo and in vivo. It is the careful and critical use of these techniques that can help to identify drug candidates, which most probably will be well absorbed from the human intestinal tract. It is well recognized that the human intestinal permeability cannot be accurately predicted based on a single preclinical method. However, the present social and scientific concerns about the animal well care as well as the pharmaceutical industries need for rapid, cheap and reliable models predicting bioavailability give reasons for using methods providing an appropriate correlation between results of in vivo and in vitro drug absorption. The aim of this review is to describe and compare in silico, in vitro, in situ, ex vivo and in vivo methods used to predict human intestinal absorption, giving a special attention to the intestinal absorption of therapeutic peptides and proteins.

  17. RUC at TREC 2014: Select Resources Using Topic Models

    DTIC Science & Technology

    2014-11-01

    them being observed (i.e. sampled). To infer the topic Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the...Selection. In CIKM 2009, pages 1277-1286. [10] M. Baillie, M. Carmen, and F. Crestani. A Multiple- Collection Latent Topic Model for Federated...RUC at TREC 2014: Select Resources Using Topic Models Qiuyue Wang, Shaochen Shi, Wei Cao School of Information Renmin University of China Beijing

  18. Rapid and selective separation for mixed proteins with thiol functionalized magnetic nanoparticles

    NASA Astrophysics Data System (ADS)

    Lee, Soo Youn; Ahn, Chi Young; Lee, Jiho; Lee, Jin Hyung; Chang, Jeong Ho

    2012-05-01

    Thiol group functionalized silica-coated magnetic nanoparticles (Si-MNPs@SH) were synthesized for rapid and selective magnetic field-based separation of mixed proteins. The highest adsorption efficiencies of binary proteins, bovine serum albumin (BSA; 66 kDa; p I = 4.65) and lysozyme (LYZ; 14.3 kDa; p I = 11) were shown at the pH values corresponding to their own p I in the single-component protein. In the mixed protein, however, the adsorption performance of BSA and LYZ by Si-MNPs@SH was governed not only by pH but also by the molecular weight of each protein in the mixed protein.

  19. 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.

  20. 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

  1. In vitro selection and evolution of functional proteins by using ribosome display

    PubMed Central

    Hanes, Jozef; Plückthun, Andreas

    1997-01-01

    We report here a system with which a correctly folded complete protein and its encoding mRNA both remain attached to the ribosome and can be enriched for the ligand-binding properties of the native protein. We have selected a single-chain fragment (scFv) of an antibody 108-fold by five cycles of transcription, translation, antigen-affinity selection, and PCR. The selected scFv fragments all mutated in vitro by acquiring up to four unrelated amino acid exchanges over the five generations, but they remained fully compatible with antigen binding. Libraries of native folded proteins can now be screened and made to evolve in a cell-free system without any transformation or constraints imposed by the host cell. PMID:9144168

  2. Role of solar neutrinos in selecting left handed proteins on the earth

    NASA Astrophysics Data System (ADS)

    Ramadurai, Souriraja

    It is shown that neutrinos from the Sun preferentially destroy one orientation of 14N. Though the rate is extremely small, it is shown that over a period of one billion years, the amount of 14N surviving the detruction is shown to be significant. The formation of proteins on the earth is guided by this orientation of 14N leading to the chiral selection. It is shown that only left handed proteins can be formed with this oriented 14N. The details of the orientation selection mechanism are gien in full to initiste a small [10**(-14)] predominance of the left handed proteins. Subsequent chemical evolotion on the earth leads to the complete chiral selection.

  3. Positive and strongly relaxed purifying selection drive the evolution of repeats in proteins

    PubMed Central

    Persi, Erez; Wolf, Yuri I.; Koonin, Eugene V

    2016-01-01

    Protein repeats are considered hotspots of protein evolution, associated with acquisition of new functions and novel phenotypic traits, including disease. Paradoxically, however, repeats are often strongly conserved through long spans of evolution. To resolve this conundrum, it is necessary to directly compare paralogous (horizontal) evolution of repeats within proteins with their orthologous (vertical) evolution through speciation. Here we develop a rigorous methodology to identify highly periodic repeats with significant sequence similarity, for which evolutionary rates and selection (dN/dS) can be estimated, and systematically characterize their evolution. We show that horizontal evolution of repeats is markedly accelerated compared with their divergence from orthologues in closely related species. This observation is universal across the diversity of life forms and implies a biphasic evolutionary regime whereby new copies experience rapid functional divergence under combined effects of strongly relaxed purifying selection and positive selection, followed by fixation and conservation of each individual repeat. PMID:27857066

  4. 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

  5. Mining protein kinases regulation using graphical models.

    PubMed

    Chen, Qingfeng; Chen, Yi-Ping Phoebe

    2011-03-01

    Abnormal kinase activity is a frequent cause of diseases, which makes kinases a promising pharmacological target. Thus, it is critical to identify the characteristics of protein kinases regulation by studying the activation and inhibition of kinase subunits in response to varied stimuli. Bayesian network (BN) is a formalism for probabilistic reasoning that has been widely used for learning dependency models. However, for high-dimensional discrete random vectors the set of plausible models becomes large and a full comparison of all the posterior probabilities related to the competing models becomes infeasible. A solution to this problem is based on the Markov Chain Monte Carlo (MCMC) method. This paper proposes a BN-based framework to discover the dependency correlations of kinase regulation. Our approach is to apply the MCMC method to generate a sequence of samples from a probability distribution, by which to approximate the distribution. The frequent connections (edges) are identified from the obtained sampling graphical models. Our results point to a number of novel candidate regulation patterns that are interesting in biology and include inferred associations that were unknown.

  6. 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.

  7. Models of selection, isolation, and gene flow in speciation.

    PubMed

    Hart, Michael W

    2014-10-01

    Many marine ecologists aspire to use genetic data to understand how selection and demographic history shape the evolution of diverging populations as they become reproductively isolated species. I propose combining two types of genetic analysis focused on this key early stage of the speciation process to identify the selective agents directly responsible for population divergence. Isolation-with-migration (IM) models can be used to characterize reproductive isolation between populations (low gene flow), while codon models can be used to characterize selection for population differences at the molecular level (especially positive selection for high rates of amino acid substitution). Accessible transcriptome sequencing methods can generate the large quantities of data needed for both types of analysis. I highlight recent examples (including our work on fertilization genes in sea stars) in which this confluence of interest, models, and data has led to taxonomically broad advances in understanding marine speciation at the molecular level. I also highlight new models that incorporate both demography and selection: simulations based on these theoretical advances suggest that polymorphisms shared among individuals (a key source of information in IM models) may lead to false-positive evidence of selection (in codon models), especially during the early stages of population divergence and speciation that are most in need of study. The false-positive problem may be resolved through a combination of model improvements plus experiments that document the phenotypic and fitness effects of specific polymorphisms for which codon models and IM models indicate selection and reproductive isolation (such as genes that mediate sperm-egg compatibility at fertilization).

  8. Modeling of display color parameters and algorithmic color selection

    NASA Astrophysics Data System (ADS)

    Silverstein, Louis D.; Lepkowski, James S.; Carter, Robert C.; Carter, Ellen C.

    1986-01-01

    An algorithmic approach to color selection, which is based on psychophysical models of color processing, is described. The factors that affect color differentiation, such as wavelength separation, color stimulus size, and brightness adaptation level, are discussed. The use of the CIE system of colorimetry and the CIELUV color difference metric for display color modeling is examined. The computer program combines the selection algorithm with internally derived correction factors for color image field size, ambient lighting characteristics, and anomalous red-green color vision deficiencies of display operators. The performance of the program is evaluated and uniform chromaticity scale diagrams for six-color and seven-color selection problems are provided.

  9. Fisher-Wright model with deterministic seed bank and selection.

    PubMed

    Koopmann, Bendix; Müller, Johannes; Tellier, Aurélien; Živković, Daniel

    2017-04-01

    Seed banks are common characteristics to many plant species, which allow storage of genetic diversity in the soil as dormant seeds for various periods of time. We investigate an above-ground population following a Fisher-Wright model with selection coupled with a deterministic seed bank assuming the length of the seed bank is kept constant and the number of seeds is large. To assess the combined impact of seed banks and selection on genetic diversity, we derive a general diffusion model. The applied techniques outline a path of approximating a stochastic delay differential equation by an appropriately rescaled stochastic differential equation. We compute the equilibrium solution of the site-frequency spectrum and derive the times to fixation of an allele with and without selection. Finally, it is demonstrated that seed banks enhance the effect of selection onto the site-frequency spectrum while slowing down the time until the mutation-selection equilibrium is reached.

  10. Prediction of subcellular location apoptosis proteins with ensemble classifier and feature selection.

    PubMed

    Gu, Quan; Ding, Yong-Sheng; Jiang, Xiao-Ying; Zhang, Tong-Liang

    2010-04-01

    Apoptosis proteins have a central role in the development and the homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. The function of an apoptosis protein is closely related to its subcellular location. It is crucial to develop powerful tools to predict apoptosis protein locations for rapidly increasing gap between the number of known structural proteins and the number of known sequences in protein databank. In this study, amino acids pair compositions with different spaces are used to construct feature sets for representing sample of protein feature selection approach based on binary particle swarm optimization, which is applied to extract effective feature. Ensemble classifier is used as prediction engine, of which the basic classifier is the fuzzy K-nearest neighbor. Each basic classifier is trained with different feature sets. Two datasets often used in prior works are selected to validate the performance of proposed approach. The results obtained by jackknife test are quite encouraging, indicating that the proposed method might become a potentially useful tool for subcellular location of apoptosis protein, or at least can play a complimentary role to the existing methods in the relevant areas. The supplement information and software written in Matlab are available by contacting the corresponding author.

  11. 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

  12. 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.

  13. Simple micromechanical model of protein crystals for their mechanical characterizations

    NASA Astrophysics Data System (ADS)

    Yoon, G.; Eom, K.; Na, S.

    2010-06-01

    Proteins have been known to perform the excellent mechanical functions and exhibit the remarkable mechanical properties such as high fracture toughness in spider silk protein [1]. This indicates that the mechanical characterization of protein molecules and/or crystals is very essential to understand such remarkable mechanical function of protein molecules. In this study, for gaining insight into mechanical behavior of protein crystals, we developed the micromechanical model by using the empirical potential field prescribed to alpha carbon atoms of a protein crystal in a unit cell. We consider the simple protein crystals for their mechanical behavior under tensile loading to be compared with full atomic models

  14. DNA-SMART: Biopatterned Polymer Film Microchannels for Selective Immobilization of Proteins and Cells.

    PubMed

    Schneider, Ann-Kathrin; Nikolov, Pavel M; Giselbrecht, Stefan; Niemeyer, Christof M

    2017-02-22

    A novel SMART module, dubbed "DNA-SMART" (DNA substrate modification and replication by thermoforming) is reported, where polymer films are premodified with single-stranded DNA capture strands, microthermoformed into 3D structures, and postmodified with complementary DNA-protein conjugates to realize complex biologically active surfaces within microfluidic devices. As a proof of feasibility, it is demonstrated that microchannels presenting three different proteins on their inner curvilinear surface can be used for selective capture of cells under flow conditions.

  15. Selective Precipitation and Purification of Monovalent Proteins Using Oligovalent Ligands and Ammonium Sulfate

    PubMed Central

    Mirica, Katherine A.; Lockett, Matthew R.; Snyder, Phillip W.; Shapiro, Nathan D.; Mack, Eric T.; Nam, Sarah; Whitesides, George M.

    2012-01-01

    This paper describes a method for the selective precipitation and purification of a monovalent protein (carbonic anhydrase is used as a demonstration) from cellular lysate using ammonium sulfate and oligovalent ligands. The oligovalent ligands induce the formation of protein-ligand aggregates, and at an appropriate concentration of dissolved ammonium sulfate, these complexes precipitate. The purification involves three steps: i) the removal of high-molecular weight impurities through the addition of ammonium sulfate to the crude cell lysate; ii) the introduction of an oligovalent ligand and the selective precipitation of the target protein-ligand aggregates from solution; and iii) the removal of the oligovalent ligand from the precipitate by dialysis to release the target protein. The increase of mass and volume of the proteins upon aggregate formation reduces their solubility, and results in the selective precipitation of these aggregates. We recovered human carbonic anhydrase, from crude cellular lysate, in 82% yield and 95% purity with a trivalent benzene sulfonamide ligand. This method provides a chromatography-free strategy of purifying monovalent proteins—for which appropriate oligovalent ligands can be synthesized—and combines the selectivity of affinity-based purification with the convenience of salt-induced precipitation. PMID:22188202

  16. Magnetic materials for the selective analysis of peptide and protein biomarkers.

    PubMed

    Capriotti, Anna Laura; Piovesana, Susy

    2016-08-05

    This mini-review article provides an overview on the use of magnetic materials for the analysis of protein biomarkers. In particular, the advantage provided by magnetic solid phase extraction will be discussed with selected examples, considering untargeted analysis for screening new biomarker proteins and targeted investigation on known and suggested new biomarkers. Aspects, such as enrichment efficiency over conventional techniques, ease of use, functionalization versatility and automation will be considered, together with quantification and deeper structure elucidation provided by coupling selective or specific enrichment to powerful characterization techniques, such as mass spectrometry.

  17. Optimizing the selective recognition of protein isoforms through tuning of nanoparticle hydrophobicity

    NASA Astrophysics Data System (ADS)

    Chen, Kaimin; Rana, Subinoy; Moyano, Daniel F.; Xu, Yisheng; Guo, Xuhong; Rotello, Vincent M.

    2014-05-01

    We demonstrate that ligand hydrophobicity can be used to increase affinity and selectivity of binding between monolayer-protected cationic gold nanoparticles and β-lactoglobulin protein isoforms containing two amino acid mutations.We demonstrate that ligand hydrophobicity can be used to increase affinity and selectivity of binding between monolayer-protected cationic gold nanoparticles and β-lactoglobulin protein isoforms containing two amino acid mutations. Electronic supplementary information (ESI) available: Experimental details, ITC, and DLS analyses. See DOI: 10.1039/c4nr01085j

  18. In vitro selection and prediction of TIP47 protein-interaction interfaces.

    PubMed

    Burguete, Alondra Schweizer; Harbury, Pehr B; Pfeffer, Suzanne R

    2004-10-01

    We present a new method for the rapid identification of amino acid residues that contribute to protein-protein interfaces. Tail-interacting protein of 47 kDa (TIP47) binds Rab9 GTPase and the cytoplasmic domains of mannose 6-phosphate receptors and is required for their transport from endosomes to the Golgi apparatus. Cysteine mutations were incorporated randomly into TIP47 by expression in Escherichia coli cells harboring specific misincorporator tRNAs. We made use of the ability of the native TIP47 protein to protect 48 cysteine probes from chemical modification by iodoacetamide as a means to obtain a surface map of TIP47, revealing the identity of surface-localized, hydrophobic residues that are likely to participate in protein-protein interactions. Direct mutation of predicted interface residues confirmed that the protein had altered binding affinity for the mannose 6-phosphate receptor. TIP47 mutants with enhanced or diminished affinities were also selected by affinity chromatography. These methods were validated in comparison with the protein's crystal structure, and provide a powerful means to predict protein-protein interaction interfaces.

  19. 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.

  20. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    USGS Publications Warehouse

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romanach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in

  1. 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.

  2. Selection of DNA-encoded small molecule libraries against unmodified and non-immobilized protein targets.

    PubMed

    Zhao, Peng; Chen, Zitian; Li, Yizhou; Sun, Dawei; Gao, Yuan; Huang, Yanyi; Li, Xiaoyu

    2014-09-15

    The selection of DNA-encoded libraries against biological targets has become an important discovery method in chemical biology and drug discovery, but the requirement of modified and immobilized targets remains a significant disadvantage. With a terminal protection strategy and ligand-induced photo-crosslinking, we show that iterated selections of DNA-encoded libraries can be realized with unmodified and non-immobilized protein targets.

  3. Differential equation modeling of HIV viral fitness experiments: model identification, model selection, and multimodel inference.

    PubMed

    Miao, Hongyu; Dykes, Carrie; Demeter, Lisa M; Wu, Hulin

    2009-03-01

    Many biological processes and systems can be described by a set of differential equation (DE) models. However, literature in statistical inference for DE models is very sparse. We propose statistical estimation, model selection, and multimodel averaging methods for HIV viral fitness experiments in vitro that can be described by a set of nonlinear ordinary differential equations (ODE). The parameter identifiability of the ODE models is also addressed. We apply the proposed methods and techniques to experimental data of viral fitness for HIV-1 mutant 103N. We expect that the proposed modeling and inference approaches for the DE models can be widely used for a variety of biomedical studies.

  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. 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.

  6. 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

  7. Selective visualization of GLUT4 storage vesicles and associated Rab proteins using IRAP-pHluorin.

    PubMed

    Chen, Yu; Lippincott-Schwartz, Jennifer

    2015-01-01

    Fluorescence microscopy and fluorescent protein (FP)-tagged GLUT4 molecule have been great tools to characterize GLUT4 localization and dynamics inside the cell. However, it was difficult to distinguish GLUT4 storage vesicles (GSVs) from other intracellular compartments containing GLUT4 in live cells. Here, we describe the use of IRAP-pHluorin and total internal reflection fluorescence (TIRF) microscopy to selectively visualize GSVs and Rab proteins that associate with GSVs. This assay is also valuable to further defining GSV identity by unraveling other GSV-associated proteins.

  8. Site-Selective Disulfide Modification of Proteins: Expanding Diversity beyond the Proteome.

    PubMed

    Kuan, Seah Ling; Wang, Tao; Weil, Tanja

    2016-11-21

    The synthetic transformation of polypeptides with molecular accuracy holds great promise for providing functional and structural diversity beyond the proteome. Consequently, the last decade has seen an exponential growth of site-directed chemistry to install additional features into peptides and proteins even inside living cells. The disulfide rebridging strategy has emerged as a powerful tool for site-selective modifications since most proteins contain disulfide bonds. In this Review, we present the chemical design, advantages and limitations of the disulfide rebridging reagents, while summarizing their relevance for synthetic customization of functional protein bioconjugates, as well as the resultant impact and advancement for biomedical applications.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. Nephrocystins and MKS proteins interact with IFT particle and facilitate transport of selected ciliary cargos.

    PubMed

    Zhao, Chengtian; Malicki, Jarema

    2011-05-20

    Cilia are required for the development and function of many organs. Efficient transport of protein cargo along ciliary axoneme is necessary to sustain these processes. Despite its importance, the mode of interaction between the intraflagellar ciliary transport (IFT) mechanism and its cargo proteins remains poorly understood. Our studies demonstrate that IFT particle components, and a Meckel-Gruber syndrome 1 (MKS1)-related, B9 domain protein, B9d2, bind each other and contribute to the ciliary localization of Inversin (Nephrocystin 2). B9d2, Inversin, and Nephrocystin 5 support, in turn, the transport of a cargo protein, Opsin, but not another photoreceptor ciliary transmembrane protein, Peripherin. Interestingly, the components of this mechanism also contribute to the formation of planar cell polarity in mechanosensory epithelia. These studies reveal a molecular mechanism that mediates the transport of selected ciliary cargos and is of fundamental importance for the differentiation and survival of sensory cells.

  14. Selective Labeling of Proteins on Living Cell Membranes Using Fluorescent Nanodiamond Probes

    PubMed Central

    Sotoma, Shingo; Iimura, Jun; Igarashi, Ryuji; Hirosawa, Koichiro M.; Ohnishi, Hidenori; Mizukami, Shin; Kikuchi, Kazuya; Fujiwara, Takahiro K.; Shirakawa, Masahiro; Tochio, Hidehito

    2016-01-01

    The impeccable photostability of fluorescent nanodiamonds (FNDs) is an ideal property for use in fluorescence imaging of proteins in living cells. However, such an application requires highly specific labeling of the target proteins with FNDs. Furthermore, the surface of unmodified FNDs tends to adsorb biomolecules nonspecifically, which hinders the reliable targeting of proteins with FNDs. Here, we combined hyperbranched polyglycerol modification of FNDs with the β-lactamase-tag system to develop a strategy for selective imaging of the protein of interest in cells. The combination of these techniques enabled site-specific labeling of Interleukin-18 receptor alpha chain, a membrane receptor, with FNDs, which eventually enabled tracking of the diffusion trajectory of FND-labeled proteins on the membrane surface. PMID:28335184

  15. Electrostatics promotes molecular crowding and selects the aggregation pathway in fibril-forming protein solutions

    NASA Astrophysics Data System (ADS)

    Raccosta, S.; Blanco, M.; J. Roberts, C.; Martorana, V.; Manno, M.

    2016-05-01

    The role of intermolecular interaction in fibril-forming protein solutions and its relation with molecular conformation are crucial aspects for the control and inhibition of amyloid structures. Here, we study the fibril formation and the protein-protein interactions for two proteins at acidic p H, lysozyme and α -chymotrypsinogen. By using light scattering experiments and the Kirkwood-Buff integral approach, we show how concentration fluctuations are damped even at moderate protein concentrations by the dominant long-ranged electrostatic repulsion, which determines an effective crowded environment. In denaturing conditions, electrostatic repulsion keeps the monomeric solution in a thermodynamically metastable state, which is escaped through kinetically populated conformational sub-states. This explains how electrostatics acts as a gatekeeper in selecting a specific aggregation pathway.

  16. Novel web service selection model based on discrete group search.

    PubMed

    Zhai, Jie; Shao, Zhiqing; Guo, Yi; Zhang, Haiteng

    2014-01-01

    In our earlier work, we present a novel formal method for the semiautomatic verification of specifications and for describing web service composition components by using abstract concepts. After verification, the instantiations of components were selected to satisfy the complex service performance constraints. However, selecting an optimal instantiation, which comprises different candidate services for each generic service, from a large number of instantiations is difficult. Therefore, we present a new evolutionary approach on the basis of the discrete group search service (D-GSS) model. With regard to obtaining the optimal multiconstraint instantiation of the complex component, the D-GSS model has competitive performance compared with other service selection models in terms of accuracy, efficiency, and ability to solve high-dimensional service composition component problems. We propose the cost function and the discrete group search optimizer (D-GSO) algorithm and study the convergence of the D-GSS model through verification and test cases.

  17. 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

  18. Binding of Bacillus thuringiensis proteins to a laboratory-selected line of Heliothis virescens.

    PubMed Central

    MacIntosh, S C; Stone, T B; Jokerst, R S; Fuchs, R L

    1991-01-01

    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

  19. Template-based protein structure modeling using TASSER(VMT.).

    PubMed

    Zhou, Hongyi; Skolnick, Jeffrey

    2012-02-01

    Template-based protein structure modeling is commonly used for protein structure prediction. Based on the observation that multiple template-based methods often perform better than single template-based methods, we further explore the use of a variable number of multiple templates for a given target in the latest variant of TASSER, TASSER(VMT) . We first develop an algorithm that improves the target-template alignment for a given template. The improved alignment, called the SP(3) alternative alignment, is generated by a parametric alignment method coupled with short TASSER refinement on models selected using knowledge-based scores. The refined top model is then structurally aligned to the template to produce the SP(3) alternative alignment. Templates identified using SP(3) threading are combined with the SP(3) alternative and HHEARCH alignments to provide target alignments to each template. These template models are then grouped into sets containing a variable number of template/alignment combinations. For each set, we run short TASSER simulations to build full-length models. Then, the models from all sets of templates are pooled, and the top 20-50 models selected using FTCOM ranking method. These models are then subjected to a single longer TASSER refinement run for final prediction. We benchmarked our method by comparison with our previously developed approach, pro-sp(3) -TASSER, on a set with 874 easy and 318 hard targets. The average GDT-TS score improvements for the first model are 3.5 and 4.3% for easy and hard targets, respectively. When tested on the 112 CASP9 targets, our method improves the average GDT-TS scores as compared to pro-sp3-TASSER by 8.2 and 9.3% for the 80 easy and 32 hard targets, respectively. It also shows slightly better results than the top ranked CASP9 Zhang-Server, QUARK and HHpredA methods. The program is available for download at http://cssb.biology.gatech.edu/.

  20. Incorporating hidden Markov models for identifying protein kinase-specific phosphorylation sites.

    PubMed

    Huang, Hsien-Da; Lee, Tzong-Yi; Tzeng, Shih-Wei; Wu, Li-Cheng; Horng, Jorng-Tzong; Tsou, Ann-Ping; Huang, Kuan-Tsae

    2005-07-30

    Protein phosphorylation, which is an important mechanism in posttranslational modification, affects essential cellular processes such as metabolism, cell signaling, differentiation, and membrane transportation. Proteins are phosphorylated by a variety of protein kinases. In this investigation, we develop a novel tool to computationally predict catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the concepts of profile Hidden Markov Models (HMM), computational models are trained from the kinase-specific groups of phosphorylation sites. After evaluating the trained models, we select the model with highest accuracy in each kinase-specific group and provide a Web-based prediction tool for identifying protein phosphorylation sites. The main contribution here is that we have developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity.

  1. A protein engineered to bind uranyl selectively and with femtomolar affinity.

    PubMed

    Zhou, Lu; Bosscher, Mike; Zhang, Changsheng; Ozçubukçu, Salih; Zhang, Liang; Zhang, Wen; Li, Charles J; Liu, Jianzhao; Jensen, Mark P; Lai, Luhua; He, Chuan

    2014-03-01

    Uranyl (UO2(2+)), the predominant aerobic form of uranium, is present in the ocean at a concentration of ~3.2 parts per 10(9) (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.

  2. 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.

  3. Multiple selection filters ensure accurate tail-anchored membrane protein targeting

    PubMed Central

    Rao, Meera; Okreglak, Voytek; Chio, Un Seng; Cho, Hyunju; Walter, Peter; Shan, Shu-ou

    2016-01-01

    Accurate protein localization is crucial to generate and maintain organization in all cells. Achieving accuracy is challenging, as the molecular signals that dictate a protein’s cellular destination are often promiscuous. A salient example is the targeting of an essential class of tail-anchored (TA) proteins, whose sole defining feature is a transmembrane domain near their C-terminus. Here we show that the Guided Entry of Tail-anchored protein (GET) pathway selects TA proteins destined to the endoplasmic reticulum (ER) utilizing distinct molecular steps, including differential binding by the co-chaperone Sgt2 and kinetic proofreading after ATP hydrolysis by the targeting factor Get3. Further, the different steps select for distinct physicochemical features of the TA substrate. The use of multiple selection filters may be general to protein biogenesis pathways that must distinguish correct and incorrect substrates based on minor differences. DOI: http://dx.doi.org/10.7554/eLife.21301.001 PMID:27925580

  4. Detection of G1 proteins in Chinese hamster cells synchronized by isoleucine deprivation or mitotic selection.

    PubMed

    Ley, K D

    1975-07-01

    Examination of labeling patterns of proteins in Chinese hamster cells(line CHO) revealed the presence of a class of protein(s) that is synthesized during G1 phase of the cell cycle. Cells arrested in G1 by isoleucine (Ile) deprivation were prelabeded with [14-C]Ile, induced to traverse G1 by addition of unlabeled Ile, and labeled with [3-H]Ile at hourly intervals. Cells were fractionated into neclear and cytoplasmic portions, and proteins were separated by sodium dodecyl sulfate-polyacrylamide get electrophoresis. Gel profiles of proteins in the 45,000-160,000 mol wt range from the cytoplasm of cells in G1 were similar to those from cells arrested in G1 except for the presence of a mojor peak of [1-H]Ile incorporated into a protein(s) of approximately 80,000 mol wt. Peaks of net [3-H]Ile incorporation were not detected in neclear preparations. Cellular fractionation by differential centrifugation showed the peak I protein was located in the soluble supernatant fraction of the cytoplasm. Time-course studies showed that synthesis of this protein began 1-2 h after initiation of G1 traverse; the protein reached maximum levels in 4-6 h and was reduced to undetectable levels by 9 h. A cytoplasmic protein with similar electrophoretic mobility was found in G1 phase of cells synchronized by mitotic selection. This class of proteins is synthesized by cells before entry into S phase and may be involved in initiation of DNA synthesis.

  5. Evolution models with base substitutions, insertions, deletions, and selection

    NASA Astrophysics Data System (ADS)

    Saakian, D. B.

    2008-12-01

    The evolution model with parallel mutation-selection scheme is solved for the case when selection is accompanied by base substitutions, insertions, and deletions. The fitness is assumed to be either a single-peak function (i.e., having one finite discontinuity) or a smooth function of the Hamming distance from the reference sequence. The mean fitness is calculated exactly in large-genome limit. In the case of insertions and deletions the evolution characteristics depend on the choice of reference sequence.

  6. Genetic signatures of natural selection in a model invasive ascidian

    NASA Astrophysics Data System (ADS)

    Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

    2017-03-01

    Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

  7. Genetic signatures of natural selection in a model invasive ascidian

    PubMed Central

    Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

    2017-01-01

    Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta. PMID:28266616

  8. Stoichiometric and irreversible cysteine-selective protein modification using carbonylacrylic reagents

    PubMed Central

    Bernardim, Barbara; Cal, Pedro M.S.D.; Matos, Maria J.; Oliveira, Bruno L.; Martínez-Sáez, Nuria; Albuquerque, Inês S.; Perkins, Elizabeth; Corzana, Francisco; Burtoloso, Antonio C.B.; Jiménez-Osés, Gonzalo; Bernardes, Gonçalo J. L.

    2016-01-01

    Maleimides remain the reagents of choice for the preparation of therapeutic and imaging protein conjugates despite the known instability of the resulting products that undergo thiol-exchange reactions in vivo. Here we present the rational design of carbonylacrylic reagents for chemoselective cysteine bioconjugation. These reagents undergo rapid thiol Michael-addition under biocompatible conditions in stoichiometric amounts. When using carbonylacrylic reagents equipped with PEG or fluorophore moieties, this method enables access to protein and antibody conjugates precisely modified at pre-determined sites. Importantly, the conjugates formed are resistant to degradation in plasma and are biologically functional, as demonstrated by the selective imaging and detection of apoptotic and HER2+ cells, respectively. The straightforward preparation, stoichiometric use and exquisite cysteine selectivity of the carbonylacrylic reagents combined with the stability of the products and the availability of biologically relevant cysteine-tagged proteins make this method suitable for the routine preparation of chemically defined conjugates for in vivo applications. PMID:27782215

  9. Stoichiometric and irreversible cysteine-selective protein modification using carbonylacrylic reagents

    NASA Astrophysics Data System (ADS)

    Bernardim, Barbara; Cal, Pedro M. S. D.; Matos, Maria J.; Oliveira, Bruno L.; Martínez-Sáez, Nuria; Albuquerque, Inês S.; Perkins, Elizabeth; Corzana, Francisco; Burtoloso, Antonio C. B.; Jiménez-Osés, Gonzalo; Bernardes, Gonçalo J. L.

    2016-10-01

    Maleimides remain the reagents of choice for the preparation of therapeutic and imaging protein conjugates despite the known instability of the resulting products that undergo thiol-exchange reactions in vivo. Here we present the rational design of carbonylacrylic reagents for chemoselective cysteine bioconjugation. These reagents undergo rapid thiol Michael-addition under biocompatible conditions in stoichiometric amounts. When using carbonylacrylic reagents equipped with PEG or fluorophore moieties, this method enables access to protein and antibody conjugates precisely modified at pre-determined sites. Importantly, the conjugates formed are resistant to degradation in plasma and are biologically functional, as demonstrated by the selective imaging and detection of apoptotic and HER2+ cells, respectively. The straightforward preparation, stoichiometric use and exquisite cysteine selectivity of the carbonylacrylic reagents combined with the stability of the products and the availability of biologically relevant cysteine-tagged proteins make this method suitable for the routine preparation of chemically defined conjugates for in vivo applications.

  10. 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.

  11. Cognitive niches: an ecological model of strategy selection.

    PubMed

    Marewski, Julian N; Schooler, Lael J

    2011-07-01

    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 strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.

  12. Facile fabrication of hydrophilic nanofibrous membranes with an immobilized metal-chelate affinity complex for selective protein separation.

    PubMed

    Zhu, Jing; Sun, Gang

    2014-01-22

    In this study, we report a facile approach to fabricate functionalized poly(vinyl alcohol-co-ethylene) (PVA-co-PE) nanofibrous membranes as immobilized metal affinity membranes for selective protein separation. Hydrophilic PVA-co-PE nanofibrous membranes with controlled fiber sizes were prepared via a melt extrusion process. A chelating group, iminodiacetic acid (IDA), was covalently attached to cyanuric acid activated membrane surfaces to form coordinative complexes with metal ions. The prepared membranes were applied to recover a model protein, lysozyme, under various conditions, and a high lysozyme adsorption capacity of 199 mg/g membrane was found under the defined optimum conditions. Smaller fiber size with a higher immobilized metal ion density on membrane surfaces showed greater lysozyme adsorption capacity. The lysozyme adsorption capacity remained consistent during five repeated cycles of adsorption-elution operations, and up to 95% of adsorbed lysozyme was efficiently eluted by using a phosphate buffer containing 0.5 M NaCl and 0.5 M imidazole as an elution media. The successful separation of lysozyme with high purity from fresh chicken egg white was achieved by using the present affinity membrane. These remarkable features, such as high capacity and selectivity, easy regeneration, as well as reliable reusability, demonstrated the great potential of the metal-chelate affinity complex immobilized nanofibrous membranes for selective protein separation.

  13. Highly Selective Fluorescent Sensing of Proteins Based on a Fluorescent Molecularly Imprinted Nanosensor

    PubMed Central

    Deng, Qiliang; Wu, Jianhua; Zhai, Xiaorui; Fang, Guozhen; Wang, Shuo

    2013-01-01

    A fluorescent molecularly imprinted nanosensor was obtained by grafting imprinted polymer onto the surface of multi-wall carbon nanotubes and post-imprinting treatment with fluorescein isothiocyanate (FITC). The fluorescence of lysozyme-imprinted polymer (Lys-MIP) was quenched more strongly by Lys than that of nonimprinted polymer (NIP), which indicated that the Lys-MIP could recognize Lys. The resulted imprinted material has the ability to selectively sense a target protein, and an imprinting factor of 3.34 was achieved. The Lys-MIP also showed selective detection for Lys among other proteins such as cytochrome C (Cyt C), hemoglobin (HB) and bovine serum albumin (BSA) due to the imprinted sites in the Lys-MIP. This approach combines the high selectivity of surface molecular imprinting technology and fluorescence, and converts binding events into detectable signals by monitoring fluorescence spectra. Therefore, it will have further applications for Lys sensing. PMID:24077318

  14. 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

  15. 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

  16. Dynamic proteomics in modeling of the living cell. Protein-protein interactions.

    PubMed

    Terentiev, A A; Moldogazieva, N T; Shaitan, K V

    2009-12-01

    This review is devoted to describing, summarizing, and analyzing of dynamic proteomics data obtained over the last few years and concerning the role of protein-protein interactions in modeling of the living cell. Principles of modern high-throughput experimental methods for investigation of protein-protein interactions are described. Systems biology approaches based on integrative view on cellular processes are used to analyze organization of protein interaction networks. It is proposed that finding of some proteins in different protein complexes can be explained by their multi-modular and polyfunctional properties; the different protein modules can be located in the nodes of protein interaction networks. Mathematical and computational approaches to modeling of the living cell with emphasis on molecular dynamics simulation are provided. The role of the network analysis in fundamental medicine is also briefly reviewed.

  17. A neural network model for visual selection and shifting.

    PubMed

    Qiao, Yuanhua; Liu, Xiaojie; Miao, Jun; Duan, Lijuan

    2016-09-01

    In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instantaneous frequency. Unlike the differential equation model using limit cycle to simulate neuron oscillation, we build an instantaneous frequency mapping dynamic model to describe the change of the neuron frequency to avoid the difficulty of generating limit cycle. The activity of the neuron is rebuilt based on the instantaneous frequency and in this work, we use the first layer of neurons to implement image segmentation and the second layer of neurons to act as visual selector. The frequency of the second neuron (central neuron) is always changing, while central neuron resonates with the neurons corresponding to an object, the object is selected, then with the central neuron frequency changing, the selected object loses attention, the process goes on.

  18. Sorting of streptavidin protein coats on phase-separating model membranes.

    PubMed

    Manley, Suliana; Horton, Margaret R; Lecszynski, Szymon; Gast, Alice P

    2008-09-01

    Heterogeneities in cell membranes due to the ordering of lipids and proteins are thought to play an important role in enabling protein and lipid trafficking throughout the secretory pathway and in maintaining cell polarization. Protein-coated vesicles provide a major mechanism for intracellular transport of select cargo, which may be sorted into lipid microdomains; however, the mechanisms and physical constraints for lipid sorting by protein coats are relatively unexplored. We studied the influence of membrane-tethered protein coats on the sorting, morphology, and phase behavior of liquid-ordered lipid domains in a model system of giant unilamellar vesicles composed of dioleoylphosphatidylcholine, sphingomyelin, and cholesterol. We created protein-coated membranes by forming giant unilamellar vesicles containing a small amount of biotinylated lipid, thereby creating binding sites for streptavidin and avidin proteins in solution. We found that individual tethered proteins colocalize with the liquid-disordered phase, whereas ordered protein domains on the membrane surface colocalize with the liquid-ordered phase. These observations may be explained by considering the thermodynamics of this coupled system, which maximizes its entropy by cosegregating ordered protein and lipid domains. In addition, protein ordering inhibits lipid domain rearrangement and modifies the morphology and miscibility transition temperature of the membrane, most dramatically near the critical point in the membrane phase diagram. This observation suggests that liquid-ordered domains are stabilized by contact with ordered protein domains; it also hints at an approach to the stabilization of lipid microdomains by cross-linked protein clusters or ordered protein coats.

  19. Tyrosine-Selective Functionalization for Bio-Orthogonal Cross-Linking of Engineered Protein Hydrogels.

    PubMed

    Madl, Christopher M; Heilshorn, Sarah C

    2017-02-02

    Engineered protein hydrogels have shown promise as artificial extracellular matrix materials for the 3D culture of stem cells due to the ability to decouple hydrogel biochemistry and mechanics. The modular design of these proteins allows for incorporation of various bioactive sequences to regulate cellular behavior. However, the chemistry used to cross-link the proteins into hydrogels can limit what bioactive sequences can be incorporated, in order to prevent nonspecific cross-linking within the bioactive region. Bio-orthogonal cross-linking chemistries may allow for the incorporation of any arbitrary bioactive sequence, but site-selective and scalable incorporation of bio-orthogonal reactive groups such as azides that do not rely on commonly used amine-reactive chemistry is often challenging. In response, we have optimized the reaction of an azide-bearing 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) with engineered elastin-like proteins (ELPs) to selectively azide-functionalize tyrosine residues within the proteins. The PTAD-azide functionalized ELPs cross-link with bicyclononyne (BCN) functionalized ELPs via the strain-promoted azide-alkyne cycloaddition (SPAAC) reaction to form hydrogels. Human mesenchymal stem cells and murine neural progenitor cells encapsulated within these hydrogels remain highly viable and maintain their phenotypes in culture. Tyrosine-specific modification may expand the number of bioactive sequences that can be designed into protein-engineered materials by permitting incorporation of lysine-containing sequences without concern for nonspecific cross-linking.

  20. 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.

  1. Quantification of milk fat globule membrane proteins using selected reaction monitoring mass spectrometry.

    PubMed

    Fong, Bertram Y; Norris, Carmen S

    2009-07-22

    Although some of the physiological roles of milk fat globule membrane (MFGM) proteins are still unclear, there is increasing evidence that the consumption of bovine MFGM proteins has significant nutritional health benefits for humans; therefore, it may be important to be able to estimate the MFGM proteins in complex ingredients. In this study, the absolute quantification (AQUA) technique, which is typically used for the quantification of proteins in proteomic studies, was applied for the quantification of bovine MFGM proteins in butter milk protein concentrate. Six MFGM proteins (fatty acid binding protein, butyrophilin, PAS 6/7, adipophilin, xanthine oxidase, and mucin 1) were simultaneously quantified using high-resolution selected reaction monitoring mass spectrometry. Samples were rehydrated in 6.7 M urea buffer prior to dilution to 2.2 M before tryspin digestion. Direct rehydration in 2.2 M urea buffer or 2.2 M urea/20% acetonitilrile buffer reduced peptide yield digestion. Isotopically labeled peptides were used as internal standards. The coefficient of variation ranged from 5 to 15%, with a recovery of 84-105%. The limit of detection was in the range of 20-40 pg.

  2. 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.

  3. 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.

  4. Sexual selection and the adaptive evolution of PKDREJ protein in primates and rodents

    PubMed Central

    Vicens, Alberto; Gómez Montoto, Laura; Couso-Ferrer, Francisco; Sutton, Keith A.; Roldan, Eduardo R.S.

    2015-01-01

    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

  5. 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.

  6. 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.

  7. 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.

  8. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    PubMed

    Ollivier, Julien F; Shahrezaei, Vahid; Swain, Peter S

    2010-11-04

    Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  9. 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.

  10. The E-MS Algorithm: Model Selection with Incomplete Data.

    PubMed

    Jiang, Jiming; Nguyen, Thuan; Rao, J Sunil

    2015-04-04

    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.

  11. 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…

  12. Gasp, a Grb2-associating protein, is critical for positive selection of thymocytes

    PubMed Central

    Patrick, Michael S.; Oda, Hiroyo; Hayakawa, Kunihiro; Sato, Yoshinori; Eshima, Koji; Kirikae, Teruo; Iemura, Shun-ichiro; Shirai, Mutsunori; Abe, Takaya; Natsume, Tohru; Sasazuki, Takehiko; Suzuki, Harumi

    2009-01-01

    T cells develop in the thymus through positive and negative selection, which are responsible for shaping the T cell receptor (TCR) repertoire. To elucidate the molecular mechanisms involved in selection remains an area of intense interest. Here, we identified and characterized a gene product Gasp (Grb2-associating protein, also called Themis) that is critically required for positive selection. Gasp is a cytosolic protein with no known functional motifs that is expressed only in T cells, especially immature CD4/CD8 double positive (DP) thymocytes. In the absence of Gasp, differentiation of both CD4 and CD8 single positive cells in the thymus was severely inhibited, whereas all other TCR-induced events such as β-selection, negative selection, peripheral activation, and homeostatic proliferation were unaffected. We found that Gasp constitutively associates with Grb2 via its N-terminal Src homology 3 domain, suggesting that Gasp acts as a thymocyte-specific adaptor for Grb2 or regulates Ras signaling in DP thymocytes. Collectively, we have described a gene called Gasp that is critical for positive selection. PMID:19805304

  13. 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

    2016-07-25

    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.

  14. 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

  15. Mushroom Tyrosinase Oxidizes Tyrosine-rich Sequences, Allowing Selective Protein Functionalization

    PubMed Central

    Long, Marcus J. C.

    2012-01-01

    We show that mushroom tyrosinase catalyzes 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), cross-linking is observed. Besthorn’s reagent intercepts the o-quinone to give a characteristic pink complex, which can be observed directly on a denaturing SDS-PAGE gel. Similar labeled species can be formed 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

  16. Selective precipitation of haptoglobin and alpha2-macroglobulin from human serum using Alocasia macrorhiza tuber protein.

    PubMed

    Nayak, B Shivananda; Ulloor, N Jagadish; Shivaraj, B

    2002-12-01

    Treatment of human serum with ammonium sulfate fraction (0-50%) of Alocasia macrorhiza tuber extract resulted in precipitation at neutral pH. The precipitate was dissolved at pH 10.5 and chromatographed on Sephadex G-100 column. Two protein peaks were resolved. While the first peak represented alpha2-macroglobulin and haptoglobin, the second peak accounted for specific Alocasia protein. Incidentally the Alocasia protein was shown to be responsible for selective and specific precipitation of alpha2-macroglobulin and haptoglobin from serum. Thus the plant protein in its pure form or in crude stage could be used for the rapid isolation of two of the prominent alpha2-globulins.

  17. Tests of Bayesian model selection techniques for gravitational wave astronomy

    SciTech Connect

    Cornish, Neil J.; Littenberg, Tyson B.

    2007-10-15

    The analysis of gravitational wave data involves many model selection problems. The most important example is the detection problem of selecting between the data being consistent with instrument noise alone, or instrument noise and a gravitational wave signal. The analysis of data from ground based gravitational wave detectors is mostly conducted using classical statistics, and methods such as the Neyman-Peterson criteria are used for model selection. Future space based detectors, such as the Laser Interferometer Space Antenna (LISA), are expected to produce rich data streams containing the signals from many millions of sources. Determining the number of sources that are resolvable, and the most appropriate description of each source poses a challenging model selection problem that may best be addressed in a Bayesian framework. An important class of LISA sources are the millions of low-mass binary systems within our own galaxy, tens of thousands of which will be detectable. Not only are the number of sources unknown, but so are the number of parameters required to model the waveforms. For example, a significant subset of the resolvable galactic binaries will exhibit orbital frequency evolution, while a smaller number will have measurable eccentricity. In the Bayesian approach to model selection one needs to compute the Bayes factor between competing models. Here we explore various methods for computing Bayes factors in the context of determining which galactic binaries have measurable frequency evolution. The methods explored include a reverse jump Markov chain Monte Carlo algorithm, Savage-Dickie density ratios, the Schwarz-Bayes information criterion, and the Laplace approximation to the model evidence. We find good agreement between all of the approaches.

  18. Strong and widespread action of site-specific positive selection in the snake venom Kunitz/BPTI protein family

    PubMed Central

    Župunski, Vera; Kordiš, Dušan

    2016-01-01

    S1 family of serine peptidases is the largest family of peptidases. They are specifically inhibited by the Kunitz/BPTI inhibitors. Kunitz domain is characterized by the compact 3D structure with the most important inhibitory loops for the inhibition of S1 peptidases. In the present study we analysed the action of site-specific positive selection and its impact on the structurally and functionally important parts of the snake venom Kunitz/BPTI family of proteins. By using numerous models we demonstrated the presence of large numbers of site-specific positively selected sites that can reach between 30–50% of the Kunitz domain. The mapping of the positively selected sites on the 3D model of Kunitz/BPTI inhibitors has shown that these sites are located in the inhibitory loops 1 and 2, but also in the Kunitz scaffold. Amino acid replacements have been found exclusively on the surface, and the vast majority of replacements are causing the change of the charge. The consequence of these replacements is the change in the electrostatic potential on the surface of the Kunitz/BPTI proteins that may play an important role in the precise targeting of these inhibitors into the active site of S1 family of serine peptidases. PMID:27841308

  19. In silico modeling of the yeast protein and protein family interaction network

    NASA Astrophysics Data System (ADS)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2004-03-01

    Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

  20. 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.

  1. Fixation probability in a two-locus intersexual selection model.

    PubMed

    Durand, Guillermo; Lessard, Sabin

    2016-06-01

    We study a two-locus model of intersexual selection in a finite haploid population reproducing according to a discrete-time Moran model with a trait locus expressed in males and a preference locus expressed in females. We show that the probability of ultimate fixation of a single mutant allele for a male ornament introduced at random at the trait locus given any initial frequency state at the preference locus is increased by weak intersexual selection and recombination, weak or strong. Moreover, this probability exceeds the initial frequency of the mutant allele even in the case of a costly male ornament if intersexual selection is not too weak. On the other hand, the probability of ultimate fixation of a single mutant allele for a female preference towards a male ornament introduced at random at the preference locus is increased by weak intersexual selection and weak recombination if the female preference is not costly, and is strong enough in the case of a costly male ornament. The analysis relies on an extension of the ancestral recombination-selection graph for samples of haplotypes to take into account events of intersexual selection, while the symbolic calculation of the fixation probabilities is made possible in a reasonable time by an optimizing algorithm.

  2. Improvement of hydrological model calibration by selecting multiple parameter ranges

    NASA Astrophysics Data System (ADS)

    Wu, Qiaofeng; Liu, Shuguang; Cai, Yi; Li, Xinjian; Jiang, Yangming

    2017-01-01

    The parameters of hydrological models are usually calibrated to achieve good performance, owing to the highly non-linear problem of hydrology process modelling. However, parameter calibration efficiency has a direct relation with parameter range. Furthermore, parameter range selection is affected by probability distribution of parameter values, parameter sensitivity, and correlation. A newly proposed method is employed to determine the optimal combination of multi-parameter ranges for improving the calibration of hydrological models. At first, the probability distribution was specified for each parameter of the model based on genetic algorithm (GA) calibration. Then, several ranges were selected for each parameter according to the corresponding probability distribution, and subsequently the optimal range was determined by comparing the model results calibrated with the different selected ranges. Next, parameter correlation and sensibility were evaluated by quantifying two indexes, RC Y, X and SE, which can be used to coordinate with the negatively correlated parameters to specify the optimal combination of ranges of all parameters for calibrating models. It is shown from the investigation that the probability distribution of calibrated values of any particular parameter in a Xinanjiang model approaches a normal or exponential distribution. The multi-parameter optimal range selection method is superior to the single-parameter one for calibrating hydrological models with multiple parameters. The combination of optimal ranges of all parameters is not the optimum inasmuch as some parameters have negative effects on other parameters. The application of the proposed methodology gives rise to an increase of 0.01 in minimum Nash-Sutcliffe efficiency (ENS) compared with that of the pure GA method. The rising of minimum ENS with little change of the maximum may shrink the range of the possible solutions, which can effectively reduce uncertainty of the model performance.

  3. Fast and selective modification of thiol proteins/peptides by N-(phenylseleno)phthalimide.

    PubMed

    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.

  4. 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.

  5. 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

  6. A Peptidomimetic Antibiotic Targets Outer Membrane Proteins and Disrupts Selectively the Outer Membrane in Escherichia coli*

    PubMed Central

    Urfer, Matthias; Bogdanovic, Jasmina; Lo Monte, Fabio; Moehle, Kerstin; Zerbe, Katja; Omasits, Ulrich; Ahrens, Christian H.; Pessi, Gabriella; Eberl, Leo; Robinson, John A.

    2016-01-01

    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

  7. 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.

  8. Uniform design based SVM model selection for face recognition

    NASA Astrophysics Data System (ADS)

    Li, Weihong; Liu, Lijuan; Gong, Weiguo

    2010-02-01

    Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

  9. Predicting bacteriophage proteins located in host cell with feature selection technique.

    PubMed

    Ding, Hui; Liang, Zhi-Yong; Guo, Feng-Biao; Huang, Jian; Chen, Wei; Lin, Hao

    2016-04-01

    A bacteriophage is a virus that can infect a bacterium. The fate of an infected bacterium is determined by the bacteriophage proteins located in the host cell. Thus, reliably identifying bacteriophage proteins located in the host cell is extremely important to understand their functions and discover potential anti-bacterial drugs. Thus, in this paper, a computational method was developed to recognize bacteriophage proteins located in host cells based only on their amino acid sequences. The analysis of variance (ANOVA) combined with incremental feature selection (IFS) was proposed to optimize the feature set. Using a jackknife cross-validation, our method can discriminate between bacteriophage proteins located in a host cell and the bacteriophage proteins not located in a host cell with a maximum overall accuracy of 84.2%, and can further classify bacteriophage proteins located in host cell cytoplasm and in host cell membranes with a maximum overall accuracy of 92.4%. To enhance the value of the practical applications of the method, we built a web server called PHPred (〈http://lin.uestc.edu.cn/server/PHPred〉). We believe that the PHPred will become a powerful tool to study bacteriophage proteins located in host cells and to guide related drug discovery.

  10. Thermochemical nanolithography of multi-functional templates for selective assembly of bioactive proteins

    NASA Astrophysics Data System (ADS)

    Wang, Debin; Kodali, Vamsi; Underwood, William; Jarvholm, Jonas; Okada, Takashi; Jones, Simon; Rumi, Mariacristina; Dai, Zhenting; King, William; Marder, Seth; Curtis, Jennifer; Riedo, Elisa

    2009-03-01

    Atomic force microscopy based techniques have been successful in generating protein nano-arrays on various substrates. However, several challenges still exist in terms of resolution, writing speed, cost, substrate choice, protein bioactivity, multi-component patterning, and surface passivation. Recently, we have developed the use of thermochemical nanolithography combined with post covalent functionalization and molecular recognition on a polymer surface of a single chip to produce multiplexed nanopatterns at speeds of mm/s. These patterns can then be functionalized under native conditions to create tailored nano-assemblies of two different species of proteins coexisting on the same surface. The proteins attach selectively and strongly to the nanopatterns via covalent and/or specific interactions, while retaining their ability to interact specifically with other proteins in buffered solution. At present, this method has produced nanopatterns of bio-active proteins with features as small as 40 nm on polymer films. This technique opens up new possibilities in nanoscale manipulation of biological macromolecules as well as many molecular biophysics studies such as inter-protein interactions.

  11. 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…

  12. A topic evolution model with sentiment and selective attention

    NASA Astrophysics Data System (ADS)

    Si, Xia-Meng; Wang, Wen-Dong; Zhai, Chun-Qing; Ma, Yan

    2017-04-01

    Topic evolution is a hybrid dynamics of information propagation and opinion interaction. The dynamics of opinion interaction is inherently interwoven with the dynamics of information propagation in the network, owing to the bidirectional influences between interaction and diffusion. The degree of sentiment determines if the topic can continue to spread from this node, and the selective attention determines the information flow direction and communicatee selection. For this end, we put forward a sentiment-based mixed dynamics model with selective attention, and applied the Bayesian updating rules on it. Our model can indirectly describe the isolated users who seem isolated from a topic due to some reasons even everybody around them has heard about it. Numerical simulations show that, more insiders initially and fewer simultaneous spreaders can lessen the extremism. To promote the topic diffusion or restrain the prevailing of extremism, fewer agents with constructive motivation and more agents with no involving motivation are encouraged.

  13. 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.

  14. The Roles of Bud-Site-Selection Proteins during Haploid Invasive Growth in Yeast

    PubMed Central

    Cullen, Paul J.; Sprague, George F.

    2002-01-01

    In haploid strains of Saccharomyces cerevisiae, glucose depletion causes invasive growth, a foraging response that requires a change in budding pattern from axial to unipolar-distal. To begin to address how glucose influences budding pattern in the haploid cell, we examined the roles of bud-site-selection proteins in invasive growth. We found that proteins required for bipolar budding in diploid cells were required for haploid invasive growth. In particular, the Bud8p protein, which marks and directs bud emergence to the distal pole of diploid cells, was localized to the distal pole of haploid cells. In response to glucose limitation, Bud8p was required for the localization of the incipient bud site marker Bud2p to the distal pole. Three of the four known proteins required for axial budding, Bud3p, Bud4p, and Axl2p, were expressed and localized appropriately in glucose-limiting conditions. However, a fourth axial budding determinant, Axl1p, was absent in filamentous cells, and its abundance was controlled by glucose availability and the protein kinase Snf1p. In the bud8 mutant in glucose-limiting conditions, apical growth and bud site selection were uncoupled processes. Finally, we report that diploid cells starved for glucose also initiate the filamentous growth response. PMID:12221111

  15. Selective protein denitrosylation activity of Thioredoxin-h5 modulates plant Immunity.

    PubMed

    Kneeshaw, Sophie; Gelineau, Silvère; Tada, Yasuomi; Loake, Gary J; Spoel, Steven H

    2014-10-02

    In eukaryotes, bursts of reactive oxygen and nitrogen species mediate cellular responses to the environment by modifying cysteines of signaling proteins. Cysteine reactivity toward nitric oxide (NO) leads to formation of S-nitrosothiols (SNOs) that play important roles in pathogenesis and immunity. However, it remains poorly understood how SNOs are employed as specific, reversible signaling cues. Here we show that in plant immunity the oxidoreductase Thioredoxin-h5 (TRXh5) reverses SNO modifications by acting as a selective protein-SNO reductase. While TRXh5 failed to restore immunity in gsnor1 mutants that display excessive accumulation of the NO donor S-nitrosoglutathione, it rescued immunity in nox1 mutants that exhibit elevated levels of free NO. Rescue by TRXh5 was conferred through selective denitrosylation of excessive protein-SNO, which reinstated signaling by the immune hormone salicylic acid. Our data indicate that TRXh5 discriminates between protein-SNO substrates to provide previously unrecognized specificity and reversibility to protein-SNO signaling in plant immunity.

  16. Membrane proteins bind lipids selectively to modulate their structure and function

    PubMed Central

    Allison, Timothy M.; Ulmschneider, Martin B.; Degiacomi, Matteo T.; Baldwin, Andrew J.; Robinson, Carol V.

    2014-01-01

    Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments1-7 and that lipids can bind to specific sites, for example in potassium channels8. Fundamental questions remain however regarding the extent of membrane protein selectivity toward lipids. Here we report a mass spectrometry (MS) approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL), aquaporin Z (AqpZ), and the ammonia channel (AmtB) using ion mobility MS (IM-MS), which reports gas-phase collision cross sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas-phase. By resolving lipid-bound states we then rank bound lipids based on their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Results show that lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability, the highest-ranking lipid however is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation9. AqpZ is also stabilized by many lipids with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays, we discover that cardiolipin modulates AqpZ function. Analogous experiments identify AmtB as being highly selective for phosphatidylglycerol prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that reposition AmtB residues to interact with the lipid bilayer. Overall our results demonstrate that resistance to unfolding correlates with specific lipid-binding events enabling distinction of lipids that merely bind from those that modulate membrane protein structure and/or function. We anticipate that these

  17. A model for non-obligate oligomer formation in protein aggregration

    PubMed Central

    Healy, Eamonn F.

    2015-01-01

    Using solvent-exposed intramolecular backbone hydrogen bonds as physico-chemical descriptors for protein packing, a role for transient, non-obligate oligomers in the formation of aberrant protein aggregates is presented. Oligomeric models of the both wild type (wt) and select mutant variants of superoxide dismutase (SOD1) are proposed to provide a structural basis for investigating the etiology of Amyotrophic Lateral Sclerosis (ALS). PMID:26282203

  18. Selection and Retention in Teacher Education: A Model

    ERIC Educational Resources Information Center

    Brubaker, Harold A.

    1976-01-01

    With the stabilization of student population and a demand for improvement in the quality of prospective teachers, a model has been developed for improving selection-retention procedures, giving administrative organization, role of student personnel services, criteria for admission to the profession, and provisions for probationary status,…

  19. Selecting Microcomputer Network Configurations: A Model for Technological Endurance.

    ERIC Educational Resources Information Center

    Drummond, Marshall; And Others

    A model approach is suggested for the selection of a microcomputer network that will identify specific needs and arrive at solutions with maximum flexibility to avoid technological obsolescence. Chapter 1 specifies functional needs for a network design. This chapter discusses the process of evaluating whether a network is appropriate; examines and…

  20. An Assessment-Based Model for Counseling Strategy Selection.

    ERIC Educational Resources Information Center

    Nelson, Mary Lee

    2002-01-01

    Presents a counseling strategy selection model grounded in technical eclecticism and based on thorough assessment of the client's problems. Assessment should consider client mental health, counseling goals, problem complexity, and capacity and desire for insight. Distinguishing between simple and complex problems can aid assessment and provide…

  1. 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…

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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).

  7. Selective excitation for spectral editing and assignment in separated local field experiments of oriented membrane proteins

    NASA Astrophysics Data System (ADS)

    Koroloff, Sophie N.; Nevzorov, Alexander A.

    2017-01-01

    Spectroscopic assignment of NMR spectra for oriented uniformly labeled membrane proteins embedded in their native-like bilayer environment is essential for their structure determination. However, sequence-specific assignment in oriented-sample (OS) NMR is often complicated by insufficient resolution and spectral crowding. Therefore, the assignment process is usually done by a laborious and expensive "shotgun" method involving multiple selective labeling of amino acid residues. Presented here is a strategy to overcome poor spectral resolution in crowded regions of 2D spectra by selecting resolved "seed" residues via soft Gaussian pulses inserted into spin-exchange separated local-field experiments. The Gaussian pulse places the selected polarization along the z-axis while dephasing the other signals before the evolution of the 1H-15N dipolar couplings. The transfer of magnetization is accomplished via mismatched Hartmann-Hahn conditions to the nearest-neighbor peaks via the proton bath. By optimizing the length and amplitude of the Gaussian pulse, one can also achieve a phase inversion of the closest peaks, thus providing an additional phase contrast. From the superposition of the selective spin-exchanged SAMPI4 onto the fully excited SAMPI4 spectrum, the 15N sites that are directly adjacent to the selectively excited residues can be easily identified, thereby providing a straightforward method for initiating the assignment process in oriented membrane proteins.

  8. 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

  9. Positive Selection Pressure Drives Variation on the Surface-Exposed Variable Proteins of the Pathogenic Neisseria.

    PubMed

    Wachter, Jenny; 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.

  10. De novo protein conformational sampling using a probabilistic graphical model.

    PubMed

    Bhattacharya, Debswapna; Cheng, Jianlin

    2015-11-06

    Efficient exploration of protein conformational space remains challenging especially for large proteins when assembling discretized structural fragments extracted from a protein structure data database. We propose a fragment-free probabilistic graphical model, FUSION, for conformational sampling in continuous space and assess its accuracy using 'blind' protein targets with a length up to 250 residues from the CASP11 structure prediction exercise. The method reduces sampling bottlenecks, exhibits strong convergence, and demonstrates better performance than the popular fragment assembly method, ROSETTA, on relatively larger proteins with a length of more than 150 residues in our benchmark set. FUSION is freely available through a web server at http://protein.rnet.missouri.edu/FUSION/.

  11. Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.

    PubMed

    Huang, Chuen-Der; Lin, Chin-Teng; Pal, Nikhil Ranjan

    2003-12-01

    The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the

  12. Selected eosinophil proteins as markers of inflammation in atopic dermatitis patients.

    PubMed

    Jenerowicz, Dorotaz; Czarnecka-Operacz, Magdalena; Silny, Wojciech

    2006-01-01

    Atopic dermatitis (AD) is an inflammatory skin disease characterized by chronic and recurrent course, beginning primarily in early childhood. The etiopathogenesis of AD has not yet been fully understood, although various types of inflammatory cells including eosinophils may be involved in its pathomechanism. The basic aim of the study was to evaluate the usefulness of selected eosinophil proteins in serum and urine of AD patients, as markers of disease severity. The study also aimed to analyze correlations between the level of examined proteins and parameters such as skin prick test (SPT) results, serum concentration of total IgE, and coexistence of symptoms of other atopic diseases. The study included 30 AD patients and two control groups: 30 patients suffering from chronic urticaria and 30 healthy individuals. The mean level of eosinophil proteins measured in serum and urine of AD patients was higher than that in controls, although a significant difference was only recorded for serum and urine level of eosinophil protein X (EPX). Patients with very severe/severe AD presented higher levels of eosinophil proteins than patients presenting with mild/moderate AD, although no significant difference was found between these two groups. AD patients with positive SPT results and detectable specific IgE in serum, and with coexisting symptoms of other atopic diseases presented with higher mean levels of serum and urine eosinophil proteins than AD cases with negative SPT results and without any symptoms of other atopic diseases. In children suffering from AD, serum eosinophil cationic protein level, EPX level and urine EPX level were higher than those in healthy children, however, without statistical significance. Study results suggested a significant role of eosinophils in the etiopathogenesis of AD. Serum and urine levels of selected eosinophil proteins may serve as an important part of diagnostic approach to AD patients, especially in differentiation of allergic and non

  13. 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)

  14. 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.

  15. Unbiased descriptor and parameter selection confirms the potential of proteochemometric modelling

    PubMed Central

    Freyhult, Eva; Prusis, Peteris; Lapinsh, Maris; Wikberg, Jarl ES; Moulton, Vincent; Gustafsson, Mats G

    2005-01-01

    Background Proteochemometrics is a new methodology that allows prediction of protein function directly from real interaction measurement data without the need of 3D structure information. Several reported proteochemometric models of ligand-receptor interactions have already yielded significant insights into various forms of bio-molecular interactions. The proteochemometric models are multivariate regression models that predict binding affinity for a particular combination of features of the ligand and protein. Although proteochemometric models have already offered interesting results in various studies, no detailed statistical evaluation of their average predictive power has been performed. In particular, variable subset selection performed to date has always relied on using all available examples, a situation also encountered in microarray gene expression data analysis. Results A methodology for an unbiased evaluation of the predictive power of proteochemometric models was implemented and results from applying it to two of the largest proteochemometric data sets yet reported are presented. A double cross-validation loop procedure is used to estimate the expected performance of a given design method. The unbiased performance estimates (P2) obtained for the data sets that we consider confirm that properly designed single proteochemometric models have useful predictive power, but that a standard design based on cross validation may yield models with quite limited performance. The results also show that different commercial software packages employed for the design of proteochemometric models may yield very different and therefore misleading performance estimates. In addition, the differences in the models obtained in the double CV loop indicate that detailed chemical interpretation of a single proteochemometric model is uncertain when data sets are small. Conclusion The double CV loop employed offer unbiased performance estimates about a given proteochemometric

  16. Broccoli: rapid selection of an RNA mimic of green fluorescent protein by fluorescence-based selection and directed evolution.

    PubMed

    Filonov, Grigory S; Moon, Jared D; Svensen, Nina; Jaffrey, Samie R

    2014-11-19

    Genetically encoded fluorescent ribonucleic acids (RNAs) have diverse applications, including imaging RNA trafficking and as a component of RNA-based sensors that exhibit fluorescence upon binding small molecules in live cells. These RNAs include the Spinach and Spinach2 aptamers, which bind and activate the fluorescence of fluorophores similar to that found in green fluorescent protein. Although additional highly fluorescent RNA-fluorophore complexes would extend the utility of this technology, the identification of novel RNA-fluorophore complexes is difficult. Current approaches select aptamers on the basis of their ability to bind fluorophores, even though fluorophore binding alone is not sufficient to activate fluorescence. Additionally, aptamers require extensive mutagenesis to efficiently fold and exhibit fluorescence in living cells. Here we describe a platform for rapid generation of highly fluorescent RNA-fluorophore complexes that are optimized for function in cells. This procedure involves selection of aptamers on the basis of their binding to fluorophores, coupled with fluorescence-activated cell sorting (FACS) of millions of aptamers expressed in Escherichia coli. Promising aptamers are then further optimized using a FACS-based directed evolution approach. Using this approach, we identified several novel aptamers, including a 49-nt aptamer, Broccoli. Broccoli binds and activates the fluorescence of (Z)-4-(3,5-difluoro-4-hydroxybenzylidene)-1,2-dimethyl-1H-imidazol-5(4H)-one. Broccoli shows robust folding and green fluorescence in cells, and increased fluorescence relative to Spinach2. This reflects, in part, improved folding in the presence of low cytosolic magnesium concentrations. Thus, this novel fluorescence-based selection approach simplifies the generation of aptamers that are optimized for expression and performance in living cells.

  17. RNA and protein 3D structure modeling: similarities and differences.

    PubMed

    Rother, Kristian; Rother, Magdalena; Boniecki, Michał; Puton, Tomasz; Bujnicki, Janusz M

    2011-09-01

    In analogy to proteins, the function of RNA depends on its structure and dynamics, which are encoded in the linear sequence. While there are numerous methods for computational prediction of protein 3D structure from sequence, there have been very few such methods for RNA. This review discusses template-based and template-free approaches for macromolecular structure prediction, with special emphasis on comparison between the already tried-and-tested methods for protein structure modeling and the very recently developed "protein-like" modeling methods for RNA. We highlight analogies between many successful methods for modeling of these two types of biological macromolecules and argue that RNA 3D structure can be modeled using "protein-like" methodology. We also highlight the areas where the differences between RNA and proteins require the development of RNA-specific solutions.

  18. A resource dependent protein synthesis model for evaluating synthetic circuits.

    PubMed

    Halter, Wolfgang; Montenbruck, Jan Maximilian; Tuza, Zoltan A; Allgöwer, Frank

    2017-03-09

    Reliable in silico design of synthetic gene networks necessitates novel approaches to model the process of protein synthesis under the influence of limited resources. We present such a novel protein synthesis model which originates from the Ribosome Flow Model and among other things describes the movement of RNA-polymerase and ribosomes on mRNA and DNA templates, respectively. By analyzing the convergence properties of this model based upon geometric considerations, we present additional insights into the dynamic mechanisms of the process of protein synthesis. Further, we demonstrate how this model can be used to evaluate the performance of synthetic gene circuits under different loading scenarios.

  19. Model selection for the extraction of movement primitives

    PubMed Central

    Endres, Dominik M.; Chiovetto, Enrico; Giese, Martin A.

    2013-01-01

    A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data. Popular examples are principal component analysis (PCA), independent component analysis (ICA), anechoic demixing, and the time-varying synergy model (d'Avella and Tresch, 2002). However, choosing the parameters of these models, or indeed choosing the type of model, is often done in a heuristic fashion, driven by result expectations as much as by the data. We propose an objective criterion which allows to select the model type, number of primitives and the temporal smoothness prior. Our approach is based on a Laplace approximation to the posterior distribution of the parameters of a given blind source separation model, re-formulated as a Bayesian generative model. We first validate our criterion on ground truth data, showing that it performs at least as good as traditional model selection criteria [Bayesian information criterion, BIC (Schwarz, 1978) and the Akaike Information Criterion (AIC) (Akaike, 1974)]. Then, we analyze human gait data, finding that an anechoic mixture model with a temporal smoothness constraint on the sources can best account for the data. PMID:24391580

  20. A model selection approach to analysis of variance and covariance.

    PubMed

    Alber, Susan A; Weiss, Robert E

    2009-06-15

    An alternative to analysis of variance is a model selection approach where every partition of the treatment means into clusters with equal value is treated as a separate model. The null hypothesis that all treatments are equal corresponds to the partition with all means in a single cluster. The alternative hypothesis correspond to the set of all other partitions of treatment means. A model selection approach can also be used for a treatment by covariate interaction, where the null hypothesis and each alternative correspond to a partition of treatments into clusters with equal covariate effects. We extend the partition-as-model approach to simultaneous inference for both treatment main effect and treatment interaction with a continuous covariate with separate partitions for the intercepts and treatment-specific slopes. The model space is the Cartesian product of the intercept partition and the slope partition, and we develop five joint priors for this model space. In four of these priors the intercept and slope partition are dependent. We advise on setting priors over models, and we use the model to analyze an orthodontic data set that compares the frictional resistance created by orthodontic fixtures.

  1. Changing Folding and Binding Stability in a Viral Coat Protein: A Comparison between Substitutions Accessible through Mutation and Those Fixed by Natural Selection

    PubMed Central

    Wichman, Holly A.; Ytreberg, F. Marty

    2014-01-01

    Previous studies have shown that most random amino acid substitutions destabilize protein folding (i.e. increase the folding free energy). No analogous studies have been carried out for protein-protein binding. Here we use a structure-based model of the major coat protein in a simple virus, bacteriophage φX174, to estimate the free energy of folding of a single coat protein and binding of five coat proteins within a pentameric unit. We confirm and extend previous work in finding that most accessible substitutions destabilize both protein folding and protein-protein binding. We compare the pool of accessible substitutions with those observed among the φX174-like wild phage and in experimental evolution with φX174. We find that observed substitutions have smaller effects on stability than expected by chance. An analysis of adaptations at high temperatures suggests that selection favors either substitutions with no effect on stability or those that simultaneously stabilize protein folding and slightly destabilize protein binding. We speculate that these mutations might involve adjusting the rate of capsid assembly. At normal laboratory temperature there is little evidence of directional selection. Finally, we show that cumulative changes in stability are highly variable; sometimes they are well beyond the bounds of single substitution changes and sometimes they are not. The variation leads us to conclude that phenotype selection acts on more than just stability. Instances of larger cumulative stability change (never via a single substitution despite their availability) lead us to conclude that selection views stability at a local, not a global, level. PMID:25405628

  2. How Many Separable Sources? Model Selection In Independent Components Analysis

    PubMed Central

    Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

    2015-01-01

    Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

  3. 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.

  4. Bayesian Variable Selection on Model Spaces Constrained by Heredity Conditions.

    PubMed

    Taylor-Rodriguez, Daniel; Womack, Andrew; Bliznyuk, Nikolay

    2016-01-01

    This paper investigates Bayesian variable selection when there is a hierarchical dependence structure on the inclusion of predictors in the model. In particular, we study the type of dependence found in polynomial response surfaces of orders two and higher, whose model spaces are required to satisfy weak or strong heredity conditions. These conditions restrict the inclusion of higher-order terms depending upon the inclusion of lower-order parent terms. We develop classes of priors on the model space, investigate their theoretical and finite sample properties, and provide a Metropolis-Hastings algorithm for searching the space of models. The tools proposed allow fast and thorough exploration of model spaces that account for hierarchical polynomial structure in the predictors and provide control of the inclusion of false positives in high posterior probability models.

  5. Model building strategy for logistic regression: purposeful selection.

    PubMed

    Zhang, Zhongheng

    2016-03-01

    Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

  6. Bayesian analysis. II. Signal detection and model selection

    NASA Astrophysics Data System (ADS)

    Bretthorst, G. Larry

    In the preceding. paper, Bayesian analysis was applied to the parameter estimation problem, given quadrature NMR data. Here Bayesian analysis is extended to the problem of selecting the model which is most probable in view of the data and all the prior information. In addition to the analytic calculation, two examples are given. The first example demonstrates how to use Bayesian probability theory to detect small signals in noise. The second example uses Bayesian probability theory to compute the probability of the number of decaying exponentials in simulated T1 data. The Bayesian answer to this question is essentially a microcosm of the scientific method and a quantitative statement of Ockham's razor: theorize about possible models, compare these to experiment, and select the simplest model that "best" fits the data.

  7. Model selection as a science driver for dark energy surveys

    NASA Astrophysics Data System (ADS)

    Mukherjee, Pia; Parkinson, David; Corasaniti, Pier Stefano; Liddle, Andrew R.; Kunz, Martin

    2006-07-01

    A key science goal of upcoming dark energy surveys is to seek time-evolution of the dark energy. This problem is one of model selection, where the aim is to differentiate between cosmological models with different numbers of parameters. However, the power of these surveys is traditionally assessed by estimating their ability to constrain parameters, which is a different statistical problem. In this paper, we use Bayesian model selection techniques, specifically forecasting of the Bayes factors, to compare the abilities of different proposed surveys in discovering dark energy evolution. We consider six experiments - supernova luminosity measurements by the Supernova Legacy Survey, SNAP, JEDI and ALPACA, and baryon acoustic oscillation measurements by WFMOS and JEDI - and use Bayes factor plots to compare their statistical constraining power. The concept of Bayes factor forecasting has much broader applicability than dark energy surveys.

  8. 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.

  9. Tracking membrane protein association in model membranes.

    PubMed

    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 A, 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 extract a

  10. Protein fragment swapping: a method for asymmetric, selective site-directed recombination.

    PubMed

    Zheng, Wei; Griswold, Karl E; Bailey-Kellogg, Chris

    2010-03-01

    This article presents a new approach to site-directed recombination, swapping combinations of selected discontiguous fragments from a source protein in place of corresponding fragments of a target protein. By being both asymmetric (differentiating source and target) and selective (swapping discontiguous fragments), our method focuses experimental effort on a more restricted portion of sequence space, constructing hybrids that are more likely to have the properties that are the objective of the experiment. Furthermore, since the source and target need to be structurally homologous only locally (rather than overall), our method supports swapping fragments from functionally important regions of a source into a target "scaffold" (for example, to humanize an exogenous therapeutic protein). A protein fragment swapping plan is defined by the residue position boundaries of the fragments to be swapped; it is assessed by an average potential score over the resulting hybrid library, with singleton and pairwise terms evaluating the importance and fit of the swapped residues. While we prove that it is NP-hard to choose an optimal set of fragments under such a potential score, we develop an integer programming approach, which we call Swagmer, that works very well in practice. We demonstrate the effectiveness of our method in three swapping problems: selective recombination between beta-lactamases, activity swapping between glutathione transferases, and activity swapping between carboxylases and mutases in the purE family. We show that the selective recombination approach generates better plan (in terms of resulting potential score) than traditional site-directed recombination approaches. We also show that in all cases the optimized experiments are significantly better than ones that would result from stochastic methods.

  11. 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

  12. 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

  13. Supplier Selection in Virtual Enterprise Model of Manufacturing Supply Network

    NASA Astrophysics Data System (ADS)

    Kaihara, Toshiya; Opadiji, Jayeola F.

    The market-based approach to manufacturing supply network planning focuses on the competitive attitudes of various enterprises in the network to generate plans that seek to maximize the throughput of the network. It is this competitive behaviour of the member units that we explore in proposing a solution model for a supplier selection problem in convergent manufacturing supply networks. We present a formulation of autonomous units of the network as trading agents in a virtual enterprise network interacting to deliver value to market consumers and discuss the effect of internal and external trading parameters on the selection of suppliers by enterprise units.

  14. Mechanisms of m-cresol induced protein aggregation studied using a model protein cytochrome c†

    PubMed Central

    Singh, Surinder M.; Hutchings, Regina L.; Mallela, Krishna M.G.

    2014-01-01

    Multi-dose protein formulations require an effective antimicrobial preservative (AP) to inhibit microbial growth during long-term storage of unused formulations. m-cresol is one such AP, but has been shown to cause protein aggregation. However, the fundamental physical mechanisms underlying such AP-induced protein aggregation are not understood. In this study, we used a model protein cytochrome c to identify the protein unfolding that triggers protein aggregation. m-cresol induced cytochrome c aggregation at preservative concentrations that are commonly used to inhibit microbial growth. Addition of m-cresol decreased the temperature at which the protein aggregated and increased the aggregation rate. However, m-cresol did not perturb the tertiary or secondary structure of cytochrome c. Instead, it populated an “invisible” partially unfolded intermediate where a local protein region around the methionine residue at position 80 was unfolded. Stabilizing the Met80 region drastically decreased the protein aggregation, which conclusively shows that this local protein region acts as an aggregation “hot-spot”. Based on these results, we propose that APs induce protein aggregation by partial rather than global unfolding. Because of the availability of site-specific probes to monitor different levels of protein unfolding, cytochrome c provided a unique advantage in characterizing the partial protein unfolding that triggers protein aggregation. PMID:21229618

  15. Selection of DNA nanoparticles with preferential binding to aggregated protein target

    PubMed Central

    Ruff, Laura E.; Sapre, Ajay A.; Plaut, Justin S.; De Maere, Elisabeth; Mortier, Charlotte; Nguyen, Valerie; Separa, Kevin; Vandenbogaerde, Sofie; Vandewalle, Laura; Esener, Sadik C.; Messmer, Bradley T.

    2016-01-01

    High affinity and specificity are considered essential for affinity reagents and molecularly-targeted therapeutics, such as monoclonal antibodies. However, life's own molecular and cellular machinery consists of lower affinity, highly multivalent interactions that are metastable, but easily reversible or displaceable. With this inspiration, we have developed a DNA-based reagent platform that uses massive avidity to achieve stable, but reversible specific recognition of polyvalent targets. We have previously selected these DNA reagents, termed DeNAno, against various cells and now we demonstrate that DeNAno specific for protein targets can also be selected. DeNAno were selected against streptavidin-, rituximab- and bevacizumab-coated beads. Binding was stable for weeks and unaffected by the presence of soluble target proteins, yet readily competed by natural or synthetic ligands of the target proteins. Thus DeNAno particles are a novel biomolecular recognition agent whose orthogonal use of avidity over affinity results in uniquely stable yet reversible binding interactions. PMID:26969734

  16. Human Immunodeficiency Virus Integration Protein Expressed in Escherichia Coli Possesses Selective DNA Cleaving Activity

    NASA Astrophysics Data System (ADS)

    Sherman, Paula A.; Fyfe, James A.

    1990-07-01

    The human immunodeficiency virus (HIV) integration protein, a potential target for selective antiviral therapy, was expressed in Escherichia coli. The purified protein, free of detectable contaminating endonucleases, selectively cleaved double-stranded DNA oligonucleotides that mimic the U3 and the U5 termini of linear HIV DNA. Two nucleotides were removed from the 3' ends of both the U5 plus strand and the U3 minus strand; in both cases, cleavage was adjacent to a conserved CA dinucleotide. The reaction was metal-ion dependent, with a preference for Mn2+ over Mg2+. Reaction selectivity was further demonstrated by the lack of cleavage of an HIV U5 substrate on the complementary (minus) strand, an analogous substrate that mimics the U3 terminus of an avian retrovirus, and an HIV U5 substrate in which the conserved CA dinucleotide was replaced with a TA dinucleotide. Such an integration protein-mediated cleavage reaction is expected to occur as part of the integration event in the retroviral life cycle, in which a double-stranded DNA copy of the viral RNA genome is inserted into the host cell DNA.

  17. 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.

  18. The Jackprot Simulation Couples Mutation Rate with Natural Selection to Illustrate How Protein Evolution Is Not Random

    PubMed Central

    Espinosa, Avelina; Bai, Chunyan Y.

    2016-01-01

    Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke “design creationism” to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane's hydrophobic/philic nature; a selective “pore” for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the “jackprot,” which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the “jackprot,” or highest-fitness complete-peptide sequence, required cumulative smaller “wins” (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons (“jackdons” that led to “jackacids” that led to the “jackprot”). The “jackprot” is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide

  19. The Jackprot Simulation Couples Mutation Rate with Natural Selection to Illustrate How Protein Evolution Is Not Random.

    PubMed

    Paz-Y-Miño C, Guillermo; Espinosa, Avelina; Bai, Chunyan Y

    2011-09-01

    Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke "design creationism" to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane's hydrophobic/philic nature; a selective "pore" for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the "jackprot," which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the "jackprot," or highest-fitness complete-peptide sequence, required cumulative smaller "wins" (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons ("jackdons" that led to "jackacids" that led to the "jackprot"). The "jackprot" is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide "edition" and gene duplications to generate the 6

  20. Approaches to Assess Functional Selectivity in GPCRs: Evaluating G Protein Signaling in an Endogenous Environment

    PubMed Central

    Bohn, Laura M.; Zhou, Lei; Ho, Jo-Hao

    2016-01-01

    Ligand-directed signaling, biased agonism, and functional selectivity are terms that describe the propensity of a ligand to drive signaling toward one GPCR pathway over another. Most of the early examples demonstrated to date examine the divergence between GPCR signaling to G protein coupling and βarrestin2 recruitment. As biased agonists begin to become available based on cell-based screening criteria, a need arises to determine if G protein signaling biases will be maintained in the endogenous setting, wherein receptors are functioning to control relevant biological responses. This report presents our method and offers tips for evaluating G protein signaling in endogenous tissues. Predominately, brain tissues are discussed here; optimization points that can be applied to any tissues are highlighted. PMID:26260601

  1. Mutant p53 proteins bind DNA in a DNA structure-selective mode

    PubMed Central

    Göhler, Thomas; Jäger, Stefan; Warnecke, Gabriele; Yasuda, Hideyo; Kim, Ella; Deppert, Wolfgang

    2005-01-01

    Despite the loss of sequence-specific DNA binding, mutant p53 (mutp53) proteins can induce or repress transcription of mutp53-specific target genes. To date, the molecular basis for transcriptional modulation by mutp53 is not understood, but increasing evidence points to the possibility that specific interactions of mutp53 with DNA play an important role. So far, the lack of a common denominator for mutp53 DNA binding, i.e. the existence of common sequence elements, has hampered further characterization of mutp53 DNA binding. Emanating from our previous discovery that DNA structure is an important determinant of wild-type p53 (wtp53) DNA binding, we analyzed the binding of various mutp53 proteins to oligonucleotides mimicking non-B DNA structures. Using various DNA-binding assays we show that mutp53 proteins bind selectively and with high affinity to non-B DNA. In contrast to sequence-specific and DNA structure-dependent binding of wtp53, mutp53 DNA binding to non-B DNA is solely dependent on the stereo-specific configuration of the DNA, and not on DNA sequence. We propose that DNA structure-selective binding of mutp53 proteins is the basis for the well-documented interaction of mutp53 with MAR elements and for transcriptional activities mediates by mutp53. PMID:15722483

  2. Information theoretic model selection applied to supernovae data

    NASA Astrophysics Data System (ADS)

    Biesiada, Marek

    2007-02-01

    Current advances in observational cosmology suggest that our Universe is flat and dominated by dark energy. There are several different theoretical ideas invoked to explain the dark energy with relatively little guidance of which one of them might be right. Therefore the emphasis of ongoing and forthcoming research in this field shifts from estimating specific parameters of the cosmological model to the model selection. In this paper we apply an information theoretic model selection approach based on the Akaike criterion as an estimator of Kullback Leibler entropy. Although this approach has already been used by some authors in a similar context, this paper provides a more systematic introduction to the Akaike criterion. In particular, we present the proper way of ranking the competing models on the basis of Akaike weights (in Bayesian language: posterior probabilities of the models). This important ingredient is lacking from alternative studies dealing with cosmological applications of the Akaike criterion. Of the many particular models of dark energy we focus on four: quintessence, quintessence with a time varying equation of state, the braneworld scenario and the generalized Chaplygin gas model, and test them on Riess's gold sample. As a result we obtain that the best model—in terms of the Akaike criterion—is the quintessence model. The odds suggest that although there exist differences in the support given to specific scenarios by supernova data, most of the models considered receive similar support. The only exception is the Chaplygin gas which is considerably less supported. One can also note that models similar in structure, e.g. ΛCDM, quintessence and quintessence with a variable equation of state, are closer to each other in terms of Kullback Leibler entropy. Models having different structure, e.g. Chaplygin gas and the braneworld scenario, are more distant (in the Kullback Leibler sense) from the best one.

  3. Nucleocapsid and matrix protein contributions to selective human immunodeficiency virus type 1 genomic RNA packaging.

    PubMed

    Poon, D T; Li, G; Aldovini, A

    1998-03-01

    The nucleocapsid protein (NC) of retroviruses plays a major role in genomic RNA packaging, and some evidence has implicated the matrix protein (MA) of certain retroviruses in viral RNA binding. To further investigate the role of NC in the selective recognition of genomic viral RNA and to address the potential contribution of MA in this process, we constructed chimeric and deletion human immunodeficiency virus type 1 (HIV-1) mutants that alter the NC or MA protein. Both HIV and mouse mammary tumor virus (MMTV) NC proteins have two zinc-binding domains and similar basic amino acid compositions but differ substantially in total length, amino acid sequence, and spacing of the zinc-binding motifs. When the entire NC coding sequence of HIV was replaced with the MMTV NC coding sequence, we found that the HIV genome was incorporated into virions at 50% of wild-type levels. Viruses produced from chimeric HIV genomes with complete NC replacements, or with the two NC zinc-binding domains replaced with MMTV sequences, preferentially incorporated HIV genomes when both HIV and MMTV genomes were simultaneously present in the cell. Viruses produced from chimeric MMTV genomes in which the MMTV NC had been replaced with HIV NC preferentially incorporated MMTV genomes when both HIV and MMTV genomes were simultaneously present in the cell. In contrast, viruses produced from chimeric HIV genomes containing the Moloney NC, which contains a single zinc-binding motif, were previously shown to preferentially incorporate Moloney genomic RNA. Taken together, these results indicate that an NC protein with two zinc-binding motifs is required for specific HIV RNA packaging and that the amino acid context of these motifs, while contributing to the process, is less crucial for specificity. The data also suggest that HIV NC may not be the exclusive determinant of RNA selectivity. Analysis of an HIV MA mutant revealed that specific RNA packaging does not require MA protein.

  4. Arsenite Interacts Selectively with Zinc Finger Proteins Containing C3H1 or C4 Motifs*

    PubMed Central

    Zhou, Xixi; Sun, Xi; Cooper, Karen L.; Wang, Feng; Liu, Ke Jian; Hudson, Laurie G.

    2011-01-01

    Arsenic inhibits DNA repair and enhances the genotoxicity of DNA-damaging agents such as benzo[a]pyrene and ultraviolet radiation. Arsenic interaction with DNA repair proteins containing functional zinc finger motifs is one proposed mechanism to account for these observations. Here, we report that arsenite binds to both CCHC DNA-binding zinc fingers of the DNA repair protein PARP-1 (poly(ADP-ribose) polymerase-1). Furthermore, trivalent arsenite coordinated with all three cysteine residues as demonstrated by MS/MS. MALDI-TOF-MS analysis of peptides harboring site-directed substitutions of cysteine with histidine residues within the PARP-1 zinc finger revealed that arsenite bound to peptides containing three or four cysteine residues, but not to peptides with two cysteines, demonstrating arsenite binding selectivity. This finding was not unique to PARP-1; arsenite did not bind to a peptide representing the CCHH zinc finger of the DNA repair protein aprataxin, but did bind to an aprataxin peptide mutated to a CCHC zinc finger. To investigate the impact of arsenite on PARP-1 zinc finger function, we measured the zinc content and DNA-binding capacity of PARP-1 immunoprecipitated from arsenite-exposed cells. PARP-1 zinc content and DNA binding were decreased by 76 and 80%, respectively, compared with protein isolated from untreated cells. We observed comparable decreases in zinc content for XPA (xeroderma pigmentosum group A) protein (CCCC zinc finger), but not SP-1 (specificity protein-1) or aprataxin (CCHH zinc finger). These findings demonstrate that PARP-1 is a direct molecular target of arsenite and that arsenite interacts selectively with zinc finger motifs containing three or more cysteine residues. PMID:21550982

  5. Targeting tumor cells via EGF receptors: selective toxicity of an HBEGF-toxin fusion protein.

    PubMed

    Chandler, L A; Sosnowski, B A; McDonald, J R; Price, J E; Aukerman, S L; Baird, A; Pierce, G F; Houston, L L

    1998-09-25

    Over-expression of the epidermal growth factor receptor (EGFR) is a hallmark of numerous solid tumors, thus providing a means of selectively targeting therapeutic agents. Heparin-binding epidermal growth factor (HBEGF) binds to EGFRs with high affinity and to heparan sulfate proteoglycans, resulting in increased mitogenic potential compared to other EGF family members. We have investigated the feasibility of using HBEGF to selectively deliver a cytotoxic protein into EGFR-expressing tumor cells. Recombinant fusion proteins consisting of mature human HBEGF fused to the plant ribosome-inactivating protein saporin (SAP) were expressed in Escherichia coli. Purified HBEGF-SAP chimeras inhibited protein synthesis in a cell-free assay and competed with EGF for binding to receptors on intact cells. A construct with a 22-amino-acid flexible linker (L22) between the HBEGF and SAP moieties exhibited an affinity for the EGFR that was comparable to that of HBEGF. The sensitivity to HBEGF-L22-SAP was determined for a variety of human tumor cell lines, including the 60 cell lines comprising the National Cancer Institute Anticancer Drug Screen. HBEGF-L22-SAP was cytotoxic in vitro to a variety of EGFR-bearing cell lines and inhibited growth of EGFR-over-expressing human breast carcinoma cells in vivo. In contrast, the fusion protein had no effect on small-cell lung carcinoma cells, which are EGFR-deficient. Our results demonstrate that fusion proteins composed of HBEGF and SAP exhibit targeting specificity and cytotoxicity that may be of therapeutic value in treating a variety of EGFR-bearing malignancies.

  6. Modification and activation of Ras proteins by electrophilic prostanoids with different structure are site-selective.

    PubMed

    Renedo, Marta; Gayarre, Javier; García-Domínguez, Carlota A; Pérez-Rodríguez, Andrea; Prieto, Alicia; Cañada, F Javier; Rojas, José M; Pérez-Sala, Dolores

    2007-06-05

    Cyclopentenone prostanoids (cyP) arise as important modulators of inflammation and cell proliferation. Although their physiological significance has not been fully elucidated, their potent biological effects have spurred their study as leads for the development of therapeutic agents. A key determinant of cyP action is their ability to bind to thiol groups in proteins or in glutathione through Michael addition. Even though several protein targets for cyP addition have been identified, little is known about the structural determinants from the protein or the cyP that drive this modification. The results herein presented provide the first evidence that cyP with different structures target distinct thiol sites in a protein molecule, namely, H-Ras. Whereas 15-deoxy-Delta12,14-prostaglandin J2 (15d-PGJ2) and Delta12-PGJ2 preferentially target the C-terminal region containing cysteines 181 and 184, PGA1 and 8-iso-PGA1 bind mainly to cysteine 118, located in the GTP-binding motif. The biological counterparts of this specificity are the site-selective modification and activation of H-Ras in cells and the differential interaction of cyP with H, N, and K-Ras proteins. Cysteine 184 is unique to H-Ras, whereas cysteine 118 is present in the three Ras homologues. Consistent with this, PGA1 binds to and activates H-, N-, and K-Ras, thus differing from the preferential interaction of 15d-PGJ2 with H-Ras. These results put forward the possibility of influencing the selectivity of cyP-protein addition by modifying cyP structure. Furthermore, they may open new avenues for the development of cyP-based drugs.

  7. Evidence for directional selection acting on pheromone-binding proteins in the genus Choristoneura.

    PubMed

    Willett, C S

    2000-04-01

    Patterns of nucleotide variation consistent with the action of natural selection have been discovered at a number of different gene loci. Here, pheromone-binding proteins (PBPs) are examined to determine if selection has acted to fix amino acid changes in PBPs in lineages in which pheromone changes have occurred. PBPs from five different species of moths in the genus Choristoneura were sequenced, along with the PBP of Argyrotaenia velutinana, which serves as an outgroup. Three independent major pheromone changes are represented within this group of five Choristoneura species. Two different lineages show evidence for selection based on polymorphism and divergence comparisons and comparisons of rates of replacement evolution to silent and noncoding evolution. Along one of these lineages, leading to Choristoneura fumiferana, there has been a change to an aldehyde pheromone from an acetate pheromone. The second branch does not appear to be associated with a major pheromone change. Other branches in the tree show a trend toward greater replacement fixation than expected under neutrality. This trend could reflect undetected selective events within this group of PBPs. Selection appears to have acted to fix amino acid changes in the PBP of moths from the genus Choristoneura, but it is not clear that this selection is due to pheromone changes between species.

  8. Use of glycol ethers for selective release of periplasmic proteins from Gram-negative bacteria.

    PubMed

    Allen, Jeffrey R; Patkar, Anant Y; Frank, Timothy C; Donate, Felipe A; Chiu, Yuk Chun; Shields, Jefry E; Gustafson, Mark E

    2007-01-01

    Genetic modification of Gram-negative bacteria to express a desired protein within the cell's periplasmic space, located between the inner cytoplasmic membrane and the outer cell wall, can offer an attractive strategy for commercial production of therapeutic proteins and industrial enzymes. In certain applications, the product expression rate is high, and the ability to isolate the product from the cell mass is greatly enhanced because of the product's compartmentalized location within the cell. Protein release methods that increase the permeability of the outer cell wall for primary recovery, but avoid rupturing the inner cell membrane, reduce contamination of the recovered product with other host cell components and simplify final purification. This article reports representative data for a new release method employing glycol ether solvents. The example involves the use of 2-butoxyethanol (commonly called ethylene glycol n-butyl ether or EB) for selective release of a proprietary biopharmaceutical protein produced in the periplasmic space of Pseudomonas fluorescens. In this example, glycol ether treatment yielded approximately 65% primary recovery with approximately 80% purity on a protein-only basis. Compared with other methods including heat treatment, osmotic shock, and the use of surfactants, the glycol ether treatment yielded significantly reduced concentrations of other host cell proteins, lipopolysaccharide endotoxin, and DNA in the recovered protein solution. The use of glycol ethers also allowed exploitation of temperature-change-induced phase splitting behavior to concentrate the desired product. Heating the aqueous EB extract solution to 55 degrees C formed two liquid phases: a glycol ether-rich phase and an aqueous product phase containing the great majority of the product protein. This phase-splitting step yielded an approximate 10-fold reduction in the volume of the initial product solution and a corresponding increase in the product's concentration.

  9. Regulation of cargo-selective endocytosis by dynamin 2 GTPase-activating protein girdin.

    PubMed

    Weng, Liang; Enomoto, Atsushi; Miyoshi, Hiroshi; Takahashi, Kiyofumi; Asai, Naoya; Morone, Nobuhiro; Jiang, Ping; An, Jian; Kato, Takuya; Kuroda, Keisuke; Watanabe, Takashi; Asai, Masato; Ishida-Takagishi, Maki; Murakumo, Yoshiki; Nakashima, Hideki; Kaibuchi, Kozo; Takahashi, Masahide

    2014-09-17

    In clathrin-mediated endocytosis (CME), specificity and selectivity for cargoes are thought to be tightly regulated by cargo-specific adaptors for distinct cellular functions. Here, we show that the actin-binding protein girdin is a regulator of cargo-selective CME. Girdin interacts with dynamin 2, a GTPase that excises endocytic vesicles from the plasma membrane, and functions as its GTPase-activating protein. Interestingly, girdin depletion leads to the defect in clathrin-coated pit formation in the center of cells. Also, we find that girdin differentially interacts with some cargoes, which competitively prevents girdin from interacting with dynamin 2 and confers the cargo selectivity for CME. Therefore, girdin regulates transferrin and E-cadherin endocytosis in the center of cells and their subsequent polarized intracellular localization, but has no effect on integrin and epidermal growth factor receptor endocytosis that occurs at the cell periphery. Our results reveal that girdin regulates selective CME via a mechanism involving dynamin 2, but not by operating as a cargo-specific adaptor.

  10. Protein kinase D regulates positive selection of CD4+ thymocytes through phosphorylation of SHP-1

    PubMed Central

    Ishikawa, Eri; Kosako, Hidetaka; Yasuda, Tomoharu; Ohmuraya, Masaki; Araki, Kimi; Kurosaki, Tomohiro; Saito, Takashi; Yamasaki, Sho

    2016-01-01

    Thymic selection shapes an appropriate T cell antigen receptor (TCR) repertoire during T cell development. Here, we show that a serine/threonine kinase, protein kinase D (PKD), is crucial for thymocyte positive selection. In T cell-specific PKD-deficient (PKD2/PKD3 double-deficient) mice, the generation of CD4 single positive thymocytes is abrogated. This defect is likely caused by attenuated TCR signalling during positive selection and incomplete CD4 lineage specification in PKD-deficient thymocytes; however, TCR-proximal tyrosine phosphorylation is not affected. PKD is activated in CD4+CD8+ double positive (DP) thymocytes on stimulation with positively selecting peptides. By phosphoproteomic analysis, we identify SH2-containing protein tyrosine phosphatase-1 (SHP-1) as a direct substrate of PKD. Substitution of wild-type SHP-1 by phosphorylation-defective mutant (SHP-1S557A) impairs generation of CD4+ thymocytes. These results suggest that the PKD–SHP-1 axis positively regulates TCR signalling to promote CD4+ T cell development. PMID:27670070

  11. The classical arabinogalactan protein AGP18 mediates megaspore selection in Arabidopsis.

    PubMed

    Demesa-Arévalo, Edgar; Vielle-Calzada, Jean-Philippe

    2013-04-01

    Female gametogenesis in most flowering plants depends on the predetermined selection of a single meiotically derived cell, as the three other megaspores die without further division or differentiation. Although in Arabidopsis thaliana the formation of the functional megaspore (FM) is crucial for the establishment of the gametophytic generation, the mechanisms that determine the specification and fate of haploid cells remain unknown. Here, we show that the classical arabinogalactan protein 18 (AGP18) exerts an active regulation over the selection and survival of megaspores in Arabidopsis. During meiosis, AGP18 is expressed in integumentary cells located in the abaxial region of the ovule. Overexpression of AGP18 results in the abnormal maintenance of surviving megaspores that can acquire a FM identity but is not sufficient to induce FM differentiation before meiosis, indicating that AGP18 positively promotes the selection of viable megaspores. We also show that all four meiotically derived cells in the ovule of Arabidopsis are competent to differentiate into a gametic precursor and that the function of AGP18 is important for their selection and viability. Our results suggest an evolutionary role for arabinogalactan proteins in the acquisition of monospory and the developmental plasticity that is intrinsic to sexual reproduction in flowering plants.

  12. Bayesian spatially dependent variable selection for small area health modeling.

    PubMed

    Choi, Jungsoon; Lawson, Andrew B

    2016-06-16

    Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. However, the impact of covariates on health outcomes may change across space and ignoring this behavior in spatial epidemiology may cause the wrong interpretation of the relations. Thus, the development of a statistical framework for spatial variable selection is important to allow for the estimation of the space-varying patterns of covariate effects as well as the early detection of disease over space. In this paper, we develop flexible spatial variable selection approaches to find the spatially-varying subsets of covariates with significant effects. A Bayesian hierarchical latent model framework is applied to account for spatially-varying covariate effects. We present a simulation example to examine the performance of the proposed models with the competing models. We apply our models to a county-level low birth weight incidence dataset in Georgia.

  13. Bayesian nonparametric centered random effects models with variable selection.

    PubMed

    Yang, Mingan

    2013-03-01

    In a linear mixed effects model, it is common practice to assume that the random effects follow a parametric distribution such as a normal distribution with mean zero. However, in the case of variable selection, substantial violation of the normality assumption can potentially impact the subset selection and result in poor interpretation and even incorrect results. In nonparametric random effects models, the random effects generally have a nonzero mean, which causes an identifiability problem for the fixed effects that are paired with the rand