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Sample records for protein model selection

  1. Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

    PubMed Central

    Offman, Marc N; Tournier, Alexander L; Bates, Paul A

    2008-01-01

    Background Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection. Results In the context of an automatic modelling pipeline, we analysed each step separately, revealing several non-intuitive trends and explored a new strategy for protein conformation sampling using Genetic Algorithms (GA). We apply the concept of alternating evolutionary pressure (AEP), i.e. intermediate rounds within the GA runs where unrestrained, linear growth of the model populations is allowed. Conclusion This approach improves the overall performance of the GA by allowing models to overcome local energy barriers. AEP enabled the selection of the best models in 40% of all targets; compared to 25% for a normal GA. PMID:18673557

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

    PubMed Central

    WANG, QINGGUO; SHANG, CHARLES; XU, DONG

    2014-01-01

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

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

    PubMed

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

    2013-10-25

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

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

    PubMed

    Popov, Petr; Grudinin, Sergei

    2015-10-26

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

  5. Selective Precipitation of Proteins.

    PubMed

    Matulis, Daumantas

    2016-01-01

    Selective precipitation of proteins can be used as a bulk method to recover the majority of proteins from a crude lysate, as a selective method to fractionate a subset of proteins from a protein solution, or as a very specific method to recover a single protein of interest from a purification step. This unit describes a number of methods suitable for selective precipitation. In each of the protocols that are outlined, the physical or chemical basis of the precipitation process, the parameters that can be varied for optimization, and the basic steps for developing an optimized precipitation are described. PMID:26836410

  6. Selective binding of proteins on functional nanoparticles via reverse charge parity model: an in vitro study

    NASA Astrophysics Data System (ADS)

    Ghosh, Goutam; Panicker, Lata; Barick, K. C.

    2014-03-01

    The conformation of proteins absorbed on nanoparticles surface plays a crucial role in applications of nanoparticles in biomedicine. The surface protein conformation depends on several factors, namely, nature of protein-nanoparticles interaction, chemical composition of the surface of nanoparticles etc. A model of the electrostatic binding of proteins on charged surface nanoparticles has been proposed earlier (Ghosh et al 2013 Colloids Surf. B 103 267). Also, the irreversible denaturation of the protein conformation due to binding of counterions was reported. In this paper, we have used this model, involving reverse charge parity, to show selective binding of proteins on charged surface iron oxide nanoparticles (IONPs). IONPs were surface functionalized with cetylpyridinium chloride (CPC), cetyl(trimethyl)ammonium bromide (CTAB) and cetylpyridinium iodide (CPI). The effect of counterions (Cl-, Br- and I-) on protein conformation has also been investigated. Several proteins such as α-lactalbumin (ALA), β-lactoglobulin (BLG), ovalbumin (OVA), bovin serum albumin (BSA) and HEWL were chosen for this investigation.

  7. 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

  8. Discovering short linear protein motif based on selective training of profile hidden Markov models.

    PubMed

    Song, Tao; Gu, Hong

    2015-07-21

    Short linear motifs (SLiMs) in proteins are relatively conservative sequence patterns within disordered regions of proteins, typically 3-10 amino acids in length. They play an important role in mediating protein-protein interactions. Discovering SLiMs by computational methods has attracted more and more attention, most of which were based on regular expressions and profiles. In this paper, a de novo motif discovery method was proposed based on profile hidden Markov models (HMMs), which can not only provide the emission probabilities of amino acids in the defined positions of SLiMs, but also model the undefined positions. We adopted the ordered region masking and the relative local conservation (RLC) masking to improve the signal to noise ratio of the query sequences while applying evolutionary weighting to make the important sequences in evolutionary process get more attention by the selective training of profile HMMs. The experimental results show that our method and the profile-based method returned different subsets within a SLiMs dataset, and the performance of the two approaches are equivalent on a more realistic discovery dataset. Profile HMM-based motif discovery methods complement the existing methods and provide another way for SLiMs analysis. PMID:25791288

  9. Selection of optimal variants of Gō-like models of proteins through studies of stretching.

    PubMed

    Sułkowska, Joanna I; Cieplak, Marek

    2008-10-01

    The Gō-like models of proteins are constructed based on the knowledge of the native conformation. However, there are many possible choices of a Hamiltonian for which the ground state coincides with the native state. Here, we propose to use experimental data on protein stretching to determine what choices are most adequate physically. This criterion is motivated by the fact that stretching processes usually start with the native structure, in the vicinity of which the Gō-like models should work the best. Our selection procedure is applied to 62 different versions of the Gō model and is based on 28 proteins. We consider different potentials, contact maps, local stiffness energies, and energy scales--uniform and nonuniform. In the latter case, the strength of the nonuniformity was governed either by specificity or by properties related to positioning of the side groups. Among them is the simplest variant: uniform couplings with no i, i + 2 contacts. This choice also leads to good folding properties in most cases. We elucidate relationship between the local stiffness described by a potential which involves local chirality and the one which involves dihedral and bond angles. The latter stiffness improves folding but there is little difference between them when it comes to stretching. PMID:18567634

  10. Selection of Optimal Variants of Gō-Like Models of Proteins through Studies of Stretching

    PubMed Central

    Sułkowska, Joanna I.; Cieplak, Marek

    2008-01-01

    The Gō-like models of proteins are constructed based on the knowledge of the native conformation. However, there are many possible choices of a Hamiltonian for which the ground state coincides with the native state. Here, we propose to use experimental data on protein stretching to determine what choices are most adequate physically. This criterion is motivated by the fact that stretching processes usually start with the native structure, in the vicinity of which the Gō-like models should work the best. Our selection procedure is applied to 62 different versions of the Gō model and is based on 28 proteins. We consider different potentials, contact maps, local stiffness energies, and energy scales—uniform and nonuniform. In the latter case, the strength of the nonuniformity was governed either by specificity or by properties related to positioning of the side groups. Among them is the simplest variant: uniform couplings with no i, i + 2 contacts. This choice also leads to good folding properties in most cases. We elucidate relationship between the local stiffness described by a potential which involves local chirality and the one which involves dihedral and bond angles. The latter stiffness improves folding but there is little difference between them when it comes to stretching. PMID:18567634

  11. Selection of optimal variants of Go-like models of proteins through studies of stretching

    NASA Astrophysics Data System (ADS)

    Sulkowska, Joanna; Cieplak, Marek

    2009-03-01

    The Go-like models of proteins are constructed based on the knowledge of the native conformation. However, there are many possible choices of a Hamiltonian for which the ground state coincides with the native state. Here, we propose to use experimental data on protein stretching to determine what choices are most adequate physically. This criterion is motivated by the fact that stretching processes usually start with the native structure, in the vicinity of which the Go-like models should work the best. Our selection procedure is applied to 62 different versions of the Go model and is based on 28 proteins. We consider different potentials, contact maps, local stiffness energies, and energy scales -- uniform and non-uniform. In the latter case, the strength of the nonuniformity was governed either by specificity or by properties related to positioning of the side groups. Among them there is the simplest variant: uniform couplings and no i,i+2 contacts. This choice also leads to good folding properties in most cases. We elucidate relationship between the local stiffness described by a potential which involves local chirality and the one which involves dihedral and bond angles. The latter stiffness improves folding but there is little difference between them when it comes to stretching.

  12. Selective activator protein-1 inhibitor T-5224 prevents lymph node metastasis in an oral cancer model.

    PubMed

    Kamide, Daisuke; Yamashita, Taku; Araki, Koji; Tomifuji, Masayuki; Tanaka, Yuya; Tanaka, Shingo; Shiozawa, Shunichi; Shiotani, Akihiro

    2016-05-01

    Activator protein-1 (AP-1) is a transcriptional factor that regulates the expression of various genes associated with tumor invasion and migration. The purpose of our study was to assess the therapeutic effects of a novel selective AP-1 inhibitor, T-5224, in preventing lymph node metastasis in head and neck squamous cell carcinoma (HNSCC) in an orthotopic mouse model. We assessed the effect of T-5224 on HNSCC cell invasion, migration, proliferation, and MMP activity by carrying out an in vitro study using an invasion assay, scratch assay, WST-8 assay, and gelatin zymography. We also observed morphological changes in HNSCC cells by time-lapse microscopy. Furthermore, cervical lymph node metastasis was assessed using an orthotopic tumor model of human oral squamous cell carcinoma cells (HSC-3-M3) injected in the tongue of a BALB/c nude mouse. T-5224 (150 mg/kg) or vehicle was given orally every day for 4 weeks. Animals were killed and assessed for lymph node metastasis by H&E staining of resected lymph nodes. T-5224 significantly inhibited the invasion, migration, and MMP activity of HNSCC cells in a dose-dependent manner; there was no significant influence on cell proliferation. The antimetastatic effect of T-5224 was also confirmed in our animal study. The rate of cervical lymph node metastasis in the model was 40.0% in the T-5224-treated group (n = 30) versus 74.1% in the vehicle-treated group (n = 27; P < 0.05). In conclusion, T-5224 inhibited the invasion and migration of HNSCC cells in vitro, and prevented lymph node metastasis in head and neck cancer in an animal model. PMID:26918517

  13. LiCABEDS II. Modeling of ligand selectivity for G-protein-coupled cannabinoid receptors.

    PubMed

    Ma, Chao; Wang, Lirong; Yang, Peng; Myint, Kyaw Z; Xie, Xiang-Qun

    2013-01-28

    The cannabinoid receptor subtype 2 (CB2) is a promising therapeutic target for blood cancer, pain relief, osteoporosis, and immune system disease. The recent withdrawal of Rimonabant, which targets another closely related cannabinoid receptor (CB1), accentuates the importance of selectivity for the development of CB2 ligands in order to minimize their effects on the CB1 receptor. In our previous study, LiCABEDS (Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps) was reported as a generic ligand classification algorithm for the prediction of categorical molecular properties. Here, we report extension of the application of LiCABEDS to the modeling of cannabinoid ligand selectivity with molecular fingerprints as descriptors. The performance of LiCABEDS was systematically compared with another popular classification algorithm, support vector machine (SVM), according to prediction precision and recall rate. In addition, the examination of LiCABEDS models revealed the difference in structure diversity of CB1 and CB2 selective ligands. The structure determination from data mining could be useful for the design of novel cannabinoid lead compounds. More importantly, the potential of LiCABEDS was demonstrated through successful identification of newly synthesized CB2 selective compounds. PMID:23278450

  14. Protein Structural Model Selection by Combining Consensus and Single Scoring Methods

    PubMed Central

    Zhang, Jingfen; Xu, Dong

    2013-01-01

    Quality assessment (QA) for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT) methods assess each decoy (predicted structural model) based on its structural similarity to all others in a decoy set and has been proved to work well when good decoys are in a majority cluster. Scoring functions evaluate each single decoy based on its structural properties. Both methods have their merits and limitations. In this paper, we present a novel method called PWCom, which consists of two neural networks sequentially to combine CGDT and single model scoring methods such as RW, DDFire and OPUS-Ca. Specifically, for every pair of decoys, the difference of the corresponding feature vectors is input to the first neural network which enables one to predict whether the decoy-pair are significantly different in terms of their GDT scores to the native. If yes, the second neural network is used to decide which one of the two is closer to the native structure. The quality score for each decoy in the pool is based on the number of winning times during the pairwise comparisons. Test results on three benchmark datasets from different model generation methods showed that PWCom significantly improves over consensus GDT and single scoring methods. The QA server (MUFOLD-Server) applying this method in CASP 10 QA category was ranked the second place in terms of Pearson and Spearman correlation performance. PMID:24023923

  15. Selective chemical labeling of proteins.

    PubMed

    Chen, Xi; Wu, Yao-Wen

    2016-06-28

    Over the years, there have been remarkable efforts in the development of selective protein labeling strategies. In this review, we deliver a comprehensive overview of the currently available bioorthogonal and chemoselective reactions. The ability to introduce bioorthogonal handles to proteins is essential to carry out bioorthogonal reactions for protein labeling in living systems. We therefore summarize the techniques that allow for site-specific "installation" of bioorthogonal handles into proteins. We also highlight the biological applications that have been achieved by selective chemical labeling of proteins. PMID:26940577

  16. Selective deuteration of tryptophan and methionine residues in maltose binding protein: a model system for neutron scattering.

    PubMed

    Laux, Valerie; Callow, Phil; Svergun, Dmitri I; Timmins, Peter A; Forsyth, V Trevor; Haertlein, Michael

    2008-07-01

    We describe methods that have been developed within the ILL-EMBL Deuteration Laboratory for the production of maltose binding protein (MBP) that has been selectively labelled either with deuterated tryptophan or deuterated methionine (single labelling), or both (double labelling). MBP is used as an important model system for biophysical studies, and selective labelling can be helpful in the analysis of small-angle neutron scattering (SANS) data, neutron reflection (NR) data, and high-resolution neutron diffraction data. The selective labelling was carried out in E. coli high-cell density cultures using auxotrophic mutants in minimal medium containing the required deuterated precursors. Five types of sample were prepared and studied: (1) unmodified hydrogenated MBP (H-MBP), (2) perdeuterated MBP (D-MBP), (3) singly labelled MBP with the tryptophan residues deuterated (D-trp MBP), (4) singly labelled MBP with methionine residues deuterated (D-met MBP) and (5) doubly labelled MBP with both tryptophan and methionine residues deuterated (D-trp/met MBP). Labelled samples were characterised by size exclusion chromatography, gel electrophoresis, light scattering and mass spectroscopy. Preliminary small-angle neutron scattering (SANS) experiments have also been carried out and show measurable differences between the SANS data recorded for the various labelled analogues. More detailed SANS experiments using these labelled MBP analogues are planned; the degree to which such data could enhance structure determination by SANS is discussed. PMID:18274740

  17. 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

  18. 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.

  19. 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

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

    2016-02-01

    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, Cys(77) and Cys(48) 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

  20. 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.

  1. A new strategy for selective protein cleavage

    SciTech Connect

    Hoyer, D.; Cho, Ho; Schultz, P.G. )

    1990-04-11

    The ability of proteolytic enzymes and chemical reagents to selectively cleave peptides and proteins at defined sequences has greatly facilitated studies of protein structure and function. Unfortunately, only a limited number of selective peptide cleavage agents exist, in contrast to the wide array of selective nucleases available for analyzing and manipulating nucleic acid structure. The development of strategies for generating site-specific peptidases of any defined sequence would greatly facilitate the mapping of protein structural domains, protein sequencing, the generation of semisynthetic proteins, and would likely lead to the development of new therapeutic agents. The authors report here a new approach to the generation of selective protein cleavage agents that is based on oxidative cleavage of the polypeptide backbone.

  2. 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.

  3. 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

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

    PubMed

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

    2016-01-01

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

  5. Short communication: Selecting the most informative mid-infrared spectra wavenumbers to improve the accuracy of prediction models for detailed milk protein content.

    PubMed

    Niero, G; Penasa, M; Gottardo, P; Cassandro, M; De Marchi, M

    2016-03-01

    The objective of this study was to investigate the ability of mid-infrared spectroscopy (MIRS) to predict protein fraction contents of bovine milk samples by applying uninformative variable elimination (UVE) procedure to select the most informative wavenumber variables before partial least squares (PLS) analysis. Reference values (n=114) of protein fractions were measured using reversed-phase HPLC and spectra were acquired through MilkoScan FT6000 (Foss Electric A/S, Hillerød, Denmark). Prediction models were built using the full data set and tested with a leave-one-out cross-validation. Compared with MIRS models developed using standard PLS, the UVE procedure reduced the number of wavenumber variables to be analyzed through PLS regression and improved the accuracy of prediction by 6.0 to 66.7%. Good predictions were obtained for total protein, total casein (CN), and α-CN, which included αS1- and αS2-CN; moderately accurate predictions were observed for κ-CN and total whey protein; and unsatisfactory results were obtained for β-CN, α-lactalbumin, and β-lactoglobulin. Results indicated that UVE combined with PLS is a valid approach to enhance the accuracy of MIRS prediction models for milk protein fractions. PMID:26774721

  6. 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

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

    PubMed

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

    2015-07-01

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

  8. 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

  9. 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.

  10. Selective memory generalization by spatial patterning of protein synthesis

    PubMed Central

    O’Donnell, Cian; Sejnowski, Terrence J.

    2014-01-01

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

  11. Principles of selective inactivation of a viral genome. Comparative kinetic study of modification of the viral RNA and model protein with oligoaziridines.

    PubMed

    Tsvetkova, E A; Nepomnyaschaya, N M

    2001-08-01

    Comparative kinetic analysis of inactivation of bacteriophage MS2 infectivity and aminoalkylation of a model protein (trypsin inhibitor) with oligoaziridines was performed in order to evaluate the selectivity of viral RNA modification with oligocationic reagents. The transition from ethyleneimine monomer to di-, tri-, and tetramer leads to a sharp increase in the rate constant of infectivity inactivation, whereas the rate constant of protein modification changes insignificantly. The selectivity coefficient of the phage RNA aminoalkylation relative to trypsin inhibitor modification increases in this series by more than an order of magnitude. This effect is probably associated with the strengthening of the reagent binding to the nucleic acid, which implies a reaction mechanism that involves the formation of a reactive intermediate. The latter might be an electrostatic complex of the oligocationic reagent and RNA, the only polyanion in the virion. A pronounced decrease in the rate constant of infectivity inactivation in the presence of multiply charged anions (in phosphate buffer) and a biogenic polyamine (spermine) favors this hypothesis. Increasing the reaction temperature increases the rate constant of infectivity inactivation and decreases selectivity of the viral RNA modification. PMID:11566057

  12. 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

  13. 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.

  14. Human telomeric proteins occupy selective interstitial sites

    PubMed Central

    Yang, Dong; Xiong, Yuanyan; Kim, Hyeung; He, Quanyuan; Li, Yumei; Chen, Rui; Songyang, Zhou

    2011-01-01

    Human telomeres are bound and protected by protein complexes assembled around the six core telomeric proteins RAP1, TRF1, TRF2, TIN2, TPP1, and POT1. The function of these proteins on telomeres has been studied extensively. Recently, increasing evidence has suggested possible roles for these proteins outside of telomeres. However, the non-canonical (extra-telomeric) function of human telomeric proteins remains poorly understood. To this end, we systematically investigated the binding sites of telomeric proteins along human chromosomes, by performing whole-genome chromatin immunoprecipitation (ChIP) for RAP1 and TRF2. ChIP sequencing (ChIP-seq) revealed that RAP1 and TRF2 could be found on a small number of interstitial sites, including regions that are proximal to genes. Some of these binding sites contain short telomere repeats, suggesting that telomeric proteins could directly bind to interstitial sites. Interestingly, only a small fraction of the available interstitial telomere repeat-containing regions were occupied by RAP1 and TRF2. Ectopically expressed TRF2 was able to occupy additional interstitial telomere repeat sites, suggesting that protein concentration may dictate the selective targeting of telomeric proteins to interstitial sites. Reducing RAP1 and TRF2 expression by RNA interference led to altered transcription of RAP1- and TRF2-targeted genes. Our results indicate that human telomeric proteins could occupy a limited number of interstitial sites and regulate gene transcription. PMID:21423278

  15. Homology modeling of major intrinsic proteins in rice, maize and Arabidopsis: comparative analysis of transmembrane helix association and aromatic/arginine selectivity filters

    PubMed Central

    Bansal, Anjali; Sankararamakrishnan, Ramasubbu

    2007-01-01

    Background The major intrinsic proteins (MIPs) facilitate the transport of water and neutral solutes across the lipid bilayers. Plant MIPs are believed to be important in cell division and expansion and in water transport properties in response to environmental conditions. More than 30 MIP sequences have been identified in Arabidopsis thaliana, maize and rice. Plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), Nod26-like intrinsic protein (NIPs) and small and basic intrinsic proteins (SIPs) are subfamilies of plant MIPs. Despite sequence diversity, all the experimentally determined structures belonging to the MIP superfamily have the same "hour-glass" fold. Results We have structurally characterized 39 rice and 31 maize MIPs and compared them with that of Arabidopsis. Homology models of 105 MIPs from all three plant species were built. Structure-based sequence alignments were generated and the residues in the helix-helix interfaces were analyzed. Small residues (Gly/Ala/Ser/Thr) are found to be highly conserved as a group in the helix-helix interface of MIP structures. Individual families sometimes prefer one or another of the residues from this group. The narrow aromatic/arginine (ar/R) selectivity filter in MIPs has been shown to provide an important constriction for solute permeability. Ar/R regions were analyzed and compared between the three plant species. Seventeen TIP, NIP and SIP members from rice and maize have ar/R signatures that are not found in Arabidopsis. A subgroup of rice and maize NIPs has small residues in three of the four positions in the ar/R tetrad, resulting in a wider constriction. These MIP members could transport larger solute molecules. Conclusion Small residues are group-conserved in the helix-helix interface of MIP structures and they seem to be important for close helix-helix interactions. Such conservation might help to preserve the hour-glass fold in MIP structures. Analysis and comparison of ar

  16. An Intriguing Shift Occurs in the Novel Protein Phosphatase 1 Binding Partner, TCTEX1D4: Evidence of Positive Selection in a Pika Model

    PubMed Central

    Korrodi-Gregório, Luís; Margarida Lopes, Ana; Esteves, Sara L. C.; Afonso, Sandra; Lemos de Matos, Ana; Lissovsky, Andrey A.; da Cruz e Silva, Odete A. B.; Esteves, Pedro José; Fardilha, Margarida

    2013-01-01

    T-complex testis expressed protein 1 domain containing 4 (TCTEX1D4) contains the canonical phosphoprotein phosphatase 1 (PPP1) binding motif, composed by the amino acid sequence RVSF. We identified and validated the binding of TCTEX1D4 to PPP1 and demonstrated that indeed this protein is a novel PPP1 interacting protein. Analyses of twenty-one mammalian species available in public databases and seven Lagomorpha sequences obtained in this work showed that the PPP1 binding motif 90RVSF93 is present in all of them and is flanked by a palindromic sequence, PLGS, except in three species of pikas (Ochotona princeps, O. dauurica and O. pusilla). Furthermore, for the Ochotona species an extra glycosylation site, motif 96NLS98, and the loss of the palindromic sequence were observed. Comparison with other lagomorphs suggests that this event happened before the Ochotona radiation. The dN/dS for the sequence region comprising the PPP1 binding motif and the flanking palindrome highly supports the hypothesis that for Ochotona species this region has been evolving under positive selection. In addition, mutational screening shows that the ability of pikas TCTEX1D4 to bind to PPP1 is maintained, although the PPP1 binding motif is disrupted, and the N- and C-terminal surrounding residues are also abrogated. These observations suggest pika as an ideal model to study novel PPP1 complexes regulatory mechanisms. PMID:24130861

  17. 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

  18. 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…

  19. A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

    PubMed Central

    2011-01-01

    Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific

  20. Cytosolic Selection Systems To Study Protein Stability

    PubMed Central

    Malik, Ajamaluddin; Mueller-Schickert, Antje

    2014-01-01

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

  1. 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…

  2. 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

    2015-01-01

    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. PMID:25739082

  3. The Anti-TNF-α Antibody Infliximab Inhibits the Expression of Fat-Transporter-Protein FAT/CD36 in a Selective Hepatic-Radiation Mouse Model

    PubMed Central

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

    2015-01-01

    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. PMID:25739082

  4. Evidence of Conformational Selection Driving the Formation of Ligand Binding Sites in Protein-Protein Interfaces

    PubMed Central

    Bohnuud, Tanggis; Kozakov, Dima; Vajda, Sandor

    2014-01-01

    Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small “probe” molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although

  5. Modeling Mercury in Proteins.

    PubMed

    Parks, J M; Smith, J C

    2016-01-01

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

  6. Lattice Tube Model of Proteins

    NASA Astrophysics Data System (ADS)

    Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos

    2004-11-01

    We present a new lattice model for proteins that incorporates a tubelike anisotropy by introducing a preference for mutually parallel alignments in the conformations. The model is demonstrated to capture many aspects of real proteins.

  7. Contingency and entrenchment in protein evolution under purifying selection

    PubMed Central

    Shah, Premal; McCandlish, David M.; Plotkin, Joshua B.

    2015-01-01

    The phenotypic effect of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as epistasis. Epistasis can profoundly influence the process of evolution in populations and shape the patterns of protein divergence across species. Whereas epistasis between adaptive substitutions has been studied extensively, relatively little is known about epistasis under purifying selection. Here we use computational models of thermodynamic stability in a ligand-binding protein to explore the structure of epistasis in simulations of protein sequence evolution. Even though the predicted effects on stability of random mutations are almost completely additive, the mutations that fix under purifying selection are enriched for epistasis. In particular, the mutations that fix are contingent on previous substitutions: Although nearly neutral at their time of fixation, these mutations would be deleterious in the absence of preceding substitutions. Conversely, substitutions under purifying selection are subsequently entrenched by epistasis with later substitutions: They become increasingly deleterious to revert over time. Our results imply that, even under purifying selection, protein sequence evolution is often contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the ancestral background. PMID:26056312

  8. CRK proteins selectively regulate T cell migration into inflamed tissues

    PubMed Central

    Huang, Yanping; Clarke, Fiona; Karimi, Mobin; Roy, Nathan H.; Williamson, Edward K.; Okumura, Mariko; Mochizuki, Kazuhiro; Chen, Emily J.H.; Park, Tae-Ju; Debes, Gudrun F.; Zhang, Yi; Curran, Tom; Kambayashi, Taku; Burkhardt, Janis K.

    2015-01-01

    Effector T cell migration into inflamed sites greatly exacerbates tissue destruction and disease severity in inflammatory diseases, including graft-versus-host disease (GVHD). T cell migration into such sites depends heavily on regulated adhesion and migration, but the signaling pathways that coordinate these functions downstream of chemokine receptors are largely unknown. Using conditional knockout mice, we found that T cells lacking the adaptor proteins CRK and CRK-like (CRKL) exhibit reduced integrin-dependent adhesion, chemotaxis, and diapedesis. Moreover, these two closely related proteins exhibited substantial functional redundancy, as ectopic expression of either protein rescued defects in T cells lacking both CRK and CRKL. We determined that CRK proteins coordinate with the RAP guanine nucleotide exchange factor C3G and the adhesion docking molecule CASL to activate the integrin regulatory GTPase RAP1. CRK proteins were required for effector T cell trafficking into sites of inflammation, but not for migration to lymphoid organs. In a murine bone marrow transplantation model, the differential migration of CRK/CRKL-deficient T cells resulted in efficient graft-versus-leukemia responses with minimal GVHD. Together, the results from our studies show that CRK family proteins selectively regulate T cell adhesion and migration at effector sites and suggest that these proteins have potential as therapeutic targets for preventing GVHD. PMID:25621495

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

    PubMed

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

    2016-03-29

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

  10. Histopathologic characterization of the BTBR mouse model of autistic-like behavior reveals selective changes in neurodevelopmental proteins and adult hippocampal neurogenesis

    PubMed Central

    2011-01-01

    Background The inbred mouse strain BTBR T+ tf/J (BTBR) exhibits behavioral deficits that mimic the core deficits of autism. Neuroanatomically, the BTBR strain is also characterized by a complete absence of the corpus callosum. The goal of this study was to identify novel molecular and cellular changes in the BTBR mouse, focusing on neuronal, synaptic, glial and plasticity markers in the limbic system as a model for identifying putative molecular and cellular substrates associated with autistic behaviors. Methods Forebrains of 8 to 10-week-old male BTBR and age-matched C57Bl/6J control mice were evaluated by immunohistochemistry using free-floating and paraffin embedded sections. Twenty antibodies directed against antigens specific to neurons, synapses and glia were used. Nissl, Timm and acetylcholinesterase (AchE) stains were performed to assess cytoarchitecture, mossy fibers and cholinergic fiber density, respectively. In the hippocampus, quantitative stereological estimates for the mitotic marker bromodeoxyuridine (BrdU) were performed to determine hippocampal progenitor proliferation, survival and differentiation, and brain-derived neurotrophic factor (BDNF) mRNA was quantified by in situ hybridization. Quantitative image analysis was performed for NG2, doublecortin (DCX), NeuroD, GAD67 and Poly-Sialic Acid Neural Cell Adhesion Molecule (PSA-NCAM). Results In midline structures including the region of the absent corpus callosum of BTBR mice, the myelin markers 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase) and myelin basic protein (MBP) were reduced, and the oligodendrocyte precursor NG2 was increased. MBP and CNPase were expressed in small ectopic white matter bundles within the cingulate cortex. Microglia and astrocytes showed no evidence of gliosis, yet orientations of glial fibers were altered in specific white-matter areas. In the hippocampus, evidence of reduced neurogenesis included significant reductions in the number of doublecortin, PSA-NCAM and

  11. Comparative Protein Structure Modeling Using Modeller

    PubMed Central

    Eswar, Narayanan; Marti-Renom, Marc A.; Madhusudhan, M.S.; Eramian, David; Shen, Min-yi; Pieper, Ursula

    2014-01-01

    Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. PMID:18428767

  12. 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…

  13. 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…

  14. 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.

  15. Posterior Predictive Bayesian Phylogenetic Model Selection

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2012-01-01

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

  17. Functional properties of select edible oilseed proteins.

    PubMed

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

    2010-05-12

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

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

    PubMed

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

    2013-10-01

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

  19. Entropic criterion for model selection

    NASA Astrophysics Data System (ADS)

    Tseng, Chih-Yuan

    2006-10-01

    Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback-Leibler distance or relative entropy as a selection criterion. Yet that will raise two questions, why use this criterion and are there any other criteria. Besides, conventional approaches require a reference prior, which is usually difficult to get. Following the logic of inductive inference proposed by Caticha [Relative entropy and inductive inference, in: G. Erickson, Y. Zhai (Eds.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering, AIP Conference Proceedings, vol. 707, 2004 (available from arXiv.org/abs/physics/0311093)], we show relative entropy to be a unique criterion, which requires no prior information and can be applied to different fields. We examine this criterion by considering a physical problem, simple fluids, and results are promising.

  20. 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.

  1. Candida albicans binds to saliva proteins selectively adsorbed to silicone.

    PubMed

    Holmes, Ann R; van der Wielen, Pauline; Cannon, Richard D; Ruske, Dean; Dawes, Patrick

    2006-10-01

    Explanted voice prostheses obtained from 5 patients at the time of prosthesis replacement were consistently colonized by yeast, in particular Candida albicans. A simple, reproducible, in vitro model of C. albicans adherence to saliva-coated voice prosthesis silicone was developed. Whole saliva promoted adherence of C. albicans to silicone in a dose-dependent manner. Saliva rinses from voice prosthesis patients also promoted binding of C. albicans to silicone in vitro (mean adherence 14.9% +/- 2.8% of input C. albicans cells). This was significantly higher than C. albicans adherence to silicone in the absence of saliva (P < .001) or adherence promoted by saliva rinses from healthy volunteers (P < .005). Polyacrylamide gel electrophoresis analysis and a blot overlay adherence assay revealed that certain salivary proteins were selectively adsorbed to silicone and that C. albicans yeast cells adhered specifically to the adsorbed salivary proteins. PMID:16997116

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

    PubMed

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

    2016-01-01

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

  3. 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

  4. 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. PMID:22084296

  5. Selection for genes encoding secreted proteins and receptors.

    PubMed Central

    Klein, R D; Gu, Q; Goddard, A; Rosenthal, A

    1996-01-01

    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. Images Fig. 1 PMID:8692953

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

    PubMed

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

    2016-08-31

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

  7. 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.

  8. Selective characterization of proteins on nanoscale concave surfaces.

    PubMed

    Qian, Xi; Rameshbabu, Utthara; Dordick, Jonathan S; Siegel, Richard W

    2016-01-01

    Nanoscale curvature plays a critical role in nanostructure-biomolecule interactions, yet the understanding of such effects in concave nanostructures is still very limited. Because concave nanostructures usually possess convex surface curvatures as well, it is challenging to selectively study the proteins on concave surfaces alone. In this work, we have developed a novel and facile method to address this issue by desorbing proteins on the external surfaces of hollow gold nanocages (AuNG), allowing the selective characterization of retained proteins immobilized on their internal concave surfaces. The selective desorption of proteins was achieved via varying the solution ionic strength, and was demonstrated by both calculation and experimental comparison with non-hollow nanoparticles. This method has created a new platform for the discrete observation of proteins adsorbed inside AuNG hollow cores, and this work suggests an expanded biomedical application space for hollow nanomaterials. PMID:26513422

  9. 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

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

    PubMed

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

    2015-08-18

    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

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

    PubMed

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

    2012-03-01

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

  12. Selective sorting of alpha-granule proteins

    PubMed Central

    Italiano, J.E.; Battinelli, E. M.

    2010-01-01

    Summary 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. The majority of this vast array of secreted proteins is 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. PMID:19630794

  13. 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...

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

    PubMed

    Rainer, Matthias; Bonn, Günther K

    2015-01-01

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

  15. Modeling electrostatic effects in proteins.

    PubMed

    Warshel, Arieh; Sharma, Pankaz K; Kato, Mitsunori; Parson, William W

    2006-11-01

    Electrostatic energies provide what is perhaps the most effective tool for structure-function correlation of biological molecules. This review considers the current state of simulations of electrostatic energies in macromolecules as well as the early developments of this field. We focus on the relationship between microscopic and macroscopic models, considering the convergence problems of the microscopic models and the fact that the dielectric 'constants' in semimacroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering a wide range of functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding and protein stability. We conclude by pointing out that, despite the current problems and the significant misunderstandings in the field, there is an overall progress that should lead eventually to quantitative descriptions of electrostatic effects in proteins and thus to quantitative descriptions of the function of proteins. PMID:17049320

  16. Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

    PubMed Central

    Chakraborty, Sandip

    2016-01-01

    Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins) are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons) tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes' adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another. PMID:27119079

  17. Absolute Quantification of Selected Proteins in the Human Osteoarthritic Secretome

    PubMed Central

    Peffers, Mandy J.; Beynon, Robert J.; Clegg, Peter D.

    2013-01-01

    Osteoarthritis (OA) is characterized by a loss of extracellular matrix which is driven by catabolic cytokines. Proteomic analysis of the OA cartilage secretome enables the global study of secreted proteins. These are an important class of molecules with roles in numerous pathological mechanisms. Although cartilage studies have identified profiles of secreted proteins, quantitative proteomics techniques have been implemented that would enable further biological questions to be addressed. To overcome this limitation, we used the secretome from human OA cartilage explants stimulated with IL-1β and compared proteins released into the media using a label-free LC-MS/MS-based strategy. We employed QconCAT technology to quantify specific proteins using selected reaction monitoring. A total of 252 proteins were identified, nine were differentially expressed by IL-1 β stimulation. Selected protein candidates were quantified in absolute amounts using QconCAT. These findings confirmed a significant reduction in TIMP-1 in the secretome following IL-1β stimulation. Label-free and QconCAT analysis produced equivocal results indicating no effect of cytokine stimulation on aggrecan, cartilage oligomeric matrix protein, fibromodulin, matrix metalloproteinases 1 and 3 or plasminogen release. This study enabled comparative protein profiling and absolute quantification of proteins involved in molecular pathways pertinent to understanding the pathogenesis of OA. PMID:24132152

  18. A Logistic Regression Model for Personnel Selection.

    ERIC Educational Resources Information Center

    Raju, Nambury S.; And Others

    1991-01-01

    A two-parameter logistic regression model for personnel selection is proposed. The model was tested with a database of 84,808 military enlistees. The probability of job success was related directly to trait levels, addressing such topics as selection, validity generalization, employee classification, selection bias, and utility-based fair…

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

    PubMed

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

    2016-04-15

    Herein, a binding-regulated click ligation (BRCL) strategy for endowing selective detection of proteins is developed with the incorporation of small-molecule ligand and clickable DNA probes. The fundamental principle underlying the strategy is the regulating capability of specific protein-ligand binding against the ligation between clickable DNA probes, which could efficiently combine the detection of particular protein with enormous DNA-based sensing technologies. In this work, the feasibly of the BRCL strategy is first verified through agarose gel electrophoresis and electrochemical impedance spectroscopy measurements, and then confirmed by transferring it to a nanomaterial-assisted fluorescence assay. Significantly, the BRCL strategy-based assay is able to respond to target protein with desirable selectivity, attributing to the specific recognition between small-molecule ligand and its target. Further experiments validate the general applicability of the sensing method by tailoring the ligand toward different proteins (i.e., avidin and folate receptor), and demonstrate its usability in complex biological samples. To our knowledge, this work pioneers the practice of click chemistry in probing specific small-molecule ligand-protein binding, and therefore may pave a new way for selective detection of proteins. PMID:26599478

  20. Site-selective protein immobilization by covalent modification of GST fusion proteins.

    PubMed

    Zhou, Yiqing; Guo, Tianlin; Tang, Guanghui; Wu, Hui; Wong, Nai-Kei; Pan, Zhengying

    2014-11-19

    The immobilization of functional proteins onto solid supports using affinity tags is an attractive approach in recent development of protein microarray technologies. Among the commonly used fusion protein tags, glutathione S-transferase (GST) proteins have been indispensable tools for protein-protein interaction studies and have extensive applications in recombinant protein purification and reversible protein immobilization. Here, by utilizing pyrimidine-based small-molecule probes with a sulfonyl fluoride reactive group, we report a novel and general approach for site-selective immobilization of Schistosoma japonicum GST (sjGST) fusion proteins through irreversible and specific covalent modification of the tyrosine-111 residue of the sjGST tag. As demonstrated by sjGST-tagged eGFP and sjGST-tagged kinase activity assays, this immobilization approach offers the advantages of high immobilization efficiency and excellent retention of protein structure and activity. PMID:25340706

  1. 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.

  2. Arginine selective reagents for ligation to peptides and proteins.

    PubMed

    Thompson, Darren A; Ng, Raymond; Dawson, Philip E

    2016-05-01

    A new class of arginine-specific bioconjugation reagents for protein labeling has been developed. This method utilizes a triazolyl-phenylglyoxal group on the probe molecule that reacts selectively with the guandinyl group of Arg residues in a protein or peptide. The reaction proceeds in neutral to basic bicarbonate buffers and is selective for arginine residues in peptides and folded proteins. Importantly, the triazolyl-phenylglyoxal group can be introduced into complex molecules containing alkyne groups using CuAAC chemistry, providing a robust approach for the generation of phenylglyoxal reactive groups into molecules to be covalently attached onto the surface of proteins. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd. PMID:27005702

  3. RCAN 1 and 3 proteins regulate thymic positive selection.

    PubMed

    Serrano-Candelas, Eva; Alemán-Muench, Germán; Solé-Sánchez, Sònia; Aubareda, Anna; Martínez-Høyer, Sergio; Adán, Jaume; Aranguren-Ibáñez, Álvaro; Pritchard, Melanie A; Soldevila, Gloria; Pérez-Riba, Mercè

    2015-05-01

    Cooperation between calcineurin (CN)-NFATc and RAF-MEK-ERK signaling pathways is essential in thymocyte positive selection. It is known that the Regulators of Calcineurin (RCAN) proteins can act either facilitating or suppressing CN-dependent signaling events. Here, we show that RCAN genes are expressed in lymphoid tissues, and address the role of RCAN proteins in T cell development. Overexpression of human RCAN3 and RCAN1 can modulate T cell development by increasing positive selection-related surface markers, as well as the "Erk(hi) competence state" in double positive thymocytes, a characteristic molecular signature of positive selection, without affecting CN activity. We also found that RCAN1/3 interact with RAF kinases and CN in a non-exclusive manner. Our data suggests that the balance of RCAN interactions with CN and/or RAF kinases may influence T cell positive selection. PMID:25783055

  4. Selection on the Drosophila seminal fluid protein Acp62F

    PubMed Central

    Wong, Alex; Rundle, Howard

    2013-01-01

    Sperm competition and sexual conflict are thought to underlie the rapid evolution of reproductive proteins in many taxa. While comparative data are generally consistent with these hypotheses, few manipulative tests have been conducted and those that have provided contradictory results in some cases. Here, we use both comparative and experimental techniques to investigate the evolution of the Drosophila melanogaster seminal fluid protein Acp62F, a protease inhibitor for which extensive functional tests have yielded ambiguous results. Using between-species sequence comparisons, we show that Acp62F has been subject to recurrent positive selection. In addition, we experimentally evolved populations polymorphic for an Acp62F null allele over eight generations, manipulating the opportunities for natural and sexual selection. We found that the Acp62F null allele increased in frequency in the presence of natural selection, with no effect of sexual selection. PMID:23919141

  5. 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.

  6. 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

  7. Zeolite Nanoparticles for Selective Sorption of Plasma Proteins.

    PubMed

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

    2015-01-01

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

  8. 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.

  9. 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…

  10. Quantification of Protein-Lipid Selectivity using FRET: Application to the M13 Major Coat Protein

    PubMed Central

    Fernandes, Fábio; Loura, Luís M. S.; Koehorst, Rob; Spruijt, Ruud B.; Hemminga, Marcus A.; Fedorov, Alexander; Prieto, Manuel

    2004-01-01

    Quantification of lipid selectivity by membrane proteins has been previously addressed mainly from electron spin resonance studies. We present here a new methodology for quantification of protein-lipid selectivity based on fluorescence resonance energy transfer. A mutant of M13 major coat protein was labeled with 7-diethylamino-3((4′iodoacetyl)amino)phenyl-4-methylcoumarin to be used as the donor in energy transfer studies. Phospholipids labeled with N-(7-nitro-2-1,3-benzoxadiazol-4-yl) were selected as the acceptors. The dependence of protein-lipid selectivity on both hydrophobic mismatch and headgroup family was determined. M13 major coat protein exhibited larger selectivity toward phospholipids which allow for a better hydrophobic matching. Increased selectivity was also observed for anionic phospholipids and the relative association constants agreed with the ones already presented in the literature and obtained through electron spin resonance studies. This result led us to conclude that fluorescence resonance energy transfer is a promising methodology in protein-lipid selectivity studies. PMID:15240469

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

    PubMed

    Tinberg, Christine E; Khare, Sagar D

    2016-01-01

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

  12. Evolution of Metal Selectivity in Templated Protein Interfaces

    PubMed Central

    Brodin, Jeffrey D.; Medina-Morales, Annette; Ni, Thomas; Salgado, Eric N.; Ambroggio, Xavier I.; Tezcan, F. Akif

    2010-01-01

    Selective binding by metalloproteins to their cognate metal ions is essential to cellular survival. How proteins originally acquired the ability to selectively bind metals and evolved a diverse array of metal-centered functions despite the availability of only a few metal-coordinating functionalities remains an open question. Using a rational design approach (Metal-Templated Interface Redesign), we describe the transformation of a monomeric electron transfer protein, cytochrome cb562, into a tetrameric assembly (C96RIDC-1) that stably and selectively binds Zn2+, and displays a metal-dependent conformational change reminiscent of a signaling protein. A thorough analysis of the metal binding properties of C96RIDC-14 reveals that it can also stably harbor other divalent metals with affinities that rival (Ni2+) or even exceed (Cu2+) those of Zn2+ on a per site basis. Nevertheless, this analysis suggests that our templating strategy also introduces an increased bias towards binding a higher number of Zn2+ ions (4 high affinity sites) versus Cu2+ or Ni2+ (2 high affinity sites), ultimately leading to the exclusive selectivity of C96RIDC-14 for Zn2 over those ions. More generally, our results indicate that an initial metal-driven nucleation event followed by the formation of a stable protein architecture around the metal provides a straightforward path for generating structural and functional diversity. PMID:20515031

  13. A novel method for protein-protein interaction site prediction using phylogenetic substitution models

    PubMed Central

    La, David; Kihara, Daisuke

    2011-01-01

    Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site prediction. Here, we present a phylogenetic framework to capture critical sequence variations that favor the selection of residues essential for protein-protein binding. Through the comprehensive analysis of diverse protein families, we show that protein binding interfaces exhibit distinct amino acid substitution as compared with other surface residues. Based on this analysis, we have developed a novel method, BindML, which utilizes the substitution models to predict protein-protein binding sites of protein with unknown interacting partners. BindML estimates the likelihood that a phylogenetic tree of a local surface region in a query protein structure follows the substitution patterns of protein binding interface and non-binding surfaces. BindML is shown to perform well compared to alternative methods for protein binding interface prediction. The methodology developed in this study is very versatile in the sense that it can be generally applied for predicting other types of functional sites, such as DNA, RNA, and membrane binding sites in proteins. PMID:21989996

  14. Model Selection Indices for Polytomous Items

    ERIC Educational Resources Information Center

    Kang, Taehoon; Cohen, Allan S.; Sung, Hyun-Jung

    2009-01-01

    This study examines the utility of four indices for use in model selection with nested and nonnested polytomous item response theory (IRT) models: a cross-validation index and three information-based indices. Four commonly used polytomous IRT models are considered: the graded response model, the generalized partial credit model, the partial credit…

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

    PubMed

    Wang, Qingguo; Shang, Yi; Xu, Dong

    2011-01-01

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

  16. The Coalescent Process in Models with Selection

    PubMed Central

    Kaplan, N. L.; Darden, T.; Hudson, R. R.

    1988-01-01

    Statistical properties of the process describing the genealogical history of a random sample of genes are obtained for a class of population genetics models with selection. For models with selection, in contrast to models without selection, the distribution of this process, the coalescent process, depends on the distribution of the frequencies of alleles in the ancestral generations. If the ancestral frequency process can be approximated by a diffusion, then the mean and the variance of the number of segregating sites due to selectively neutral mutations in random samples can be numerically calculated. The calculations are greatly simplified if the frequencies of the alleles are tightly regulated. If the mutation rates between alleles maintained by balancing selection are low, then the number of selectively neutral segregating sites in a random sample of genes is expected to substantially exceed the number predicted under a neutral model. PMID:3066685

  17. Model selection for anomaly detection

    NASA Astrophysics Data System (ADS)

    Burnaev, E.; Erofeev, P.; Smolyakov, D.

    2015-12-01

    Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion detection, etc. Performance of an anomaly detection algorithm crucially depends on a kernel, used to measure similarity in a feature space. The standard approaches (e.g. cross-validation) for kernel selection, used in two-class classification problems, can not be used directly due to the specific nature of a data (absence of a second, abnormal, class data). In this paper we generalize several kernel selection methods from binary-class case to the case of one-class classification and perform extensive comparison of these approaches using both synthetic and real-world data.

  18. 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…

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

    PubMed

    Nguyen, Peter Q; Silberg, Jonathan J

    2010-07-01

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

  20. 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

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

    PubMed Central

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

    2016-01-01

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

  2. 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.

  3. 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

  4. Selectivity by Small-Molecule Inhibitors of Protein Interactions Can Be Driven by Protein Surface Fluctuations

    PubMed Central

    Johnson, David K.; Karanicolas, John

    2015-01-01

    Small-molecules that inhibit interactions between specific pairs of proteins have long represented a promising avenue for therapeutic intervention in a variety of settings. Structural studies have shown that in many cases, the inhibitor-bound protein adopts a conformation that is distinct from its unbound and its protein-bound conformations. This plasticity of the protein surface presents a major challenge in predicting which members of a protein family will be inhibited by a given ligand. Here, we use biased simulations of Bcl-2-family proteins to generate ensembles of low-energy conformations that contain surface pockets suitable for small molecule binding. We find that the resulting conformational ensembles include surface pockets that mimic those observed in inhibitor-bound crystal structures. Next, we find that the ensembles generated using different members of this protein family are overlapping but distinct, and that the activity of a given compound against a particular family member (ligand selectivity) can be predicted from whether the corresponding ensemble samples a complementary surface pocket. Finally, we find that each ensemble includes certain surface pockets that are not shared by any other family member: while no inhibitors have yet been identified to take advantage of these pockets, we expect that chemical scaffolds complementing these “distinct” pockets will prove highly selective for their targets. The opportunity to achieve target selectivity within a protein family by exploiting differences in surface fluctuations represents a new paradigm that may facilitate design of family-selective small-molecule inhibitors of protein-protein interactions. PMID:25706586

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

    PubMed

    Tastan Bishop, Ozlem; Kroon, Matthys

    2011-12-01

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

  6. Modeling Enzymatic Reactions in Proteins.

    NASA Astrophysics Data System (ADS)

    Friesner, Richard

    2007-03-01

    We will discuss application of our density functional (DFT)-based QM/MM methodology to modeling a variety of protein active sites, including methane monooxygenase, myoglobin, and cytochrome P450. In addition to the calculation of intermediates, transition states, and rate constants, we will discuss modeling of reactions requiring protein conformational changes. Our methodology reliably achieves small errors as a result of imposition of the QM/MM boundary. However, the accuracy of DFT methods can vary significantly with the type of system under study. We will discuss a novel approach to the reduction of errors in gradient corrected and hybrid DFT functionals, using empirical localized orbital corrections (DFT-LOC), which addresses this problem effectively. For example, the mean unsigned error in atomization energies for the G3 data set using the B3LYP-LOC model is 0.8 kcal/mole, as compared with 4.8 kcal/mole for B3LYP and 1.0 kcal/mole for G3 theory.

  7. Protein models: The Grand Challenge of protein docking

    PubMed Central

    Anishchenko, Ivan; Kundrotas, Petras J.; Tuzikov, Alexander V.; Vakser, Ilya A.

    2016-01-01

    Characterization of life processes at the molecular level requires structural details of protein–protein interactions (PPIs). The number of experimentally determined protein structures accounts only for a fraction of known proteins. This gap has to be bridged by modeling, typically using experimentally determined structures as templates to model related proteins. The fraction of experimentally determined PPI structures is even smaller than that for the individual proteins, due to a larger number of interactions than the number of individual proteins, and a greater difficulty of crystallizing protein–protein complexes. The approaches to structural modeling of PPI (docking) often have to rely on modeled structures of the interactors, especially in the case of large PPI networks. Structures of modeled proteins are typically less accurate than the ones determined by X-ray crystallography or nuclear magnetic resonance. Thus the utility of approaches to dock these structures should be assessed by thorough benchmarking, specifically designed for protein models. To be credible, such benchmarking has to be based on carefully curated sets of structures with levels of distortion typical for modeled proteins. This article presents such a suite of models built for the benchmark set of the X-ray structures from the Dockground resource (http://dockground.bioinformatics.ku.edu) by a combination of homology modeling and Nudged Elastic Band method. For each monomer, six models were generated with predefined Cα root mean square deviation from the native structure (1, 2, . . ., 6 Å). The sets and the accompanying data provide a comprehensive resource for the development of docking methodology for modeled proteins. PMID:23934791

  8. Tyrosine-selective protein alkylation using pi-allylpalladium complexes.

    PubMed

    Tilley, S David; Francis, Matthew B

    2006-02-01

    A new protein modification reaction has been developed based on a palladium-catalyzed allylic alkylation of tyrosine residues. This technique employs electrophilic pi-allyl intermediates derived from allylic acetate and carbamate precursors and can be used to modify proteins in aqueous solution at room temperature. To facilitate the detection of modified proteins using SDS-PAGE analysis, a fluorescent allyl acetate was synthesized and coupled to chymotrypsinogen A and bacteriophage MS2. The tyrosine selectivity of the reaction was confirmed through trypsin digest analysis. The utility of the reaction was demonstrated by using taurine-derived carbamates as water solubilizing groups that are cleaved upon protein functionalization. This solubility switching technique was used to install hydrophobic farnesyl and C(17) chains on chymotrypsinogen A in water using little or no cosolvent. Following this, the C(17) alkylated proteins were found to associate with lipid vesicles. In addition to providing a new protein modification strategy targeting an under-utilized amino acid side chain, this method provides convenient access to synthetic lipoproteins. PMID:16433516

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

    PubMed

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

    2016-04-01

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

  10. A Collaborative Model for Principal Selection.

    ERIC Educational Resources Information Center

    Richardson, M. D.; And Others

    Although the principal is critical for the success of the school and the school district, many school districts lack a structured and systematic means for identifying and selecting principals. This paper presents a collaborative model for principal selection, which is based on a valid job description, advertisement of the position, interview…

  11. Plasmid maintenance and protein overproduction in selective recycle bioreactors.

    PubMed

    Ogden, K L; Davis, R H

    1991-02-20

    A new plasmid construct has been used in conjunction with selective recycle to successfully maintain otherwise unstable plasmid-bearing E. coli cells in a continuous bioreactor and to produce significant amounts of the plasmid-encoded protein beta-lactamase. The plasmid is constructed so that pilin expression, which leads to bacterial flocculation, is under control of the tac operon. The plasmid-bearing cells are induced to flocculate in the separator, whereas cell growth and product synthesis occur in the main fermentation vessel without the inhibiting effects of pilin production. Selective recycle allows for the maintenance of the plasmid-bearing cells by separating flocculent, plasmid-bearing cells from nonflocculent, segregant cells in an inclined settler, and recycling only the plasmid-bearing cells to the reactor. As a result, product expression levels are maintained that are more than ten times the level achieved without selective recycle. All experimental data agree well with theoretical predictions. PMID:18597374

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

    PubMed Central

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

    2014-01-01

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

  13. 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.

  14. 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…

  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. Ion selective transistor modelling for behavioural simulations.

    PubMed

    Daniel, M; Janicki, M; Wroblewski, W; Dybko, A; Brzozka, Z; Napieralski, A

    2004-01-01

    Computer aided design and simulation of complex silicon microsystems oriented for environment monitoring requires efficient and accurate models of ion selective sensors, compatible with the existing behavioural simulators. This paper concerns sensors based on the back-side contact Ion Sensitive Field Effect Transistors (ISFETs). The ISFETs with silicon nitride gate are sensitive to hydrogen ion concentration. When the transistor gate is additionally covered with a special ion selective membrane, selectivity to other than hydrogen ions can be achieved. Such sensors are especially suitable for flow analysis of solutions containing various ions. The problem of ion selective sensor modelling is illustrated here on a practical example of an ammonium sensitive membrane. The membrane is investigated in the presence of some interfering ions and appropriate selectivity coefficients are determined. Then, the model of the whole sensor is created and used in subsequent electrical simulations. Providing that appropriate selectivity coefficients are known, the proposed model is applicable for any membrane, and can be straightforwardly implemented for behavioural simulation of water monitoring microsystems. The model has been already applied in a real on-line water pollution monitoring system for detection of various contaminants. PMID:15685987

  17. Biophysical modeling of mismatch repair proteins

    NASA Astrophysics Data System (ADS)

    Salsbury, Freddie

    2009-03-01

    Mismatch repair proteins play a vital role in the bology of cancer due to their dual functions as repair proteins and as sensors of DNA damage. Computational modeling of mismatch repair proteins in conjunction with biological experimentation has demonstrated the role of long-range communication in the functions of these proteins. Furthermore, different conformations have been shown to be associated with different cellular functions, and these differences are being exploited in drug discovery. The latest results in this modeling will be presented.

  18. 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.

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

    PubMed

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

    2015-01-01

    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. PMID:26325288

  20. A Pragmatic Model for Instructional Technology Selection.

    ERIC Educational Resources Information Center

    Vaccare, Carmel; Sherman, Greg

    2001-01-01

    The 4S model uses the criteria "Simple, Stable, Scalable, and Sustainable" as a filter for selecting instructional technologies. This paper considers a social dimension that uses culture and interaction as the primary consideration in the deployment of any instructional technology within the context of the 4S model. (Author/MES)

  1. Melody Track Selection Using Discriminative Language Model

    NASA Astrophysics Data System (ADS)

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

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

  2. Selecting model complexity in learning problems

    SciTech Connect

    Buescher, K.L.; Kumar, P.R.

    1993-10-01

    To learn (or generalize) from noisy data, one must resist the temptation to pick a model for the underlying process that overfits the data. Many existing techniques solve this problem at the expense of requiring the evaluation of an absolute, a priori measure of each model`s complexity. We present a method that does not. Instead, it uses a natural, relative measure of each model`s complexity. This method first creates a pool of ``simple`` candidate models using part of the data and then selects from among these by using the rest of the data.

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

    PubMed Central

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

    2012-01-01

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

  4. Selective Metal-Site-Guided Arylation of Proteins.

    PubMed

    Willwacher, Jens; Raj, Ritu; Mohammed, Shabaz; Davis, Benjamin G

    2016-07-20

    We describe palladium-mediated S-arylation that exploits natural metal-binding motifs to ensure high site selectivity for a proximal reactive residue. This allows the chemical identification not only of proteins that bind metals but also the environment of the metal-binding site itself through proteomic analysis of arylation sites. The transformation is easy to perform under standard conditions, does not require the isolation of a reactive Ar-Pd complex, is broad in scope, and is applicable in cell lysates as well as to covalent inhibition/modulation of metal-dependent enzymatic activity. PMID:27336299

  5. 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.

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

    DOE PAGESBeta

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

    2015-12-24

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

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

    PubMed Central

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

    2015-01-01

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

  8. Mutational robustness emerges in a microscopic model of protein evolution

    NASA Astrophysics Data System (ADS)

    Zeldovich, Konstantin; Shakhnovich, Eugene

    2009-03-01

    The ability to absorb mutations while retaining structure and function, or mutational robustness, is a remarkable property of natural proteins. We use a computational model of organismic evolution [Zeldovich et al, PLOS Comp Biol 3(7):e139 (2007)], which explicitly couples protein physics and population dynamics, to study mutational robustness of evolved model proteins. We compare evolved sequences with the ones designed to fold into the same native structures and having the same thermodynamic stability, and find that evolved sequences are more robust against point mutations, being less likely to be destabilized, and more likely to increase stability upon a point mutation. These results point to sequence evolution as an important method of protein engineering if mutational robustness of the artificially developed proteins is desired. On the biological side, mutational robustness of proteins appears to be a natural consequence of the divergence-mutation- selection evolutionary process.

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

    PubMed Central

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

    2012-01-01

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

  10. 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…

  11. Grid selection of models of nucleotide substitution

    PubMed Central

    Loureiro, Marta; Pan, Miguel; Rodríguez-Pascual, Manuel; Posada, David; Mayo, Rafael

    2016-01-01

    jModelTest is a Java program for the statistical selection of models of nucleotide substitution with thousands of users around the world. For large data sets, the calculations carried out by this program can be too expensive for many users. Here we describe the port of the jModeltest code for Grid computing using DRMAA. This work should facilitate the use of jModelTest on a broad scale. PMID:20543444

  12. Discriminative Feature Selection via Multiclass Variable Memory Markov Model

    NASA Astrophysics Data System (ADS)

    Slonim, Noam; Bejerano, Gill; Fine, Shai; Tishby, Naftali

    2003-12-01

    We propose a novel feature selection method based on a variable memory Markov (VMM) model. The VMM was originally proposed as a generative model trying to preserve the original source statistics from training data. We extend this technique to simultaneously handle several sources, and further apply a new criterion to prune out nondiscriminative features out of the model. This results in a multiclass discriminative VMM (DVMM), which is highly efficient, scaling linearly with data size. Moreover, we suggest a natural scheme to sort the remaining features based on their discriminative power with respect to the sources at hand. We demonstrate the utility of our method for text and protein classification tasks.

  13. Automated sample plan selection for OPC modeling

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  14. Modeling repetitive, non-globular proteins.

    PubMed

    Basu, Koli; Campbell, Robert L; Guo, Shuaiqi; Sun, Tianjun; Davies, Peter L

    2016-05-01

    While ab initio modeling of protein structures is not routine, certain types of proteins are more straightforward to model than others. Proteins with short repetitive sequences typically exhibit repetitive structures. These repetitive sequences can be more amenable to modeling if some information is known about the predominant secondary structure or other key features of the protein sequence. We have successfully built models of a number of repetitive structures with novel folds using knowledge of the consensus sequence within the sequence repeat and an understanding of the likely secondary structures that these may adopt. Our methods for achieving this success are reviewed here. PMID:26914323

  15. 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

  16. Temporally Variable Selection on Proteolysis-Related Reproductive Tract Proteins in Drosophila

    PubMed Central

    Wong, Alex; Turchin, Michael; Wolfner, Mariana F.; Aquadro, Charles F.

    2012-01-01

    In order to gain further insight into the processes underlying rapid reproductive protein evolution, we have conducted a population genetic survey of 44 reproductive tract–expressed proteases, protease inhibitors, and targets of proteolysis in Drosophila melanogaster and Drosophila simulans. Our findings suggest that positive selection on this group of genes is temporally heterogeneous, with different patterns of selection inferred using tests sensitive at different time scales. Such variation in the strength and targets of selection through time may be expected under models of sexual conflict and/or host–pathogen interaction. Moreover, available functional information concerning the genes that show evidence of selection suggests that both sexual selection and immune processes have been important in the evolutionary history of this group of molecules. PMID:21940639

  17. 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.

  18. Tabu search model selection for SVM.

    PubMed

    Lebrun, Gilles; Charrier, Christophe; Lezoray, Olivier; Cardot, Hubert

    2008-02-01

    A model selection method based on tabu search is proposed to build support vector machines (binary decision functions) of reduced complexity and efficient generalization. The aim is to build a fast and efficient support vector machines classifier. A criterion is defined to evaluate the decision function quality which blends recognition rate and the complexity of a binary decision functions together. The selection of the simplification level by vector quantization, of a feature subset and of support vector machines hyperparameters are performed by tabu search method to optimize the defined decision function quality criterion in order to find a good sub-optimal model on tractable times. PMID:18344220

  19. 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

  20. Stochastic model for protein flexibility analysis

    NASA Astrophysics Data System (ADS)

    Xia, Kelin; Wei, Guo-Wei

    2013-12-01

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

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

    PubMed

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

    2016-01-01

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

  2. 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.

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

    PubMed

    Price, Morgan N; Arkin, Adam P

    2016-01-01

    We use simple models of the costs and benefits of microbial gene expression to show that changing a protein's expression away from its optimum by 2-fold should reduce fitness by at least [Formula: see text], where P is the fraction the cell's protein that the gene accounts for. As microbial genes are usually expressed at above 5 parts per million, and effective population sizes are likely to be above 10(6), this implies that 2-fold changes to gene expression levels are under strong selection, as [Formula: see text], where Ne is the effective population size and s is the selection coefficient. Thus, most gene duplications should be selected against. On the other hand, we predict that for most genes, small changes in the expression will be effectively neutral. PMID:27289091

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

    PubMed

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

    2014-11-13

    Protein-RNA interaction plays a very crucial role in many biological processes, such as protein synthesis, transcription and post-transcription of gene expression and pathogenesis of disease. Especially RNAs always function through binding to proteins. Identification of binding interface region is especially useful for cellular pathways analysis and drug design. In this study, we proposed a novel approach for binding sites identification in proteins, which not only integrates local features and global features from protein sequence directly, but also constructed a balanced training dataset using sub-sampling based on submodularity subset selection. Firstly we extracted local features and global features from protein sequence, such as evolution information and molecule weight. Secondly, the number of non-interaction sites is much more than interaction sites, which leads to a sample imbalance problem, and hence biased machine learning model with preference to non-interaction sites. To better resolve this problem, instead of previous randomly sub-sampling over-represented non-interaction sites, a novel sampling approach based on submodularity subset selection was employed, which can select more representative data subset. Finally random forest were trained on optimally selected training subsets to predict interaction sites. Our result showed that our proposed method is very promising for predicting protein-RNA interaction residues, it achieved an accuracy of 0.863, which is better than other state-of-the-art methods. Furthermore, it also indicated the extracted global features have very strong discriminate ability for identifying interaction residues from random forest feature importance analysis. PMID:25462339

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

    PubMed

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

    2015-03-10

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

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

    PubMed

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

    2014-04-22

    Pigs may have retained the capacity to choose feeds based on their nutritional requirements, even after decades in which they are not allowed to select their diet composition due to the common feeding systems of the intensive pig industry. We used 480 early-weaned piglets in two experiments to assess their ability to select and prefer protein-related sources, depending on their protein status. Piglets were fed after weaning with two isoenergetic diets formulated to contain an optimal or sub-optimal crude-protein (CP) content, a high-protein (HP, 204g CP/kg as-fed) or a low-protein diet (LP, 142g CP/kg), respectively. In Experiment 1, the preference of piglets was assessed by using a choice test between protein (porcine digestible peptides [PDP] 40g/L) and carbohydrate (sucrose 40g/L) water-based solutions for a period of 3min. Piglets showed higher intake and preference for the sucrose 40g/L than for the PDP 40g/L solution, independently of the dietary CP content (9.8mL/kg body weight [BW] vs. 3.7mL/kg BW and 10.4mL/kg BW vs. 4.3mL/kg BW in HP and LP pigs, respectively). In Experiment 2, piglets were given eight training sessions in which two equally preferred flavors were mixed with protein (porcine animal plasma 60g/L, CSp) or carbohydrate (maltodextrin 60g/L, CSc) solutions. In the subsequent choice test, piglets fed the HP diet showed a tendency to a higher intake of CSc than of CSp (6.5mL/kg BW vs. 5.4mL/kg BW). On the other hand, piglets fed the LP diet showed a higher intake and preference for CSp than for CSc (15.5mL/kg BW vs. 10.2mL/kg BW), differences being higher for medium and low BW piglets than for heavy ones. The results show that piglets are unable to express a specific appetite for protein to correct previous underfeeding with it; however, they may show an appropriate dietary selection pattern in order to overcome protein deficiency through associative learning. PMID:24582664

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

    PubMed Central

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

    2014-01-01

    Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces generate reliable models without the need for complex software packages or downloading large databases. Here, we describe the latest version of the SWISS-MODEL expert system for protein structure modelling. The SWISS-MODEL template library provides annotation of quaternary structure and essential ligands and co-factors to allow for building of complete structural models, including their oligomeric structure. The improved SWISS-MODEL pipeline makes extensive use of model quality estimation for selection of the most suitable templates and provides estimates of the expected accuracy of the resulting models. The accuracy of the models generated by SWISS-MODEL is continuously evaluated by the CAMEO system. The new web site allows users to interactively search for templates, cluster them by sequence similarity, structurally compare alternative templates and select the ones to be used for model building. In cases where multiple alternative template structures are available for a protein of interest, a user-guided template selection step allows building models in different functional states. SWISS-MODEL is available at http://swissmodel.expasy.org/. PMID:24782522

  8. A New Hidden Markov Model for Protein Quality Assessment Using Compatibility Between Protein Sequence and Structure

    PubMed Central

    He, Zhiquan; Ma, Wenji; Zhang, Jingfen; Xu, Dong

    2015-01-01

    Protein structure Quality Assessment (QA) is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA. In this work, we developed a new Hidden Markov Model (HMM) to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities: (1) encoding local structure of each position by jointly considering sequence and structure information, and (2) assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP, and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets. PMID:26221066

  9. 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. PMID:14563566

  10. Student Selection and the Special Regression Model.

    ERIC Educational Resources Information Center

    Deck, Dennis D.

    The feasibility of constructing composite scores which will yield pretest measures having all the properties required by the special regression model is explored as an alternative to the single pretest score usually used in student selection for Elementary Secondary Education Act Title I compensatory education programs. Reading data, including…

  11. 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.

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

    PubMed

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

    2015-01-01

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

  13. Mechanical Strength of 17 134 Model Proteins and Cysteine Slipknots

    PubMed Central

    2009-01-01

    A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations. PMID:19876372

  14. 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

  15. Structural determinants of G-protein alpha subunit selectivity by regulator of G-protein signaling 2 (RGS2).

    PubMed

    Kimple, Adam J; Soundararajan, Meera; Hutsell, Stephanie Q; Roos, Annette K; Urban, Daniel J; Setola, Vincent; Temple, Brenda R S; Roth, Bryan L; Knapp, Stefan; Willard, Francis S; Siderovski, David P

    2009-07-17

    "Regulator of G-protein signaling" (RGS) proteins facilitate the termination of G protein-coupled receptor (GPCR) signaling via their ability to increase the intrinsic GTP hydrolysis rate of Galpha subunits (known as GTPase-accelerating protein or "GAP" activity). RGS2 is unique in its in vitro potency and selectivity as a GAP for Galpha(q) subunits. As many vasoconstrictive hormones signal via G(q) heterotrimer-coupled receptors, it is perhaps not surprising that RGS2-deficient mice exhibit constitutive hypertension. However, to date the particular structural features within RGS2 determining its selectivity for Galpha(q) over Galpha(i/o) substrates have not been completely characterized. Here, we examine a trio of point mutations to RGS2 that elicits Galpha(i)-directed binding and GAP activities without perturbing its association with Galpha(q). Using x-ray crystallography, we determined a model of the triple mutant RGS2 in complex with a transition state mimetic form of Galpha(i) at 2.8-A resolution. Structural comparison with unliganded, wild type RGS2 and of other RGS domain/Galpha complexes highlighted the roles of these residues in wild type RGS2 that weaken Galpha(i) subunit association. Moreover, these three amino acids are seen to be evolutionarily conserved among organisms with modern cardiovascular systems, suggesting that RGS2 arose from the R4-subfamily of RGS proteins to have specialized activity as a potent and selective Galpha(q) GAP that modulates cardiovascular function. PMID:19478087

  16. Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination

    PubMed Central

    Kazmier, Kelli; Alexander, Nathan S.; Meiler, Jens; Mchaourab, Hassane S.

    2010-01-01

    A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al., 2008). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 50% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, the number of which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance. PMID:21074624

  17. A soft and transparent handleable protein model

    NASA Astrophysics Data System (ADS)

    Kawakami, Masaru

    2012-08-01

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

  18. Solvent accessibility and purifying selection within proteins of Escherichia coli and Salmonella enterica.

    PubMed

    Bustamante, C D; Townsend, J P; Hartl, D L

    2000-02-01

    The neutral theory of molecular evolution predicts that variation within species is inversely related to the strength of purifying selection, but the strength of purifying selection itself must be related to physical constraints imposed by protein folding and function. In this paper, we analyzed five enzymes for which polymorphic sequence variation within Escherichia coli and/or Salmonella enterica was available, along with a protein structure. Single and multivariate logistic regression models are presented that evaluate amino acid size, physicochemical properties, solvent accessibility, and secondary structure as predictors of polymorphism. A model that contains a positive coefficient of association between polymorphism and solvent accessibility and separate intercepts for each secondary-structure element is sufficient to explain the observed variation in polymorphism between sites. The model predicts an increase in the probability of amino acid polymorphism with increasing solvent accessibility for each protein regardless of physicochemical properties, secondary-structure element, or size of the amino acid. This result, when compared with the distribution of synonymous polymorphism, which shows no association with solvent accessibility, suggests a strong decrease in purifying selection with increasing solvent accessibility. PMID:10677853

  19. Neutral evolution of Protein-protein interactions: a computational study using simple models

    PubMed Central

    Noirel, Josselin; Simonson, Thomas

    2007-01-01

    Background Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions. Results In the model, viable sequences all have the same fitness, following the neutral evolution theory. A very simple, two-dimensional lattice representation of the protein structures is used, and the model only considers two kinds of amino acids: hydrophobic and polar. With these approximations, exact calculations are performed. The results do not depend too strongly on these assumptions, since a model using a 3D, off-lattice representation of the proteins gives results in qualitative agreement with the 2D one. With both models, the evolutionary dynamics lead to a steady state population that is enriched in sequences that dimerize with a high affinity, well beyond the minimal level needed to survive. Correspondingly, sequences close to the viability threshold are less abundant in the steady state, being subject to a larger proportion of lethal mutations. The set of viable sequences has a "funnel" shape, consistent with earlier studies: sequences that are highly populated in the steady state are "close" to each other (with proximity being measured by the number of amino acids that differ). Conclusion This bias in the the steady state sequences should lead to an increased resistance of the population to environmental change and an increased ability to evolve. PMID:18021454

  20. Autophagy and selective deployment of Atg proteins in antiviral defense

    PubMed Central

    2013-01-01

    Autophagy is an evolutionarily ancient process eukaryotic cells utilize to remove and recycle intracellular material in order to maintain cellular homeostasis. In metazoans, the autophagy machinery not only functions in this capacity but also has evolved to perform a diverse repertoire of intracellular transport and regulatory functions. In response to virus infections, the autophagy machinery degrades viruses, shuttles viral pathogen-associated molecular patterns to endosomes containing Toll-like receptors, facilitates viral-antigen processing for major histocompatibility complex presentation and transports antiviral proteins to viral replication sites. This is accomplished through canonical autophagy or through processes involving distinct subsets of the autophagy-related genes (Atgs). Herein, we discuss how the variable components of the autophagy machinery contribute to antiviral defense and highlight three emerging themes: first, autophagy delivers viral cytosolic components to several distinct endolysosomal compartments; second, Atg proteins act alone, as subgroups or collectively; and third, the specificity of autophagy and the autophagy machinery is achieved by recognition of triggers and selective targeting by adaptors. PMID:23042773

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

    PubMed Central

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

    2012-01-01

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

  2. 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

  3. 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. PMID:24037756

  4. 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

  5. Enhanced Selectivity for Sulfatide by Engineered Human Glycolipid Transfer Protein

    PubMed Central

    Samygina, Valeria R.; Popov, Alexander N.; Cabo-Bilbao, Aintzane; Ochoa-Lizarralde, Borja; Goni-de-Cerio, Felipe; Zhai, Xiuhong; Molotkovsky, Julian G.; Patel, Dinshaw J.; Brown, Rhoderick E.; Malinina, Lucy

    2011-01-01

    SUMMARY Human glycolipid transfer protein (GLTP) fold represents a novel structural motif for lipid binding/transfer and reversible membrane translocation. GLTPs transfer glycosphingolipids (GSLs) which are key regulators of cell growth, division, surface adhesion, and neurodevelopment. Herein, we report structure-guided engineering of the lipid binding features of GLTP. New crystal structures of wild-type GLTP and two mutants (D48V and A47D||D48V), each containing bound N-nervonoyl-sulfatide, reveal the molecular basis for selective anchoring of sulfatide (3-O-sulfo-galactosylceramide) by D48V-GLTP. Directed point mutations of ‘portal entrance’ residues, A47 and D48, reversibly regulate sphingosine access to the hydrophobic pocket via a mechanism that could involve homo-dimerization. ‘Door-opening’ conformational changes by phenylalanines within the hydrophobic pocket are revealed during lipid encapsulation by new crystal structures of bona fide apo-GLTP and GLTP complexed with N-oleoyl-glucosylceramide. The development of ‘engineered GLTPs’ with enhanced specificity for select GSLs provides a potential new therapeutic approach for targeting GSL-mediated pathologies. PMID:22078563

  6. Identifying relevant positions in proteins by Critical Variable Selection.

    PubMed

    Grigolon, Silvia; Franz, Silvio; Marsili, Matteo

    2016-06-21

    Evolution in its course has found a variety of solutions to the same optimisation problem. The advent of high-throughput genomic sequencing has made available extensive data from which, in principle, one can infer the underlying structure on which biological functions rely. In this paper, we present a new method aimed at the extraction of sites encoding structural and functional properties from a set of protein primary sequences, namely a multiple sequence alignment. The method, called critical variable selection, is based on the idea that subsets of relevant sites correspond to subsequences that occur with a particularly broad frequency distribution in the dataset. By applying this algorithm to in silico sequences, to the response regulator receiver and to the voltage sensor domain of ion channels, we show that this procedure recovers not only the information encoded in single site statistics and pairwise correlations but also captures dependencies going beyond pairwise correlations. The method proposed here is complementary to statistical coupling analysis, in that the most relevant sites predicted by the two methods differ markedly. We find robust and consistent results for datasets as small as few hundred sequences that reveal a hidden hierarchy of sites that are consistent with the present knowledge on biologically relevant sites and evolutionary dynamics. This suggests that critical variable selection is capable of identifying a core of sites encoding functional and structural information in a multiple sequence alignment. PMID:26974515

  7. Modeling of Protein Subcellular Localization in Bacteria

    NASA Astrophysics Data System (ADS)

    Xu, Xiaohua; Kulkarni, Rahul

    2006-03-01

    Specific subcellular localization of proteins is a vital component of important bacterial processes: e.g. the Min proteins which regulate cell division in E. coli and Spo0J-Soj system which is critical for sporulation in B. subtilis. We examine how the processes of diffusion and membrane attachment contribute to protein subcellular localization for the above systems. We use previous experimental results to suggest minimal models for these processes. For the minimal models, we derive analytic expressions which provide insight into the processes that determine protein subcellular localization. Finally, we present the results of numerical simulations for the systems studied and make connections to the observed experiemental phenomenology.

  8. 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.

  9. 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/. PMID:25209223

  10. Optimized Null Model for Protein Structure Networks

    PubMed Central

    Lappe, Michael; Pržulj, Nataša

    2009-01-01

    Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by

  11. Preservation of protein clefts in comparative models

    PubMed Central

    Piedra, David; Lois, Sergi; de la Cruz, Xavier

    2008-01-01

    Background Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein. Results We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality – measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues. Conclusion We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and

  12. 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

  13. 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

  14. Integrative variable selection via Bayesian model uncertainty.

    PubMed

    Quintana, M A; Conti, D V

    2013-12-10

    We are interested in developing integrative approaches for variable selection problems that incorporate external knowledge on a set of predictors of interest. In particular, we have developed an integrative Bayesian model uncertainty (iBMU) method, which formally incorporates multiple sources of data via a second-stage probit model on the probability that any predictor is associated with the outcome of interest. Using simulations, we demonstrate that iBMU leads to an increase in power to detect true marginal associations over more commonly used variable selection techniques, such as least absolute shrinkage and selection operator and elastic net. In addition, iBMU leads to a more efficient model search algorithm over the basic BMU method even when the predictor-level covariates are only modestly informative. The increase in power and efficiency of our method becomes more substantial as the predictor-level covariates become more informative. Finally, we demonstrate the power and flexibility of iBMU for integrating both gene structure and functional biomarker information into a candidate gene study investigating over 50 genes in the brain reward system and their role with smoking cessation from the Pharmacogenetics of Nicotine Addiction and Treatment Consortium. PMID:23824835

  15. 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

  16. Aspects of model selection in multivariate analyses

    SciTech Connect

    Picard, R.

    1982-01-01

    Analysis of data sets that involve large numbers of variables usually entails some type of model fitting and data reduction. In regression problems, a fitted model that is obtained by a selection process can be difficult to evaluate because of optimism induced by the choice mechanism. Problems in areas such as discriminant analysis, calibration, and the like often lead to similar difficulties. The preceeding sections reviewed some of the general ideas behind assessment of regression-type predictors and illustrated how they can be easily incorporated into a standard data analysis.

  17. Conformational selection underpins recognition of multiple DNA sequences by proteins and consequent functional actions.

    PubMed

    Naiya, Gitashri; Raha, Paromita; Mondal, Manas Kumar; Pal, Uttam; Saha, Rajesh; Chaudhuri, Susobhan; Batabyal, Subrata; Kumar Pal, Samir; Bhattacharyya, Dhananjay; Maiti, Nakul C; Roy, Siddhartha

    2016-08-21

    Recognition of multiple functional DNA sequences by a DNA-binding protein occurs widely in nature. The physico-chemical basis of this phenomenon is not well-understood. The E. coli gal repressor, a gene regulatory protein, binds two homologous but non-identical sixteen basepair sequences in the gal operon and interacts by protein-protein interaction to regulate gene expression. The two sites have nearly equal affinities for the Gal repressor. Spectroscopic studies of the Gal repressor bound to these two different DNA sequences detected significant conformational differences between them. Comprehensive single base-substitution and binding measurements were carried out on the two sequences to understand the nature of the two protein-DNA interfaces. Magnitudes of basepair-protein interaction energy show significant variation between homologous positions of the two DNA sequences. Magnitudes of variation are such that when summed over the whole sequence they largely cancel each other out, thus producing nearly equal net affinity. Modeling suggests significant alterations in the protein-DNA interface in the two complexes, which are consistent with conformational adaptation of the protein to different DNA sequences. The functional role of the two sequences was studied by substitution of one site by the other and vice versa. In both cases, substitution reduces repression in vivo. This suggests that naturally occurring DNA sequence variations play functional roles beyond merely acting as high-affinity anchoring points. We propose that two different pre-existing conformations in the conformational ensemble of the free protein are selected by two different DNA sequences for efficient sequence read-out and the conformational difference of the bound proteins leads to different functional roles. PMID:27426617

  18. Template-based structure modeling of protein-protein interactions

    PubMed Central

    Szilagyi, Andras; Zhang, Yang

    2014-01-01

    The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput experimental data. Nevertheless, bottlenecks exist due to the incompleteness of the proteinprotein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement. PMID:24721449

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

    PubMed

    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. PMID:27097106

  20. Gaussian Process Modeling of Protein Turnover.

    PubMed

    Rahman, Mahbubur; Previs, Stephen F; Kasumov, Takhar; Sadygov, Rovshan G

    2016-07-01

    We describe a stochastic model to compute in vivo protein turnover rate constants from stable-isotope labeling and high-throughput liquid chromatography-mass spectrometry experiments. We show that the often-used one- and two-compartment nonstochastic models allow explicit solutions from the corresponding stochastic differential equations. The resulting stochastic process is a Gaussian processes with Ornstein-Uhlenbeck covariance matrix. We applied the stochastic model to a large-scale data set from (15)N labeling and compared its performance metrics with those of the nonstochastic curve fitting. The comparison showed that for more than 99% of proteins, the stochastic model produced better fits to the experimental data (based on residual sum of squares). The model was used for extracting protein-decay rate constants from mouse brain (slow turnover) and liver (fast turnover) samples. We found that the most affected (compared to two-exponent curve fitting) results were those for liver proteins. The ratio of the median of degradation rate constants of liver proteins to those of brain proteins increased 4-fold in stochastic modeling compared to the two-exponent fitting. Stochastic modeling predicted stronger differences of protein turnover processes between mouse liver and brain than previously estimated. The model is independent of the labeling isotope. To show this, we also applied the model to protein turnover studied in induced heart failure in rats, in which metabolic labeling was achieved by administering heavy water. No changes in the model were necessary for adapting to heavy-water labeling. The approach has been implemented in a freely available R code. PMID:27229456

  1. Computational model for protein unfolding simulation

    NASA Astrophysics Data System (ADS)

    Tian, Xu-Hong; Zheng, Ye-Han; Jiao, Xiong; Liu, Cai-Xing; Chang, Shan

    2011-06-01

    The protein folding problem is one of the fundamental and important questions in molecular biology. However, the all-atom molecular dynamics studies of protein folding and unfolding are still computationally expensive and severely limited by the time scale of simulation. In this paper, a simple and fast protein unfolding method is proposed based on the conformational stability analyses and structure modeling. In this method, two structure-based conditions are considered to identify the unstable regions of proteins during the unfolding processes. The protein unfolding trajectories are mimicked through iterative structure modeling according to conformational stability analyses. Two proteins, chymotrypsin inhibitor 2 (CI2) and α -spectrin SH3 domain (SH3) were simulated by this method. Their unfolding pathways are consistent with the previous molecular dynamics simulations. Furthermore, the transition states of the two proteins were identified in unfolding processes and the theoretical Φ values of these transition states showed significant correlations with the experimental data (the correlation coefficients are >0.8). The results indicate that this method is effective in studying protein unfolding. Moreover, we analyzed and discussed the influence of parameters on the unfolding simulation. This simple coarse-grained model may provide a general and fast approach for the mechanism studies of protein folding.

  2. Information criteria and selection of vibration models.

    PubMed

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

    2014-12-01

    This paper presents a method of determining an appropriate equation of motion of two-dimensional plane structures like membranes and plates from vibration response measurements. The local steady-state vibration field is used as input for the inverse problem that approximately determines the dispersion curve of the structure. This dispersion curve is then statistically treated with Akaike information criterion (AIC), which compares the experimentally measured curve to several candidate models (equations of motion). The model with the lowest AIC value is then chosen, and the utility of other models can also be assessed. This method is applied to three experimental case studies: A red cedar wood plate for musical instruments, a thick paper subjected to unknown membrane tension, and a thick composite sandwich panel. These three cases give three different situations of a model selection. PMID:25480053

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

    PubMed

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

    2009-10-01

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

  4. Quinalizarin as a potent, selective and cell-permeable inhibitor of protein kinase CK2.

    PubMed

    Cozza, Giorgio; Mazzorana, Marco; Papinutto, Elena; Bain, Jenny; Elliott, Matthew; di Maira, Giovanni; Gianoncelli, Alessandra; Pagano, Mario A; Sarno, Stefania; Ruzzene, Maria; Battistutta, Roberto; Meggio, Flavio; Moro, Stefano; Zagotto, Giuseppe; Pinna, Lorenzo A

    2009-08-01

    Emodin (1,3,8-trihydroxy-6-methyl-anthraquinone) is a moderately potent and poorly selective inhibitor of protein kinase CK2, one of the most pleiotropic serine/threonine protein kinases, implicated in neoplasia and in other global diseases. By virtual screening of the MMS (Molecular Modeling Section) database, we have now identified quinalizarin (1,2,5,8-tetrahydroxyanthraquinone) as an inhibitor of CK2 that is more potent and selective than emodin. CK2 inhibition by quinalizarin is competitive with respect to ATP, with a Ki value of approx. 50 nM. Tested at 1 microM concentration on a panel of 75 protein kinases, quinalizarin drastically inhibits only CK2, with a promiscuity score (11.1), which is the lowest ever reported so far for a CK2 inhibitor. Especially remarkable is the ability of quinalizarin to discriminate between CK2 and a number of kinases, notably DYRK1a (dual-specificity tyrosine-phosphorylated and -regulated kinase), PIM (provirus integration site for Moloney murine leukaemia virus) 1, 2 and 3, HIPK2 (homeodomain-interacting protein kinase-2), MNK1 [MAPK (mitogen-activated protein kinase)-interacting kinase 1], ERK8 (extracellular-signal-regulated kinase 8) and PKD1 (protein kinase D 1), which conversely tend to be inhibited as drastically as CK2 by commercially available CK2 inhibitors. The determination of the crystal structure of a complex between quinalizarin and CK2alpha subunit highlights the relevance of polar interactions in stabilizing the binding, an unusual characteristic for a CK2 inhibitor, and disclose other structural features which may account for the narrow selectivity of this compound. Tested on Jurkat cells, quinalizarin proved able to inhibit endogenous CK2 and to induce apoptosis more efficiently than the commonly used CK2 inhibitors TBB (4,5,6,7-tetrabromo-1H-benzotriazole) and DMAT (2-dimethylamino-4,5,6,7-tetrabromo-1H-benzimidazole). PMID:19432557

  5. Model selection for multi-component frailty models.

    PubMed

    Ha, Il Do; Lee, Youngjo; MacKenzie, Gilbert

    2007-11-20

    Various frailty models have been developed and are now widely used for analysing multivariate survival data. It is therefore important to develop an information criterion for model selection. However, in frailty models there are several alternative ways of forming a criterion and the particular criterion chosen may not be uniformly best. In this paper, we study an Akaike information criterion (AIC) on selecting a frailty structure from a set of (possibly) non-nested frailty models. We propose two new AIC criteria, based on a conditional likelihood and an extended restricted likelihood (ERL) given by Lee and Nelder (J. R. Statist. Soc. B 1996; 58:619-678). We compare their performance using well-known practical examples and demonstrate that the two criteria may yield rather different results. A simulation study shows that the AIC based on the ERL is recommended, when attention is focussed on selecting the frailty structure rather than the fixed effects. PMID:17476647

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

    PubMed

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

    2016-05-01

    We introduce active surfaces generated by immobilizing protein-polymer nanoreactors on a solid support for sensitive sugar alcohols detection. First, such selective nanoreactors were engineered in solution by simultaneous encapsulation of specific enzymes in copolymer polymersomes, and insertion of membrane proteins for selective conduct of sugar alcohols. Despite the artificial surroundings, and the thickness of the copolymer membrane, functionality of reconstituted Escherichia coli glycerol facilitator (GlpF) was preserved, and allowed selective diffusion of sugar alcohols to the inner cavity of the polymersome, where encapsulated ribitol dehydrogenase (RDH) enzymes served as biosensing entities. Ribitol, selected as a model sugar alcohol, was detected quantitatively by the RDH-nanoreactors with GlpF-mediated permeability in a concentration range of 1.5-9 mM. To obtain "active surfaces" for detecting sugar alcohols, the nanoreactors optimized in solution were then immobilized on a solid support: aldehyde groups exposed at the compartment external surface reacted via an aldehyde-amino reaction with glass surfaces chemically modified with amino groups. The nanoreactors preserved their architecture and activity after immobilization on the glass surface, and represent active biosensing surfaces for selective detection of sugar alcohols, with high sensitivity. PMID:26950167

  7. 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.

  8. Model selection for radiochromic film dosimetry

    NASA Astrophysics Data System (ADS)

    Méndez, I.

    2015-05-01

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

  9. 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

  10. COARSE-GRAINED MODELING OF PROTEIN UNFOLDING DYNAMICS*

    PubMed Central

    DENG, MINGGE

    2014-01-01

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

  11. Selection and estimation for mixed graphical models

    PubMed Central

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

    2016-01-01

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

  12. 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

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

    PubMed

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

    2011-01-01

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

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

    PubMed Central

    Price, Morgan N.; Arkin, Adam P.

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Basu, Aakash; Chowdhury, Debashish

    2007-10-01

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

  16. 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.

  17. Physical microscopic model of proteins under force.

    PubMed

    Dokholyan, Nikolay V

    2012-06-14

    Nature has evolved proteins to counteract forces applied on living cells, and has designed proteins that can sense forces. One can appreciate Nature's ingenuity in evolving these proteins to be highly sensitive to force and to have a high dynamic force range at which they operate. To achieve this level of sensitivity, many of these proteins are composed of multiple domains and linking peptides connecting these domains, each of them having their own force response regimes. Here, using a simple model of a protein, we address the question of how each individual domain responds to force. We also ask how multidomain proteins respond to forces. We find that the end-to-end distance of individual domains under force scales linearly with force. In multidomain proteins, we find that the force response has a rich range: at low force, extension is predominantly governed by "weaker" linking peptides or domain intermediates, while at higher force, the extension is governed by unfolding of individual domains. Overall, the force extension curve comprises multiple sigmoidal transitions governed by unfolding of linking peptides and domains. Our study provides a basic framework for the understanding of protein response to force, and allows for interpretation experiments in which force is used to study the mechanical properties of multidomain proteins. PMID:22375559

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

    PubMed

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  20. 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

  1. 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.

  2. A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition

    PubMed Central

    2013-01-01

    Background Assigning a protein into one of its folds is a transitional step for discovering three dimensional protein structure, which is a challenging task in bimolecular (biological) science. The present research focuses on: 1) the development of classifiers, and 2) the development of feature extraction techniques based on syntactic and/or physicochemical properties. Results Apart from the above two main categories of research, we have shown that the selection of physicochemical attributes of the amino acids is an important step in protein fold recognition and has not been explored adequately. We have presented a multi-dimensional successive feature selection (MD-SFS) approach to systematically select attributes. The proposed method is applied on protein sequence data and an improvement of around 24% in fold recognition has been noted when selecting attributes appropriately. Conclusion The MD-SFS has been applied successfully in selecting physicochemical attributes of the amino acids. The selected attributes show improved protein fold recognition performance. PMID:23879571

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

    PubMed

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

    2009-09-01

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

  4. A computational system for modelling flexible protein-protein and protein-DNA docking.

    PubMed

    Sternberg, M J; Aloy, P; Gabb, H A; Jackson, R M; Moont, G; Querol, E; Aviles, F X

    1998-01-01

    A computational system is described that predicts the structure of protein/protein and protein/DNA complexes starting from unbound coordinate sets. The approach is (i) a global search with rigid-body docking for complexes with shape complementarity and favourable electrostatics; (ii) use of distance constraints from experimental (or predicted) knowledge of critical residues; (iii) use of pair potential to screen docked complexes and (iv) refinement and further screening by protein-side chain optimisation and interfacial energy minimisation. The system has been applied to model ten protein/protein and eight protein-repressor/DNA (steps i to iii only) complexes. In general a few complexes, one of which is close to the true structure, can be generated. PMID:9783224

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

    PubMed Central

    Kelleher, Erin S.; Markow, Therese A.

    2009-01-01

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

  6. Modeling of protein misfolding in disease.

    PubMed

    Małolepsza, Edyta B

    2008-01-01

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

  7. A soft and transparent handleable protein model.

    PubMed

    Kawakami, Masaru

    2012-08-01

    The field of structural biology currently relies on computer-generated graphical representations of three-dimensional (3D) structures to conceptualize biomolecules. As the size and complexity of the molecular structure increases, model generation and peer discussions become more difficult. It is even more problematic when discussing protein-protein interactions wherein large surface area contact is considered. This report demonstrates the viability of a new handleable protein molecular model with a soft and transparent silicone body similar to the molecule's surface. A full-color printed main chain structure embedded in the silicone body enables users to simultaneously feel the molecular surface, view through the main chain structure, and manually simulate molecular docking. The interactive, hands-on experience deepens the user's intuitive understanding of the complicated 3D protein structure and elucidates ligand binding and protein-protein interactions. This model would be an effective discussion tool for the classroom or laboratory that stimulates inspired learning in this study field. PMID:22938316

  8. Parameter recovery and model selection in mixed Rasch models.

    PubMed

    Preinerstorfer, David; Formann, Anton K

    2012-05-01

    This study examines the precision of conditional maximum likelihood estimates and the quality of model selection methods based on information criteria (AIC and BIC) in mixed Rasch models. The design of the Monte Carlo simulation study included four test lengths (10, 15, 25, 40), three sample sizes (500, 1000, 2500), two simulated mixture conditions (one and two groups), and population homogeneity (equally sized subgroups) or heterogeneity (one subgroup three times larger than the other). The results show that both increasing sample size and increasing number of items lead to higher accuracy; medium-range parameters were estimated more precisely than extreme ones; and the accuracy was higher in homogeneous populations. The minimum-BIC method leads to almost perfect results and is more reliable than AIC-based model selection. The results are compared to findings by Li, Cohen, Kim, and Cho (2009) and practical guidelines are provided. PMID:21675964

  9. Modeling selective local interactions with memory

    PubMed Central

    Galante, Amanda; Levy, Doron

    2012-01-01

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

  10. Transformation model selection by multiple hypotheses testing

    NASA Astrophysics Data System (ADS)

    Lehmann, Rüdiger

    2014-12-01

    Transformations between different geodetic reference frames are often performed such that first the transformation parameters are determined from control points. If in the first place we do not know which of the numerous transformation models is appropriate then we can set up a multiple hypotheses test. The paper extends the common method of testing transformation parameters for significance, to the case that also constraints for such parameters are tested. This provides more flexibility when setting up such a test. One can formulate a general model with a maximum number of transformation parameters and specialize it by adding constraints to those parameters, which need to be tested. The proper test statistic in a multiple test is shown to be either the extreme normalized or the extreme studentized Lagrange multiplier. They are shown to perform superior to the more intuitive test statistics derived from misclosures. It is shown how model selection by multiple hypotheses testing relates to the use of information criteria like AICc and Mallows' , which are based on an information theoretic approach. Nevertheless, whenever comparable, the results of an exemplary computation almost coincide.

  11. Entropic Priors and Bayesian Model Selection

    NASA Astrophysics Data System (ADS)

    Brewer, Brendon J.; Francis, Matthew J.

    2009-12-01

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

  12. 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.

  13. Selecting a model of supersymmetry breaking mediation

    SciTech Connect

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

    2009-08-01

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

  14. Target selection by natural and redesigned PUF proteins.

    PubMed

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

    2015-12-29

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

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

    PubMed Central

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

    2010-01-01

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

  16. 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.

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

    NASA Technical Reports Server (NTRS)

    Holmquist, R.

    1979-01-01

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

  18. Selective Constraints on Amino Acids Estimated by a Mechanistic Codon Substitution Model with Multiple Nucleotide Changes

    PubMed Central

    Miyazawa, Sanzo

    2011-01-01

    Background Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices. Results Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins. Conclusions/Significance The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences. PMID:21445250

  19. 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.

  20. Animal models for protein respiratory sensitizers.

    PubMed

    Ward, Marsha D W; Selgrade, Maryjane K

    2007-01-01

    Protein induced respiratory hypersensitivity, particularly atopic disease in general, and allergic asthma in particular, has increased dramatically over the last several decades in the US and other industrialized nations as a result of ill-defined changes in living conditions in modern western society. In addition, work-related asthma has become the most frequently diagnosed occupational respiratory illness. Animal models have demonstrated great utility in developing an understanding of the etiology and mechanisms of many diseases. A few models been developed as predictive models to identify a protein as an allergen or to characterize its potency. Here we describe animal models that have been used to investigate and identify protein respiratory sensitizers. In addition to prototypical experimental design, methods for exposure route, sample collection, and endpoint assessment are described. Some of the most relevant endpoints in assessing the potential for a given protein to induce atopic or allergic asthma respiratory hypersensitivity are the development of cytotropic antibodies (IgE, IgG1), eosinophil influx into the lung, and airway hyperresponsiveness to the sensitizing protein and/or to non-antigenic stimuli (Mch). The utility of technologies such as PCR and multiplexing assay systems is also described. These models and methods have been used to elucidate the potential for protein sources to induce allergy, identify environmental conditions (pollutants) to impact allergy responsiveness, and establish safe exposure limits. As an example, data are presented from an experiment designed to compare the allergenicity of a fungal biopesticide Metarhizium anisopliae (MACA) crude extract with the one of its components, conidia (CON) extract. PMID:17161304

  1. A Protein Solvation Model Based on Residue Burial.

    PubMed

    Ceres, Nicoletta; Pasi, Marco; Lavery, Richard

    2012-06-12

    The influence of solvent on the individual amino acids of a protein depends not simply on their surface exposure but rather on the degree of their burial within the structure. This property can be related to a simple geometrical measure termed circular variance. Circular variance depends on the spatial distribution of neighboring residues and varies from zero to one as a residue becomes buried. Its only adjustable parameter is a cutoff distance for selecting neighbors. Here, we show that circular variance can be used to build a fast and effective model of protein solvation energies. For this, we combine a coarse-grain protein representation with statistical potentials derived by Boltzmann inversion of circular variance probability distributions for different classes of pseudoatom within a large protein structure database. The method is shown to work well for distinguishing native protein structures from decoy structures generated in a variety of ways. It can also be used to detect specific residues in unfavorable solvent environments. Compared to surface accessibility, circular variance calculations are faster, less sensitive to small conformational changes, and able to account for the longer-range interactions that characterize the electrostatic component of solvent effects. The resulting solvation energies can be used alone or as part of a more general coarse-grain protein model. PMID:26593844

  2. Protein quantification by MALDI-selected reaction monitoring mass spectrometry using sulfonate derivatized peptides.

    PubMed

    Lesur, Antoine; Varesio, Emmanuel; Hopfgartner, Gérard

    2010-06-15

    The feasibility of protein absolute quantification with matrix-assisted laser desorption/ionization (MALDI) using the selected reaction monitoring (SRM) acquisition mode on a triple quadrupole linear ion trap mass spectrometer (QqQ(LIT)) equipped with a high-frequency laser is demonstrated. A therapeutic human monoclonal antibody (mAb) was used as a model protein, and four tryptic peptides generated by fast tryptic digestion were selected as quantification surrogates. MALDI produces mostly singly charged peptides which hardly fragment under low-energy collision-induced dissociation (CID), and therefore the benefits of using 4-sulfophenyl isothiocyanate (SPITC) as a fragmentation enhancer derivatization agent were evaluated. Despite a moderate impact on the sensitivity, the N-terminus sulfonated peptides generate nearly complete y-ion ladders when native peptides produce few fragments. This aspect provides an alternative SRM transition set for each peptide. As a consequence, SRM transitions selectivity can be tuned more easily for peptide quantitation in complex matrices when monitoring several SRM transitions. From a quantitative point of view, the signal response depending on mAb concentration was found to be linear over 2.5 orders of magnitude for the most sensitive peptide, allowing precise and accurate measurement by MALDI-SRM/MS. PMID:20481516

  3. Information-driven modeling of protein-peptide complexes.

    PubMed

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

    2015-01-01

    Despite their biological importance in many regulatory processes, protein-peptide recognition mechanisms are difficult to study experimentally at the structural level because of the inherent flexibility of peptides and the often transient interactions on which they rely. Complementary methods like biomolecular docking are therefore required. The prediction of the three-dimensional structure of protein-peptide complexes raises unique challenges for computational algorithms, as exemplified by the recent introduction of protein-peptide targets in the blind international experiment CAPRI (Critical Assessment of PRedicted Interactions). Conventional protein-protein docking approaches are often struggling with the high flexibility of peptides whose short sizes impede protocols and scoring functions developed for larger interfaces. On the other side, protein-small ligand docking methods are unable to cope with the larger number of degrees of freedom in peptides compared to small molecules and the typically reduced available information to define the binding site. In this chapter, we describe a protocol to model protein-peptide complexes using the HADDOCK web server, working through a test case to illustrate every steps. The flexibility challenge that peptides represent is dealt with by combining elements of conformational selection and induced fit molecular recognition theories. PMID:25555727

  4. 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.

  5. Protein scaffolds for selective enrichment of metal ions

    DOEpatents

    He, Chuan; Zhou, Lu; Bosscher, Michael

    2016-02-09

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

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

    PubMed Central

    2016-01-01

    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 tRNACUA 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. PMID:25982410

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

    PubMed

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

    2015-10-01

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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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. PMID:17905832

  13. Differentiation of myeloid cell lines correlates with a selective expression of RIZ protein.

    PubMed Central

    Gazzerro, P.; Bontempo, P.; Schiavone, E. M.; Abbondanza, C.; Moncharmont, B.; Armetta, I.; Medici, N.; De Simone, M.; Nola, E.; Puca, G. A.; Molinari, A. M.

    2001-01-01

    BACKGROUND: The retinoblastoma-interacting zinc-finger gene RIZ is expressed in two forms (RIZ1 and RIZ2) that differ for the presence near the N-terminus of RIZ1 of a conserved domain, defined PR (PRDI-BF1-RIZ homology), homologous to a similar domain present in other proteins recognized as tumor suppressor gene products. The RIZ1 form is usually absent or expressed at low levels in tumor cells, whereas RIZ2 is frequently expressed. We investigated a possible involvement of RIZ1 in differentiation control using a myeloid cell maturation model that is easily modulated by retinoids and other agents. MATERIALS AND METHODS: HL60 or NB4 cell lines or patients' leukemic promyelocytes were treated with all- trans -retinoic acid or other agents to induce differentiation. RIZ gene expression was determined with reverse transcriptase polymerase chain reaction (RT-PCR) and RNase protection assay. Immunocytochemistry was performed to assess variation of the intracellular distribution of RIZ protein on all- trans-retinoic acid treatment. Forced expression of RIZ1 protein was obtained with a recombinant adenovirus containing RIZ1 cDNA. RESULTS: Treatment with retinoic acid induced a selective expression of RIZ1 in HL60 cell line. Retinoic acid effect was maximal at 7 days and correlated to the granulocytic differentiation of cells. A similar effect was obtained in retinoic acid-sensitive NB4 cell line or in patients' leukemic promyelocytes, but not in the retinoic acid-resistant cell line NB4.007/6 or in the U937 cell line. Selective expression of RIZ1 was also induced by 12-O-tetradecanoyl-phorbol-13-acetate in the U937 and HL60 cell lines and by 1,25-dihydroxyvitamin D(3) only in HL60 cells. In HL60 cells, RIZ1 was also induced by activation of a retinoid alpha receptor-independent maturation pathway based on retinoid X receptor agonist and protein kinase A synergism. In addition, retinoic acid produced a redistribution of the antigen within the nucleus in these cells. Forced

  14. The selectivity of protein kinase inhibitors: a further update

    PubMed Central

    Bain, Jenny; Plater, Lorna; Elliott, Matt; Shpiro, Natalia; Hastie, C. James; Mclauchlan, Hilary; Klevernic, Iva; Arthur, J. Simon C.; Alessi, Dario R.; Cohen, Philip

    2007-01-01

    The specificities of 65 compounds reported to be relatively specific inhibitors of protein kinases have been profiled against a panel of 70–80 protein kinases. On the basis of this information, the effects of compounds that we have studied in cells and other data in the literature, we recommend the use of the following small-molecule inhibitors: SB 203580/SB202190 and BIRB 0796 to be used in parallel to assess the physiological roles of p38 MAPK (mitogen-activated protein kinase) isoforms, PI-103 and wortmannin to be used in parallel to inhibit phosphatidylinositol (phosphoinositide) 3-kinases, PP1 or PP2 to be used in parallel with Src-I1 (Src inhibitor-1) to inhibit Src family members; PD 184352 or PD 0325901 to inhibit MKK1 (MAPK kinase-1) or MKK1 plus MKK5, Akt-I-1/2 to inhibit the activation of PKB (protein kinase B/Akt), rapamycin to inhibit TORC1 [mTOR (mammalian target of rapamycin)–raptor (regulatory associated protein of mTOR) complex], CT 99021 to inhibit GSK3 (glycogen synthase kinase 3), BI-D1870 and SL0101 or FMK (fluoromethylketone) to be used in parallel to inhibit RSK (ribosomal S6 kinase), D4476 to inhibit CK1 (casein kinase 1), VX680 to inhibit Aurora kinases, and roscovitine as a pan-CDK (cyclin-dependent kinase) inhibitor. We have also identified harmine as a potent and specific inhibitor of DYRK1A (dual-specificity tyrosine-phosphorylated and -regulated kinase 1A) in vitro. The results have further emphasized the need for considerable caution in using small-molecule inhibitors of protein kinases to assess the physiological roles of these enzymes. Despite being used widely, many of the compounds that we analysed were too non-specific for useful conclusions to be made, other than to exclude the involvement of particular protein kinases in cellular processes. PMID:17850214

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

    PubMed Central

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

    2010-01-01

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

  16. A Simple Model for Protein Folding

    NASA Astrophysics Data System (ADS)

    Henry, Eric R.; Eaton, William A.

    We describe a simple Ising-like statistical mechanical model for folding proteins based on the α-carbon contact map of the native structure. In this model residues can adopt two microscopic states corresponding to the native and non-native conformations. In order to exactly enumerate the large number of possible configurations, structure is considered to grow as continuous sequences of native residues, with no more than two sequences in each molecule. Inter-residue contacts can only form within each sequence and between residues of the two native sequences. As structure grows there is a tradeoff between the stabilizing effect of inter-residue contacts and the entropy losses from ordering residues in their native conformation and from forming a disordered loop to connect two continuous sequences. Folding kinetics are calculated from the dynamics on the free energy profile, as in Kramers' reaction rate theory. Although non-native interactions responsible for roughness in the energy landscape are not explicitly considered in the model, they are implicitly included by determining the absolute rates for motion on the free energy profile. With the exception of α-helical proteins, the kinetic progress curves exhibit single exponential time courses, consistent with two state behavior, as observed experimentally. The calculated folding rates are in remarkably good agreement with the measured values for the 25 two-state proteins investigated, with a correlation coefficient of 0.8. With its coarse-grained description of both the energy and entropy, and only three independently adjustable parameters, the model may be regarded as the simplest possible analytical model of protein folding capable of predicting experimental properties of specific proteins.

  17. Kinetic Analysis of Protein Folding Lattice Models

    NASA Astrophysics Data System (ADS)

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

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

  18. Structural Heterogeneity in Transmembrane Amyloid Precursor Protein Homodimer Is a Consequence of Environmental Selection

    PubMed Central

    2015-01-01

    The 99 amino acid C-terminal fragment of amyloid precursor protein (C99), consisting of a single transmembrane (TM) helix, is known to form homodimers. Homodimers can be processed by γ-secretase to produce amyloid-β (Aβ) protein, which is implicated in Alzheimer’s disease (AD). While knowledge of the structure of C99 homodimers is of great importance, experimental NMR studies and simulations have produced varying structural models, including right-handed and left-handed coiled-coils. In order to investigate the structure of this critical protein complex, simulations of the C9915–55 homodimer in POPC membrane bilayer and DPC surfactant micelle environments were performed using a multiscale approach that blends atomistic and coarse-grained models. The C9915–55 homodimer adopts a dominant right-handed coiled-coil topology consisting of three characteristic structural states in a bilayer, only one of which is dominant in the micelle. Our structural study, which provides a self-consistent framework for understanding a number of experiments, shows that the energy landscape of the C99 homodimer supports a variety of slowly interconverting structural states. The relative importance of any given state can be modulated through environmental selection realized by altering the membrane or micelle characteristics. PMID:24926593

  19. A feature-based approach to modeling protein-protein interaction hot spots.

    PubMed

    Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

    2009-05-01

    Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions. PMID:19273533

  20. Feature selection and nearest centroid classification for protein mass spectrometry

    PubMed Central

    Levner, Ilya

    2005-01-01

    Background The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard supervised classification algorithms can be employed, the "curse of dimensionality" needs to be solved. Due to the sheer amount of information contained within the mass spectra, most standard machine learning techniques cannot be directly applied. Instead, feature selection techniques are used to first reduce the dimensionality of the input space and thus enable the subsequent use of classification algorithms. This paper examines feature selection techniques for proteomic mass spectrometry. Results This study examines the performance of the nearest centroid classifier coupled with the following feature selection algorithms. Student-t test, Kolmogorov-Smirnov test, and the P-test are univariate statistics used for filter-based feature ranking. From the wrapper approaches we tested sequential forward selection and a modified version of sequential backward selection. Embedded approaches included shrunken nearest centroid and a novel version of boosting based feature selection we developed. In addition, we tested several dimensionality reduction approaches, namely principal component analysis and principal component analysis coupled with linear discriminant analysis. To fairly assess each algorithm, evaluation was done using stratified cross validation with an internal leave-one-out cross-validation loop for automated feature selection. Comprehensive experiments, conducted on five popular cancer data sets, revealed that the less advocated sequential forward selection and boosted feature selection algorithms produce the most consistent results across all data sets. In contrast, the state-of-the-art performance reported on isolated data sets for several of the studied algorithms, does not hold across all data sets. Conclusion This study tested a number of popular feature selection methods using the

  1. 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.

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

    PubMed

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

    2016-06-01

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

  3. 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

  4. Cargo- and compartment-selective endocytic scaffold proteins

    PubMed Central

    2004-01-01

    The endocytosis of membrane receptors is a complex and tightly controlled process that is essential for maintaining cellular homoeostasis. The removal of receptors from the cell surface can be constitutive or ligand-induced, and occurs in a clathrin-dependent or -independent manner. The recruitment of receptors into specialized membrane domains, the formation of vesicles and the trafficking of receptors together with their ligands within endocytic compartments are regulated by reversible protein modifications, and multiple protein–protein and protein–lipid interactions. Recent reports describe a variety of multidomain molecules that facilitate receptor endocytosis and function as platforms for the assembly of protein complexes. These scaffold proteins typically act in a cargo-specific manner, recognizing one or more receptor types, or function at the level of endocytic cellular microcompartments by controlling the movement of cargo molecules and linking endocytic machineries to signalling pathways. In the present review we summarize present knowledge on endocytic scaffold molecules and discuss their functions. PMID:15219178

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

    SciTech Connect

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

    2005-08-23

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  8. Selective Protein Hyperpolarization in Cell Lysates Using Targeted Dynamic Nuclear Polarization.

    PubMed

    Viennet, Thibault; Viegas, Aldino; Kuepper, Arne; Arens, Sabine; Gelev, Vladimir; Petrov, Ognyan; Grossmann, Tom N; Heise, Henrike; Etzkorn, Manuel

    2016-08-26

    Nuclear magnetic resonance (NMR) spectroscopy has the intrinsic capabilities to investigate proteins in native environments. In general, however, NMR relies on non-natural protein purity and concentration to increase the desired signal over the background. We here report on the efficient and specific hyperpolarization of low amounts of a target protein in a large isotope-labeled background by combining dynamic nuclear polarization (DNP) and the selectivity of protein interactions. Using a biradical-labeled ligand, we were able to direct the hyperpolarization to the protein of interest, maintaining comparable signal enhancement with about 400-fold less radicals than conventionally used. We could selectively filter out our target protein directly from crude cell lysate obtained from only 8 mL of fully isotope-enriched cell culture. Our approach offers effective means to study proteins with atomic resolution in increasingly native concentrations and environments. PMID:27351143

  9. 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.

  10. A potent and highly selective peptide substrate for protein kinase C assay.

    PubMed Central

    Toomik, R; Ek, P

    1997-01-01

    Protein kinases exhibit substrate specificities that are often primarily determined by the amino acids around the phosphorylation sites. Peptides corresponding to protein kinase C phosphorylation sites in several different proteins were synthesized on SPOTs membrane which has recently been found to be applicable for studies of protein kinase specificity. After phosphorylation with protein kinase C, we chose the best phosphorylated peptides for the investigation of the importance of amino acids immediately adjacent to the phosphorylation site. The selectivity of the best protein kinase C substrates from this study was analysed with protein kinases A, CK1 and CK2. According to these tests, the most favourable characteristics of SPOTs-membrane-associated peptides were demonstrated by peptide KRAKRKTAKKR. Kinetic analysis of peptide phosphorylation with protein kinase C revealed an apparent Km of 0.49 +/- 0.13 microM and Vmax of 10.0 +/- 0.5 nmol/min per mg with soluble peptide KRAKRKTAKKR. In addition, we assayed several other soluble peptides commonly used as protein kinase C substrates. Peptide KRAKRKTAKKR showed the lowest Km and the highest Vmax/Km value in comparison with peptides FKKSFKL, pEKRPSQRSKYL and KRAKRKTTKKR. Furthermore, of the peptides tested, KRAKRKTAKKR was the most selective substrate for protein kinase C. The favourable kinetic parameters combined with the selectivity should make the KRAKRKTAKKR peptide useful as a substrate for protein kinase C in the assays of both purified enzyme and in crude cell extracts. PMID:9065763

  11. 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

  12. A generative model for protein contact networks.

    PubMed

    Livi, Lorenzo; Maiorino, Enrico; Giuliani, Alessandro; Rizzi, Antonello; Sadeghian, Alireza

    2016-07-01

    In this paper, we present a generative model for protein contact networks (PCNs). The soundness of the proposed model is investigated by focusing primarily on mesoscopic properties elaborated from the spectra of the graph Laplacian. To complement the analysis, we also study the classical topological descriptors, such as statistics of the shortest paths and the important feature of modularity. Our experiments show that the proposed model results in a considerable improvement with respect to two suitably chosen generative mechanisms, mimicking with better approximation real PCNs in terms of diffusion properties elaborated from the normalized Laplacian spectra. However, as well as the other network models, it does not reproduce with sufficient accuracy the shortest paths structure. To compensate this drawback, we designed a second step involving a targeted edge reconfiguration process. The ensemble of reconfigured networks denotes further improvements that are statistically significant. As an important byproduct of our study, we demonstrate that modularity, a well-known property of proteins, does not entirely explain the actual network architecture characterizing PCNs. In fact, we conclude that modularity, intended as a quantification of an underlying community structure, should be considered as an emergent property of the structural organization of proteins. Interestingly, such a property is suitably optimized in PCNs together with the feature of path efficiency. PMID:26474097

  13. Selecting protein families for environmental features based on manifold regularization.

    PubMed

    Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

    2014-06-01

    Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data. PMID:24802701

  14. Selective experimental review of the Standard Model

    SciTech Connect

    Bloom, E.D.

    1985-02-01

    Before disussing experimental comparisons with the Standard Model, (S-M) it is probably wise to define more completely what is commonly meant by this popular term. This model is a gauge theory of SU(3)/sub f/ x SU(2)/sub L/ x U(1) with 18 parameters. The parameters are ..cap alpha../sub s/, ..cap alpha../sub qed/, theta/sub W/, M/sub W/ (M/sub Z/ = M/sub W//cos theta/sub W/, and thus is not an independent parameter), M/sub Higgs/; the lepton masses, M/sub e/, M..mu.., M/sub r/; the quark masses, M/sub d/, M/sub s/, M/sub b/, and M/sub u/, M/sub c/, M/sub t/; and finally, the quark mixing angles, theta/sub 1/, theta/sub 2/, theta/sub 3/, and the CP violating phase delta. The latter four parameters appear in the quark mixing matrix for the Kobayashi-Maskawa and Maiani forms. Clearly, the present S-M covers an enormous range of physics topics, and the author can only lightly cover a few such topics in this report. The measurement of R/sub hadron/ is fundamental as a test of the running coupling constant ..cap alpha../sub s/ in QCD. The author will discuss a selection of recent precision measurements of R/sub hadron/, as well as some other techniques for measuring ..cap alpha../sub s/. QCD also requires the self interaction of gluons. The search for the three gluon vertex may be practically realized in the clear identification of gluonic mesons. The author will present a limited review of recent progress in the attempt to untangle such mesons from the plethora q anti q states of the same quantum numbers which exist in the same mass range. The electroweak interactions provide some of the strongest evidence supporting the S-M that exists. Given the recent progress in this subfield, and particularly with the discovery of the W and Z bosons at CERN, many recent reviews obviate the need for further discussion in this report. In attempting to validate a theory, one frequently searches for new phenomena which would clearly invalidate it. 49 references, 28 figures.

  15. 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

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

    PubMed

    Zhou, Qinhua; Lu, Zhufeng; Cao, Xuebo

    2014-02-01

    We reported the prompt charge selective binding and magnetic separation of mixed proteins by utilizing heterostructured Fe3O4-Na2Ti3O7 nanosheets. Fe3O4-Na2Ti3O7 nanosheets are found to combine a variety of structure and property merits, such as the increased interlayer galleries, exposed exchange sites, flexible framework, and magnetic manipulability. Probing the dissociation dynamics of Na(+) inside the nanosheets reveals that they possess remarkably enhanced Na(+) dissociation capability and the dissociation rate of Na(+) reaches 7.9×10(-)(6)mol g(-)(1)s(-)(1), much superior to titanate nanotubes. In model protein separation experiments, we utilize mixed proteins containing albumin and hemoglobin to assess Fe3O4-Na2Ti3O7 nanosheets. It is found that, by controlling the pH of the sample at 6, positively charged hemoglobin and negatively charged albumin are immediately separated (∼5s) by the nanosheets and the saturated loading capacity of hemoglobin on the nanosheets reaches 4.7±0.61g g(-)(1). Furthermore, hemoglobin bound to the nanosheets can be readily released after buffer wash and is not damaged, while the nanosheets are recyclable and maintain their high efficiency. The outstanding performance of Fe3O4-Na2Ti3O7 nanosheets in separating mixed proteins is attributed to the ultrafast Na(+) dissociation rate, flexible titanate framework, open geometry, and aqueous-like environment to stabilize proteins. These merits, together with the recyclability and cost effectiveness, should make Fe3O4-Na2Ti3O7 nanosheets ideal candidates for biological recognition, isolation, and purification under technologically useful conditions. PMID:24267329

  17. 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

  18. Support Vector Training of Protein Alignment Models

    PubMed Central

    Joachims, Thorsten; Elber, Ron; Pillardy, Jaroslaw

    2008-01-01

    Abstract Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features such as secondary structure, solvent accessibility, or evolutionary information improve sequence to structure alignment accuracy, but conventional generative estimation techniques for alignment models impose independence assumptions that make these features difficult to include in a principled way. In this paper, we overcome this problem using a Support Vector Machine (SVM) method that provides a well-founded way of estimating complex alignment models with hundred of thousands of parameters. Furthermore, we show that the method can be trained using a variety of loss functions. In a rigorous empirical evaluation, the SVM algorithm outperforms the generative alignment method SSALN, a highly accurate generative alignment model that incorporates structural information. The alignment model learned by the SVM aligns 50% of the residues correctly and aligns over 70% of the residues within a shift of four positions. PMID:18707536

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

    PubMed

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

    2016-06-01

    After traumatic brain injury (TBI), secondary injuries develop, including neuroinflammatory processes that contribute to long-lasting impairments. These secondary injuries represent potential targets for treatment and diagnostics. The translocator protein 18 kDa (TSPO) is expressed in activated microglia cells and upregulated in response to brain injury and therefore a potential biomarker of the neuroinflammatory processes. Second-generation radioligands of TSPO, such as [(123)I]CLINDE, have a higher signal-to-noise ratio as the prototype ligand PK11195. [(123)I]CLINDE has been employed in human studies using single-photon emission computed tomography to image the neuroinflammatory response after stroke. In this study, we used the same tracer in a rat model of TBI to determine changes in TSPO expression. Adult Sprague-Dawley rats were subjected to moderate controlled cortical impact injury and sacrificed at 6, 24, 72 h and 28 days post surgery. TSPO expression was assessed in brain sections employing [(123)I]CLINDE in vitro autoradiography. From 24 h to 28 days post surgery, injured animals exhibited a marked and time-dependent increase in [(123)I]CLINDE binding in the ipsilateral motor, somatosensory and parietal cortex, as well as in the hippocampus and thalamus. Interestingly, binding was also significantly elevated in the contralateral M1 motor cortex following TBI. Craniotomy without TBI caused a less marked increase in [(123)I]CLINDE binding, restricted to the ipsilateral hemisphere. Radioligand binding was consistent with an increase in TSPO mRNA expression and CD11b immunoreactivity at the contusion site. This study demonstrates the applicability of [(123)I]CLINDE for detailed regional and quantitative assessment of glial activity in experimental models of TBI. PMID:26969181

  20. Macromolecular Composition Dictates Receptor and G Protein Selectivity of Regulator of G Protein Signaling (RGS) 7 and 9-2 Protein Complexes in Living Cells*

    PubMed Central

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

    2013-01-01

    Regulator of G protein signaling (RGS) proteins play essential roles in the regulation of signaling via G protein-coupled receptors (GPCRs). With hundreds of GPCRs and dozens of G proteins, it is important to understand how RGS regulates selective GPCR-G protein signaling. In neurons of the striatum, two RGS proteins, RGS7 and RGS9-2, regulate signaling by μ-opioid receptor (MOR) and dopamine D2 receptor (D2R) and are implicated in drug addiction, movement disorders, and nociception. Both proteins form trimeric complexes with the atypical G protein β subunit Gβ5 and a membrane anchor, R7BP. In this study, we examined GTPase-accelerating protein (GAP) activity as well as Gα and GPCR selectivity of RGS7 and RGS9-2 complexes in live cells using a bioluminescence resonance energy transfer-based assay that monitors dissociation of G protein subunits. We showed that RGS9-2/Gβ5 regulated both Gi and Go with a bias toward Go, but RGS7/Gβ5 could serve as a GAP only for Go. Interestingly, R7BP enhanced GAP activity of RGS7 and RGS9-2 toward Go and Gi and enabled RGS7 to regulate Gi signaling. Neither RGS7 nor RGS9-2 had any activity toward Gz, Gs, or Gq in the absence or presence of R7BP. We also observed no effect of GPCRs (MOR and D2R) on the G protein bias of R7 RGS proteins. However, the GAP activity of RGS9-2 showed a strong receptor preference for D2R over MOR. Finally, RGS7 displayed an four times greater GAP activity relative to RGS9-2. These findings illustrate the principles involved in establishing G protein and GPCR selectivity of striatal RGS proteins. PMID:23857581

  1. 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

  2. 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. PMID:26118653

  3. 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. PMID:26931646

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

    PubMed

    Rodrigue, Nicolas; Philippe, Hervé; Lartillot, Nicolas

    2010-03-01

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

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  7. [Rapid selection of white clover germplasms' crude protein traits by SPAD and Fourier transform near-infrared reflectance spectroscopy].

    PubMed

    Zhang, Xian; Yan, Rong; Cao, Wen-juan; Shu, Bin; Zhang, Ying-jun

    2009-09-01

    White clover is one of the most important forages in the world, with high nutritive value and crude protein content. Crude protein traits of white clover germplasms was selected using SPAD and near infrared reflectance spectroscopy. The SPAD value was measured by Chlorophyll Meter SPAD-502, and was used to evaluate the crude protein of white clover. In the vegetative period, there was a positive relationship between SPAD value and foliar protein content (y = 0.422x + 4.984, R2 = 0.737), but in the flowering period, there was a negative relationship between the two indexes (y = -0.345x + 37.50, R2 = 0.711). Crude protein content of white clover germplasms was predicted using near infrared reflectance spectroscopy with PLS regression and the model was validated by cross validation and external validation. The results showed that the correlation coefficient of cross validation, the RMSECV, and the correlation coefficient of external validation are 0.904, 0.988%, and 0.987, respectively. NIRS model of white clover crude protein content has good accuracy and precision. FT-NIRS was more accurate than SPAD. NIRS is feasible as a rapid analysis method, and can be used in the selection and breeding of white clover germplasms to improve the breeding efficiency. PMID:19950635

  8. Protease-resistant prions selectively decrease Shadoo protein.

    PubMed

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

    2011-11-01

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

  9. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

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

  10. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

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

  11. 42 CFR 425.600 - Selection of risk model.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

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

  12. Selection of Instructional Materials. A Model Policy and Rules.

    ERIC Educational Resources Information Center

    Bartlett, Larry D.; And Others

    This model prepared by the State of Iowa Department of Public Instruction is intended to provide assistance to schools in developing their own policy and procedures for the selection of library media and text materials. A brief model statement of policy is followed by a model statement of rules which includes (1) responsibility for selection of…

  13. Protein Simulation Data in the Relational Model.

    PubMed

    Simms, Andrew M; Daggett, Valerie

    2012-10-01

    High performance computing is leading to unprecedented volumes of data. Relational databases offer a robust and scalable model for storing and analyzing scientific data. However, these features do not come without a cost-significant design effort is required to build a functional and efficient repository. Modeling protein simulation data in a relational database presents several challenges: the data captured from individual simulations are large, multi-dimensional, and must integrate with both simulation software and external data sites. Here we present the dimensional design and relational implementation of a comprehensive data warehouse for storing and analyzing molecular dynamics simulations using SQL Server. PMID:23204646

  14. Protein Simulation Data in the Relational Model

    PubMed Central

    Simms, Andrew M.; Daggett, Valerie

    2011-01-01

    High performance computing is leading to unprecedented volumes of data. Relational databases offer a robust and scalable model for storing and analyzing scientific data. However, these features do not come without a cost—significant design effort is required to build a functional and efficient repository. Modeling protein simulation data in a relational database presents several challenges: the data captured from individual simulations are large, multi-dimensional, and must integrate with both simulation software and external data sites. Here we present the dimensional design and relational implementation of a comprehensive data warehouse for storing and analyzing molecular dynamics simulations using SQL Server. PMID:23204646

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

    PubMed Central

    2015-01-01

    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

  16. Modeling of protein loops by simulated annealing.

    PubMed Central

    Collura, V.; Higo, J.; Garnier, J.

    1993-01-01

    A method is presented to model loops of protein to be used in homology modeling of proteins. This method employs the ESAP program of Higo et al. (Higo, J., Collura, V., & Garnier, J., 1992, Biopolymers 32, 33-43) and is based on a fast Monte Carlo simulation and a simulated annealing algorithm. The method is tested on different loops or peptide segments from immunoglobulin, bovine pancreatic trypsin inhibitor, and bovine trypsin. The predicted structure is obtained from the ensemble average of the coordinates of the Monte Carlo simulation at 300 K, which exhibits the lowest internal energy. The starting conformation of the loop prior to modeling is chosen to be completely extended, and a closing harmonic potential is applied to N, CA, C, and O atoms of the terminal residues. A rigid geometry potential of Robson and Platt (1986, J. Mol. Biol. 188, 259-281) with a united atom representation is used. This we demonstrate to yield a loop structure with good hydrogen bonding and torsion angles in the allowed regions of the Ramachandran map. The average accuracy of the modeling evaluated on the eight modeled loops is 1 A root mean square deviation (rmsd) for the backbone atoms and 2.3 A rmsd for all heavy atoms. PMID:8401234

  17. Green fluorescent protein as a visual selection marker for papaya (Carica papaya L.) transformation.

    PubMed

    Zhu, Y J; Agbayani, R; Moore, P H

    2004-04-01

    Chemical-based selection for plant transformation is associated with a number of real and perceived problems that might be avoided through visual selection. We have used green fluorescent protein (GFP), as a visual selectable marker to produce transformed papaya ( Carica papaya) plants following microprojectile bombardment of embryogenic callus. GFP selection reduced the selection time from 3 months on a geneticin (G418) antibiotic-containing medium to 3-4 weeks. Moreover, GFP selection increased the number of transformed papaya plants by five-to eightfold compared to selection in the presence of antibiotics. Overall, the use of GFP for selecting transgenic papaya lines improved our throughput for transformation by 15- to 24-fold while avoiding the drawbacks associated with the use of antibiotic resistance-based selection markers. PMID:14749892

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

    PubMed

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

    2011-09-20

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

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

    PubMed

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

    2011-01-01

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

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

    PubMed

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

    2011-01-01

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

  1. Selecting Optimum Eukaryotic Integral Membrane Proteins for Structure Determination by Rapid Expression and Solubilization Screening

    PubMed Central

    Li, Min; Hays, Franklin A.; Roe-Zurz, Zygy; Vuong, Linda; Kelly, Libusha; Ho, Chi-Min; Robbins, Renée M.; Pieper, Ursula; O’Connell, Joseph D.; Miercke, Larry J. W.; Giacomini, Kathleen M.; Sali, Andrej; Stroud, Robert M.

    2009-01-01

    A medium throughput approach is used to rapidly identify membrane proteins from a eukaryotic organism that are most amenable to expression in amounts and quality adequate to support structure determination. The goal was to expand knowledge of new membrane protein structures based on proteome-wide coverage. In the first phase membrane proteins from the budding yeast Saccharomyces cerevisiae were selected for homologous expression in S. cerevisiae, a system that can be adapted to expression of membrane proteins from other eukaryotes. We performed medium-scale expression and solubilization tests on 351 rationally selected membrane proteins from the budding yeast Saccharomyces cerevisiae. These targets are inclusive of all annotated and unannotated membrane protein families within the organism’s membrane proteome. 272 targets were expressed and of these 234 solubilized in the detergent n-dodecyl-β-D-maltopyranoside. Furthermore, we report the identity of a subset of targets that were purified to homogeneity to facilitate structure determinations. The extensibility of this approach is demonstrated with the expression of ten human integral membrane proteins from the solute carrier superfamily (SLC). This discovery-oriented pipeline provides an efficient way to select proteins from particular membrane protein classes, families, or organisms that may be more suited to structure analysis than others. PMID:19061901

  2. 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

  3. sDFIRE: Sequence-specific statistical energy function for protein structure prediction by decoy selections.

    PubMed

    Hoque, Md Tamjidul; Yang, Yuedong; Mishra, Avdesh; Zhou, Yaoqi

    2016-05-01

    An important unsolved problem in molecular and structural biology is the protein folding and structure prediction problem. One major bottleneck for solving this is the lack of an accurate energy to discriminate near-native conformations against other possible conformations. Here we have developed sDFIRE energy function, which is an optimized linear combination of DFIRE (the Distance-scaled Finite Ideal gas Reference state based Energy), the orientation dependent (polar-polar and polar-nonpolar) statistical potentials, and the matching scores between predicted and model structural properties including predicted main-chain torsion angles and solvent accessible surface area. The weights for these scoring terms are optimized by three widely used decoy sets consisting of a total of 134 proteins. Independent tests on CASP8 and CASP9 decoy sets indicate that sDFIRE outperforms other state-of-the-art energy functions in selecting near native structures and in the Pearson's correlation coefficient between the energy score and structural accuracy of the model (measured by TM-score). © 2016 Wiley Periodicals, Inc. PMID:26849026

  4. Course 3: Modelling Motor Protein Systems

    NASA Astrophysics Data System (ADS)

    Duke, T.

    Contents 1 Making a move: Principles of energy transduction 1.1 Motor proteins and Carnot engines 1.2 Simple Brownian ratchet 1.3 Polymerization ratchet 1.4 Isothermal ratchets 1.5 Motor proteins as isothermal ratchets 1.6 Design principles for effective motors 2 Pulling together: Mechano-chemical model of actomyosin 2.1 Swinging lever-arm model 2.2 Mechano-chemical coupling 2.3 Equivalent isothermal ratchet 2.4 Many motors working together 2.5 Designed to work 2.6 Force-velocity relation 2.7 Dynamical instability and biochemical synchronization 2.8 Transient response ofmuscle 3 Motors at work: Collective properties of motor proteins 3.1 Dynamical instabilities 3.2 Bidirectional movement 3.3 Critical behaviour 3.4 Oscillations 3.5 Dynamic buckling instability 3.6 Undulation of flagella 4 Sense and sensitivity: Mechano-sensation in hearing 4.1 System performance 4.2 Mechano-sensors: Hair bundles 4.3 Active amplification 4.4 Self-tuned criticality 4.5 Motor-driven oscillations 4.6 Channel compliance and relaxation oscillations 4.7 Channel-driven oscillations 4.8 Hearing at the noise limit

  5. Markov state models of protein misfolding.

    PubMed

    Sirur, Anshul; De Sancho, David; Best, Robert B

    2016-02-21

    Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity. PMID:26897000

  6. Markov state models of protein misfolding

    NASA Astrophysics Data System (ADS)

    Sirur, Anshul; De Sancho, David; Best, Robert B.

    2016-02-01

    Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

  7. Cognitive Niches: An Ecological Model of Strategy Selection

    ERIC Educational Resources Information Center

    Marewski, Julian N.; Schooler, Lael J.

    2011-01-01

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

  8. HABITAT MODELING APPROACHES FOR RESTORATION SITE SELECTION

    EPA Science Inventory

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

  9. Patterns of Neutral Diversity Under General Models of Selective Sweeps

    PubMed Central

    Coop, Graham; Ralph, Peter

    2012-01-01

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

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

    PubMed

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

    1996-05-01

    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. PMID:8653201

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

    PubMed

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

    2016-09-01

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

  12. A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting.

    PubMed

    Wiśniewski, Jacek R; Mann, Matthias

    2016-07-01

    Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system. PMID:27297043

  13. Selection in the rapid evolution of gamete recognition proteins in marine invertebrates.

    PubMed

    Vacquier, Victor D; Swanson, Willie J

    2011-11-01

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

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

    PubMed Central

    Vacquier, Victor D.; Swanson, Willie J.

    2011-01-01

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

  15. Molecularly imprinted plasmonic nanosensor for selective SERS detection of protein biomarkers.

    PubMed

    Lv, Yongqin; Qin, Yating; Svec, Frantisek; Tan, Tianwei

    2016-06-15

    Molecularly imprinted plasmonic nanosensor has been prepared via the rational design of an ultrathin polymer layer on the surface of gold nanorods imprinted with the target protein. This nanosensor enabled selective fishing-out of the target protein biomarker even from a complex real sample such as human serum. Sensitive SERS detection of the protein biomarkers with a strong Raman enhancement was achieved by formation of protein imprinted gold nanorods aggregates, stacking of protein imprinted gold nanorods onto a glass plate, or self-assembly of protein imprinted gold nanorods into close-packed array. High specificity and sensitivity of this method were demonstrated with a detection limit of at least 10(-8)mol/L for the target protein. This could provide a promising alternative for the currently used immunoassays and fluorescence detection, and offer an ultrasensitive, non-destructive, and label-free technique for clinical diagnosis applications. PMID:26874111

  16. The unfolded protein response selectively targets active smoothened mutants.

    PubMed

    Marada, Suresh; Stewart, Daniel P; Bodeen, William J; Han, Young-Goo; Ogden, Stacey K

    2013-06-01

    The Hedgehog signaling pathway, an essential regulator of developmental patterning, has been implicated in playing causative and survival roles in a range of human cancers. The signal-transducing component of the pathway, Smoothened, has revealed itself to be an efficacious therapeutic target in combating oncogenic signaling. However, therapeutic challenges remain in cases where tumors acquire resistance to Smoothened antagonists, and also in cases where signaling is driven by active Smoothened mutants that exhibit reduced sensitivity to these compounds. We previously demonstrated that active Smoothened mutants are subjected to prolonged endoplasmic reticulum (ER) retention, likely due to their mutations triggering conformation shifts that are detected by ER quality control. We attempted to exploit this biology and demonstrate that deregulated Hedgehog signaling driven by active Smoothened mutants is specifically attenuated by ER stressors that induce the unfolded protein response (UPR). Upon UPR induction, active Smoothened mutants are targeted by ER-associated degradation, resulting in attenuation of inappropriate pathway activity. Accordingly, we found that the UPR agonist thapsigargin attenuated mutant Smoothened-induced phenotypes in vivo in Drosophila melanogaster. Wild-type Smoothened and physiological Hedgehog patterning were not affected, suggesting that UPR modulation may provide a novel therapeutic window to be evaluated for targeting active Smoothened mutants in disease. PMID:23572559

  17. Ion selectivity of the anthrax toxin channel and its effect on protein translocation

    PubMed Central

    Anderson, Damon; Finkelstein, Alan

    2015-01-01

    Anthrax toxin consists of three ∼85-kD proteins: lethal factor (LF), edema factor (EF), and protective antigen (PA). PA63 (the 63-kD, C-terminal portion of PA) forms heptameric channels ((PA63)7) in planar phospholipid bilayer membranes that enable the translocation of LF and EF across the membrane. These mushroom-shaped channels consist of a globular cap domain and a 14-stranded β-barrel stem domain, with six anionic residues lining the interior of the stem to form rings of negative charges. (PA63)7 channels are highly cation selective, and, here, we investigate the effects on both cation selectivity and protein translocation of mutating each of these anionic residues to a serine. We find that although some of these mutations reduce cation selectivity, selectivity alone does not directly predict the rate of protein translocation; local changes in electrostatic forces must be considered as well. PMID:26170174

  18. 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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2016-10-01

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

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

    PubMed

    Buksa, Krzysztof

    2016-09-01

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

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

    PubMed

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

    2015-02-01

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

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

    PubMed Central

    Stoltenburg, Regina; Schubert, Thomas; Strehlitz, Beate

    2015-01-01

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

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

    PubMed

    Stoltenburg, Regina; Schubert, Thomas; Strehlitz, Beate

    2015-01-01

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

  5. 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.

  6. Model Selection for Monitoring CO2 Plume during Sequestration

    Energy Science and Technology Software Center (ESTSC)

    2014-12-31

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

  7. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-02-03

    The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the DB and BDB accidents to be used in the future study.

  8. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the Design Basis and Beyond Design Basis accidents to be used in the future study.

  9. 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…

  10. 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.

  11. 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

  12. 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%.

  13. 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.

  14. 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

  15. Fast Geometric Consensus Approach for Protein Model Quality Assessment

    PubMed Central

    Adamczak, Rafal; Pillardy, Jaroslaw; Vallat, Brinda K.

    2011-01-01

    Abstract Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well. PMID:21244273

  16. 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

  17. 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

  18. Pathophysiological Progression Model for Selected Toxicological Endpoints

    EPA Science Inventory

    The existing continuum paradigms are effective models to organize toxicological data associated with endpoints used in human health assessments. A compendium of endpoints characterized along a pathophysiological continuum would serve to: weigh the relative importance of effects o...

  19. 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.

  20. Deviance statistics in model fit and selection in ROC studies

    NASA Astrophysics Data System (ADS)

    Lei, Tianhu; Bae, K. Ty

    2013-03-01

    A general non-linear regression model-based Bayesian inference approach is used in our ROC (Receiver Operating Characteristics) study. In the sampling of posterior distribution, two prior models - continuous Gaussian and discrete categorical - are used for the scale parameter. How to judge Goodness-of-Fit (GOF) of each model and how to criticize these two models, Deviance statistics and Deviance information criterion (DIC) are adopted to address these problems. Model fit and model selection focus on the adequacy of models. Judging model adequacy is essentially measuring agreement of model and observations. Deviance statistics and DIC provide overall measures on model fit and selection. In order to investigate model fit at each category of observations, we find that the cumulative, exponential contributions from individual observations to Deviance statistics are good estimates of FPF (false positive fraction) and TPF (true positive fraction) on which the ROC curve is based. This finding further leads to a new measure for model fit, called FPF-TPF distance, which is an Euclidean distance defined on FPF-TPF space. It combines both local and global fitting. Deviance statistics and FPFTPF distance are shown to be consistent and in good agreement. Theoretical derivation and numerical simulations for this new method for model fit and model selection of ROC data analysis are included. Keywords: General non-linear regression model, Bayesian Inference, Markov Chain Monte Carlo (MCMC) method, Goodness-of-Fit (GOF), Model selection, Deviance statistics, Deviance information criterion (DIC), Continuous conjugate prior, Discrete categorical prior. ∗

  1. Python Program to Select HII Region Models

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  2. 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

  3. Evolution of Protein Quaternary Structure in Response to Selective Pressure for Increased Thermostability.

    PubMed

    Fraser, Nicholas J; Liu, Jian-Wei; Mabbitt, Peter D; Correy, Galen J; Coppin, Chris W; Lethier, Mathilde; Perugini, Matthew A; Murphy, James M; Oakeshott, John G; Weik, Martin; Jackson, Colin J

    2016-06-01

    Oligomerization has been suggested to be an important mechanism for increasing or maintaining the thermostability of proteins. Although it is evident that protein-protein contacts can result in substantial stabilization in many extant proteins, evidence for evolutionary selection for oligomerization is largely indirect and little is understood of the early steps in the evolution of oligomers. A laboratory-directed evolution experiment that selected for increased thermostability in the αE7 carboxylesterase from the Australian sheep blowfly, Lucilia cuprina, resulted in a thermostable variant, LcαE7-4a, that displayed increased levels of dimeric and tetrameric quaternary structure. A trade-off between activity and thermostability was made during the evolution of thermostability, with the higher-order oligomeric species displaying the greatest thermostability and lowest catalytic activity. Analysis of monomeric and dimeric LcαE7-4a crystal structures revealed that only one of the oligomerization-inducing mutations was located at a potential protein-protein interface. This work demonstrates that by imposing a selective pressure demanding greater thermostability, mutations can lead to increased oligomerization and stabilization, providing support for the hypothesis that oligomerization is a viable evolutionary strategy for protein stabilization. PMID:27016206

  4. Human self protein CD8+ T cell epitopes are both positively and negatively selected

    PubMed Central

    almani, Michal; Raffaeli, Shai; Vider-Shalit, Tal; Tsaban, Lea; Fishbain, Vered; Louzoun, Yoram

    2009-01-01

    The cellular immune system recognizes self epitopes in the context of MHC-I molecules. The immunological general view presumes that these self epitopes are just a background, both positively and negatively selecting T cells. We here estimate the number of epitopes in each human protein for many frequent HLA alleles, and a score representing over or under presentation of epitopes on these proteins. We further show that there is a clear selection for the presentation of specific self proteins types. Proteins presenting many epitopes include for example AIRE upregulated Tissue specific antigens, immune system receptors and proteins with a high expression level. On the other hand, proteins that may be considered less “useful” for the immune system, such as low expression level proteins, are under presented. We combine our epitope estimate with SNP measures to show that this selection can be directly observed through the fraction of non-synonymous SNPs (replacement fraction), which is significantly higher inside epitopes than outside PMID:19291702

  5. Human self-protein CD8+ T-cell epitopes are both positively and negatively selected.

    PubMed

    Almani, Michal; Raffaeli, Shai; Vider-Shalit, Tal; Tsaban, Lea; Fishbain, Vered; Louzoun, Yoram

    2009-04-01

    The cellular immune system recognizes self-epitopes in the context of MHC-I molecules. The immunological general view presumes that these self-epitopes are just a background, both positively and negatively selecting T cells. We here estimate the number of epitopes in each human protein for many frequent HLA alleles, and a score representing over or under presentation of epitopes on these proteins. We further show that there is a clear selection for the presentation of specific self-protein types. Proteins presenting many epitopes include, for example, autoimmune regulator (AIRE) upregulated tissue-specific antigens, immune system receptors and proteins with a high expression level. On the other hand, proteins that may be considered less "useful" for the immune system, such as low expression level proteins, are under-presented. We combine our epitope estimate with single nucleotide polymorphism (SNP) measures to show that this selection can be directly observed through the fraction of non-synonymous SNP (replacement fraction), which is significantly higher inside epitopes than outside. PMID:19291702

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

    PubMed Central

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

    1993-01-01

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

  7. Cholinergic dysregulation produced by selective inactivation of the dystonia-associated protein TorsinA

    PubMed Central

    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.

    2012-01-01

    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 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. PMID:22579992

  8. 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

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

    PubMed Central

    2012-01-01

    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; pI = 4.65) and lysozyme (LYZ; 14.3 kDa; pI = 11) were shown at the pH values corresponding to their own pI 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. PMID:22650609

  10. The unfolded protein response triggers selective mRNA release from the endoplasmic reticulum.

    PubMed

    Reid, David W; Chen, Qiang; Tay, Angeline S-L; Shenolikar, Shirish; Nicchitta, Christopher V

    2014-09-11

    The unfolded protein response (UPR) is a stress response program that reprograms cellular translation and gene expression in response to proteotoxic stress in the endoplasmic reticulum (ER). One of the primary means by which the UPR alleviates this stress is by reducing protein flux into the ER via a general suppression of protein synthesis and ER-specific mRNA degradation. We report here an additional UPR-induced mechanism for the reduction of protein flux into the ER, where mRNAs that encode signal sequences are released from the ER to the cytosol. By removing mRNAs from the site of translocation, this mechanism may serve as a potent means to transiently reduce ER protein folding load and restore proteostasis. These findings identify the dynamic subcellular localization of mRNAs and translation as a selective and rapid regulatory feature of the cellular response to protein folding stress. PMID:25215492

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

    PubMed

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

    2016-01-01

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

  12. 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.

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

    PubMed Central

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

    2015-01-01

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

  14. Protein surface topology-probing by selective chemical modification and mass spectrometric peptide mapping.

    PubMed Central

    Suckau, D; Mak, M; Przybylski, M

    1992-01-01

    Aminoacetylation of lysine residues and the modification of arginine by 1,2-cyclohexanedione to N7,N8-(dihydroxy-1,2-cyclohexylidene)arginine were used for probing the surface topology of hen-eggwhite lysozyme as a model protein. The molecular identification of lysine and arginine modification sites was provided by molecular weight determinations of modified and unmodified tryptic peptide mixtures (peptide mapping) using 252Cf plasma desorption mass spectrometry. At conditions of limited chemical modification, mass-spectrometric peptide-mapping analyses of lysozyme derivatives enabled the direct assignment of relative reactivities of lysine and arginine residues at different reaction times and reagent concentrations. The relative reactivities of lysine residues showed a direct correlation with their surface accessibilities from x-ray structure data. For the reaction with 1,2-cyclohexanedione, a selective modification at Arg-5, -125, -112, and -73 was identified, and an inverse correlation of relative reactivities with the surface accessibility ratios of the N7- and the N8-guanidino functions was obtained. By examination of the x-ray structural data of lysozyme, this selective modification was attributed to intramolecular catalysis because of the presence of neighboring proton acceptor groups, such as the Asp-119 carboxylate group for Arg-125 and the Trp-123 and Arg-125 carbonyl groups for Arg-5. PMID:1608973

  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. 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.

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

    PubMed

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

    2016-06-22

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

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

    PubMed Central

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

    2014-01-01

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

  19. 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

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

    PubMed

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

    2016-01-01

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

  1. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

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

  2. Transcriptional Profiling of a Selective CREB Binding Protein Bromodomain Inhibitor Highlights Therapeutic Opportunities.

    PubMed

    Chekler, Eugene L Piatnitski; Pellegrino, Jessica A; Lanz, Thomas A; Denny, R Aldrin; Flick, Andrew C; Coe, Jotham; Langille, Jonathan; Basak, Arindrajit; Liu, Shenping; Stock, Ingrid A; Sahasrabudhe, Parag; Bonin, Paul D; Lee, Kevin; Pletcher, Mathew T; Jones, Lyn H

    2015-12-17

    Bromodomains are involved in transcriptional regulation through the recognition of acetyl lysine modifications on diverse proteins. Selective pharmacological modulators of bromodomains are lacking, although the largely hydrophobic nature of the pocket makes these modules attractive targets for small-molecule inhibitors. This work describes the structure-based design of a highly selective inhibitor of the CREB binding protein (CBP) bromodomain and its use in cell-based transcriptional profiling experiments. The inhibitor downregulated a number of inflammatory genes in macrophages that were not affected by a selective BET bromodomain inhibitor. In addition, the CBP bromodomain inhibitor modulated the mRNA level of the regulator of G-protein signaling 4 (RGS4) gene in neurons, suggesting a potential therapeutic opportunity for CBP inhibitors in the treatment of neurological disorders. PMID:26670081

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

    PubMed Central

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

    2011-01-01

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

  4. Lamina-associated Polypeptide 1: Protein Interactions and Tissue-selective Functions

    PubMed Central

    Shin, Ji-Yeon; Dauer, William T.; Worman, Howard J.

    2014-01-01

    Mutations in genes encoding widely expressed nuclear envelope proteins often lead to diseases that manifest in specific tissues. Lamina-associated polypeptide 1 (LAP1) is an integral protein of the inner nuclear membrane that is expressed in most cells and tissues. Within the nuclear envelope, LAP1 interacts physically with lamins, torsinA and emerin, suggesting it may serve as a key node for transducing signals across the inner nuclear membrane. Indeed, recent in vivo studies in genetically modified mice strongly support functional links between LAP1 and both torsinA (in neurons) and emerin (in muscle). These studies suggest that tissue-selective diseases caused by mutations in genes encoding nuclear envelope proteins may result, at least in part, from the selective disruption of discrete nuclear envelope protein complexes. PMID:24508913

  5. Selective and Reversible Photochemical Derivatization of Cysteine Residues in Peptides and Proteins.

    PubMed

    Arumugam, Selvanathan; Guo, Jun; Mbua, Ngalle Eric; Friscourt, Frédéric; Lin, Nannan; Nekongo, Emmanuel; Boons, Geert-Jan; Popik, Vladimir V

    2014-04-01

    Selective derivatization of solvent-exposed cysteine residues in peptides and proteins is achieved by brief irradiation of an aqueous solution containing 3-(hydroxymethyl)-2-naphthol derivatives (NQMPs) with 350 nm fluorescent lamp. NQMP can be conjugated with various moieties, such as PEG, dyes, carbohydrates, or possess a fragment for further selective derivatization, e.g., biotin, azide, alkyne, etc. Attractive features of this labeling approach include an exceptionally fast rate of the reaction and a requirement for low equivalence of the reagent. The NQMP-thioether linkage is stable under ambient conditions, survives protein digestion and MS analysis. Irradiation of NQMP-labeled protein in a dilute solution (<40 μM) or in the presence of a vinyl ether results in a traceless release of the substrate. The reversible biotinylation of bovine serum albumin, as well as capture and release of this protein using NeutrAvidin Agarose resin beads has been demonstrated. PMID:24765521

  6. Global analysis of cellular protein flux quantifies the selectivity of basal autophagy.

    PubMed

    Zhang, Tian; Ghaemmaghami, Sina

    2016-08-01

    In eukaryotic cells, the macroautophagy pathway has been implicated in the degradation of long-lived proteins and damaged organelles. Although it has been demonstrated that macroautophagy can selectively degrade specific targets, its contribution to the basal turnover of cellular proteins had previously not been quantified on proteome-wide scales. In a recent study, we utilized dynamic proteomics to provide a global comparison of protein half-lives between wild-type and autophagy-deficient cells. Our results indicated that in quiescent fibroblasts, macroautophagy contributes to the basal turnover of a substantial fraction of the proteome. However, the contribution of macroautophagy to constitutive protein turnover is variable within the proteome. The methodology outlined in the study provides a global strategy for quantifying the selectivity of basal macroautophagy. PMID:27248575

  7. Selectivity analysis of single binder assays used in plasma protein profiling

    PubMed Central

    Neiman, Maja; Fredolini, Claudia; Johansson, Henrik; Lehtiö, Janne; Nygren, Per-Åke; Uhlén, Mathias; Nilsson, Peter; Schwenk, Jochen M

    2013-01-01

    The increasing availability of antibodies toward human proteins enables broad explorations of the proteomic landscape in cells, tissues, and body fluids. This includes assays with antibody suspension bead arrays that generate protein profiles of plasma samples by flow cytometer analysis. However, antibody selectivity is context dependent so it is necessary to corroborate on-target detection over off-target binding. To address this, we describe a concept to directly verify interactions from antibody-coupled beads by analysis of their eluates by Western blots and MS. We demonstrate selective antibody binding in complex samples with antibodies toward a set of chosen proteins with different abundance in plasma and serum, and illustrate the need to adjust sample and bead concentrations accordingly. The presented approach will serve as an important tool for resolving differential protein profiles from antibody arrays within plasma biomarker discoveries. PMID:24151238

  8. Modeling selective intergranular oxidation of binary alloys.

    PubMed

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

    2015-01-01

    Intergranular attack of alloys under hydrothermal conditions is a complex problem that depends on metal and oxygen transport kinetics via solid-state and channel-like pathways to an advancing oxidation front. Experiments reveal very different rates of intergranular attack and minor element depletion distances ahead of the oxidation front for nickel-based binary alloys depending on the minor element. For example, a significant Cr depletion up to 9 μm ahead of grain boundary crack tips was documented for Ni-5Cr binary alloy, in contrast to relatively moderate Al depletion for Ni-5Al (∼100 s of nm). We present a mathematical kinetics model that adapts Wagner's model for thick film growth to intergranular attack of binary alloys. The transport coefficients of elements O, Ni, Cr, and Al in bulk alloys and along grain boundaries were estimated from the literature. For planar surface oxidation, a critical concentration of the minor element can be determined from the model where the oxide of minor element becomes dominant over the major element. This generic model for simple grain boundary oxidation can predict oxidation penetration velocities and minor element depletion distances ahead of the advancing front that are comparable to experimental data. The significant distance of depletion of Cr in Ni-5Cr in contrast to the localized Al depletion in Ni-5Al can be explained by the model due to the combination of the relatively faster diffusion of Cr along the grain boundary and slower diffusion in bulk grains, relative to Al. PMID:25573575

  9. Reconstitution of Membrane Proteins into Model Membranes: Seeking Better Ways to Retain Protein Activities

    PubMed Central

    Shen, Hsin-Hui; Lithgow, Trevor; Martin, Lisandra L.

    2013-01-01

    The function of any given biological membrane is determined largely by the specific set of integral membrane proteins embedded in it, and the peripheral membrane proteins attached to the membrane surface. The activity of these proteins, in turn, can be modulated by the phospholipid composition of the membrane. The reconstitution of membrane proteins into a model membrane allows investigation of individual features and activities of a given cell membrane component. However, the activity of membrane proteins is often difficult to sustain following reconstitution, since the composition of the model phospholipid bilayer differs from that of the native cell membrane. This review will discuss the reconstitution of membrane protein activities in four different types of model membrane—monolayers, supported lipid bilayers, liposomes and nanodiscs, comparing their advantages in membrane protein reconstitution. Variation in the surrounding model environments for these four different types of membrane layer can affect the three-dimensional structure of reconstituted proteins and may possibly lead to loss of the proteins activity. We also discuss examples where the same membrane proteins have been successfully reconstituted into two or more model membrane systems with comparison of the observed activity in each system. Understanding of the behavioral changes for proteins in model membrane systems after membrane reconstitution is often a prerequisite to protein research. It is essential to find better solutions for retaining membrane protein activities for measurement and characterization in vitro. PMID:23344058

  10. Affinity chromatographic selection of carbonylated proteins followed by identification of oxidation sites using tandem mass spectrometry.

    PubMed

    Mirzaei, Hamid; Regnier, Fred

    2005-04-15

    It has been shown that oxidatively modified forms of proteins accumulate during oxidative stress, aging, and in some age-related diseases. One of the unique features of a wide variety of routes by which proteins are oxidized is the generation of carbonyl groups. This paper reports a method for the isolation of oxidized proteins, which involves (1) biotinylation of oxidized proteins with biotin hydrazide and (2) affinity enrichment using monomeric avidin affinity chromatography columns. The selectivity of the method was validated by adding in vitro oxidized biotinylated BSA to a yeast lysate and showing that the predominant protein recovered was BSA. This method was applied to the question of whether large doses of 2-nitropropane produce oxidized proteins. A study of rat liver homogenates showed that animals dosed with 2-nitropropane produced 17 times more oxidized protein than controls in 6 h. Tryptic digestion of these oxidized proteins followed by reversed-phase chromatography and tandem mass spectrometry led to the identification of 14 peptides and their parent proteins. Nine of the 14 identified peptides were found to carry 1 or 2 oxidation sites and 5 of the 9 peptides were biotinylated. The significance of this affinity method is that it allows the isolation of oxidized proteins from the rest of the proteome and facilitates their identification. In some cases, it is even possible to identify the site of oxidation. PMID:15828771

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

    PubMed

    Gupta, Aditi; Adami, Christoph

    2016-03-01

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

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

    ERIC Educational Resources Information Center

    Nelson, Allan; Goetze, Jim

    2004-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  14. 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.

  15. 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.

  16. 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

  17. flankr: An R package implementing computational models of attentional selectivity.

    PubMed

    Grange, James A

    2016-06-01

    The Eriksen flanker task (Eriksen and Eriksen, Perception & Psychophysics, 16, 143-149, 1974) is a classic test in cognitive psychology of visual selective attention. Two recent computational models have formalised the dynamics of the apparent increasing attentional selectivity during stimulus processing, but with very different theoretical underpinnings: The shrinking spotlight (SSP) model (White et al., Cognitive Psychology, 210-238, 2011) assumes attentional selectivity improves in a gradual, continuous manner; the dual stage two phase (DSTP) model (Hübner et al., Psychological Review, 759-784, 2010) assumes attentional selectivity changes from a low- to a high-mode of selectivity at a discrete time-point. This paper presents an R package-flankr-that instantiates both computational models. flankr allows the user to simulate data from both models, and to fit each model to human data. flankr provides statistics of the goodness-of-fit to human data, allowing users to engage in competitive model comparison of the DSTP and the SSP models on their own data. It is hoped that the utility of flankr lies in allowing more researchers to engage in the important issue of the dynamics of attentional selectivity. PMID:26174713

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

    PubMed

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

    2013-01-01

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

  19. A Protocol for Phage Display and Affinity Selection Using Recombinant Protein Baits

    PubMed Central

    Kushwaha, Rekha; Schäfermeyer, Kim R.; Downie, A. Bruce

    2014-01-01

    Using recombinant phage as a scaffold to present various protein portions encoded by a directionally cloned cDNA library to immobilized bait molecules is an efficient means to discover interactions. The technique has largely been used to discover protein-protein interactions but the bait molecule to be challenged need not be restricted to proteins. The protocol presented here has been optimized to allow a modest number of baits to be screened in replicates to maximize the identification of independent clones presenting the same protein. This permits greater confidence that interacting proteins identified are legitimate interactors of the bait molecule. Monitoring the phage titer after each affinity selection round provides information on how the affinity selection is progressing as well as on the efficacy of negative controls. One means of titering the phage, and how and what to prepare in advance to allow this process to progress as efficiently as possible, is presented. Attributes of amplicons retrieved following isolation of independent plaque are highlighted that can be used to ascertain how well the affinity selection has progressed. Trouble shooting techniques to minimize false positives or to bypass persistently recovered phage are explained. Means of reducing viral contamination flare up are discussed. PMID:24637694

  20. 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.

  1. 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.

  2. 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

  3. Modelling three-dimensional protein structures for applications in drug design

    PubMed Central

    Schmidt, Tobias; Bergner, Andreas; Schwede, Torsten

    2013-01-01

    A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided. PMID:24216321

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

    PubMed Central

    Wise, K S; Kim, M F

    1987-01-01

    Surface protein antigens of Mycoplasma hyopneumoniae were identified by direct antibody-surface binding or by radioimmunoprecipitation of surface 125I-labeled proteins with a series of monoclonal antibodies (MAbs). Surface proteins p70, p65, p50, and p44 were shown to be integral membrane components by selective partitioning into the hydrophobic phase during Triton X-114 (TX-114)-phase fractionation, whereas p41 was concomitantly identified as a surface protein exclusively partitioning into the aqueous phase. Radioimmunoprecipitation of TX-114-phase proteins from cells labeled with [35S]methionine, 14C-amino acids, or [3H] palmitic acid showed that proteins p65, p50, and p44 were abundant and (with one other hydrophobic protein, p60) were selectively labeled with lipid. Covalent lipid attachment was established by high-performance liquid chromatography identification of [3H]methyl palmitate after acid methanolysis of delipidated proteins. An additional, unidentified methanolysis product suggested conversion of palmitate to another form of lipid also attached to these proteins. 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 larger 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. These studies establish that a highly restricted set of distinct, lipid

  5. Selecting Research Collections for Digitization: Applying the Harvard Model.

    ERIC Educational Resources Information Center

    Brancolini, Kristine R.

    2000-01-01

    Librarians at Harvard University have written the most comprehensive guide to selecting research collections for digitization. This article applies the Harvard Model to a digitization project at Indiana University in order to evaluate the appropriateness of the model for use at another institution and to adapt the model to local needs. (Contains 7…

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

    ERIC Educational Resources Information Center

    Petersen, Nancy S.; Novick, Melvin R.

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

  7. 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…

  8. 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)

  9. 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…

  10. 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…

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

    PubMed

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

    2015-09-01

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

  12. Use of hydrostatic pressure for modulation of protein chemical modification and enzymatic selectivity.

    PubMed

    Makarov, Alexey A; Helmy, Roy; Joyce, Leo; Reibarkh, Mikhail; Maust, Mathew; Ren, Sumei; Mergelsberg, Ingrid; Welch, Christopher J

    2016-05-11

    Using hydrostatic pressure to induce protein conformational changes can be a powerful tool for altering the availability of protein reactive sites and for changing the selectivity of enzymatic reactions. Using a pressure apparatus, it has been demonstrated that hydrostatic pressure can be used to modulate the reactivity of lysine residues of the protein ubiquitin with a water-soluble amine-specific homobifunctional coupling agent. Fewer reactive lysine residues were observed when the reaction was carried out under elevated pressure of 3 kbar, consistent with a pressure-induced conformational change of ubiquitin that results in fewer exposed lysine residues. Additionally, modulation of the stereoselectivity of an enzymatic transamination reaction was observed at elevated hydrostatic pressure. In one case, the minor diasteromeric product formed at atmospheric pressure became the major product at elevated pressure. Such pressure-induced alterations of protein reactivity may provide an important new tool for enzymatic reactions and the chemical modification of proteins. PMID:27088756

  13. 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.

  14. Ecohydrological model parameter selection for stream health evaluation.

    PubMed

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

    2015-04-01

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

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

    PubMed

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

    1991-10-15

    A laboratory-selected colony of Heliothis virescens displaying a 20- to 70-fold level of resistance to Bacillus thuringiensis proteins was evaluated to identify mechanism(s) of resistance. Brush-border membrane vesicles were isolated from larval midgut epithelium from the susceptible and resistant strains of H. virescens. Two B. thuringiensis proteins, CryIA(b) and CryIA(c), were iodinated and shown to specifically bind to brush-border membrane vesicles of both insect strains. Multiple changes in the receptor-binding parameters were seen in the resistant strain as compared with the susceptible strain. A 2- to 4-fold reduction in binding affinity was accompanied by a 4- to 6-fold increase in binding-site concentration for both proteins. Although these two B. thuringiensis proteins competed for the same high-affinity binding site, competition experiments revealed different receptor specificity toward these proteins in the resistant H. virescens line. The H. virescens strains were not sensitive to a coleopteran-active protein, CryIIIA, nor did these proteins compete with the CryIA proteins for binding. Complexity of the mechanism of resistance is consistent with the complex mode of action of B. thuringiensis proteins. PMID:1924353

  16. The different roles of selective autophagic protein degradation in mammalian cells

    PubMed Central

    Wang, Da-wei; Peng, Zhen-ju; Ren, Guang-fang; Wang, Guang-xin

    2015-01-01

    Autophagy is an intracellular pathway for bulk protein degradation and the removal of damaged organelles by lysosomes. Autophagy was previously thought to be unselective; however, studies have increasingly confirmed that autophagy-mediated protein degradation is highly regulated. Abnormal autophagic protein degradation has been associated with multiple human diseases such as cancer, neurological disability and cardiovascular disease; therefore, further elucidation of protein degradation by autophagy may be beneficial for protein-based clinical therapies. Macroautophagy and chaperone-mediated autophagy (CMA) can both participate in selective protein degradation in mammalian cells, but the process is quite different in each case. Here, we summarize the various types of macroautophagy and CMA involved in determining protein degradation. For this summary, we divide the autophagic protein degradation pathways into four categories: the post-translational modification dependent and independent CMA pathways and the ubiquitin dependent and independent macroautophagy pathways, and describe how some non-canonical pathways and modifications such as phosphorylation, acetylation and arginylation can influence protein degradation by the autophagy lysosome system (ALS). Finally, we comment on why autophagy can serve as either diagnostics or therapeutic targets in different human diseases. PMID:26415220

  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. 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.

  19. 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.

  20. Akaike information criterion to select well-fit resist models

    NASA Astrophysics Data System (ADS)

    Burbine, Andrew; Fryer, David; Sturtevant, John

    2015-03-01

    In the field of model design and selection, there is always a risk that a model is over-fit to the data used to train the model. A model is well suited when it describes the physical system and not the stochastic behavior of the particular data collected. K-fold cross validation is a method to check this potential over-fitting to the data by calibrating with k-number of folds in the data, typically between 4 and 10. Model training is a computationally expensive operation, however, and given a wide choice of candidate models, calibrating each one repeatedly becomes prohibitively time consuming. Akaike information criterion (AIC) is an information-theoretic approach to model selection based on the maximized log-likelihood for a given model that only needs a single calibration per model. It is used in this study to demonstrate model ranking and selection among compact resist modelforms that have various numbers and types of terms to describe photoresist behavior. It is shown that there is a good correspondence of AIC to K-fold cross validation in selecting the best modelform, and it is further shown that over-fitting is, in most cases, not indicated. In modelforms with more than 40 fitting parameters, the size of the calibration data set benefits from additional parameters, statistically validating the model complexity.

  1. A hidden markov model derived structural alphabet for proteins.

    PubMed

    Camproux, A C; Gautier, R; Tufféry, P

    2004-06-01

    Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction. PMID:15147844

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    Uranyl (UO22+), the predominant aerobic form of uranium, is present in the ocean at a concentration of ~3.2 parts per 109 (13.7 nM) however, the successful enrichment of uranyl from this vast resource has been limited by the high concentrations of metal ions of similar size and charge, which makes it difficult to design a binding motif that is selective for uranyl. Here we report the design and rational development of a uranyl-binding protein using a computational screening process in the initial search for potential uranyl-binding sites. The engineered protein is thermally stable and offers very high affinity and selectivity for uranyl with a Kd of 7.4 femtomolar (fM) and >10,000-fold selectivity over other metal ions. We also demonstrated that the uranyl-binding protein can repeatedly sequester 30-60% of the uranyl in synthetic sea water. The chemical strategy employed here may be applied to engineer other selective metal-binding proteins for biotechnology and remediation applications.

  3. 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. PMID:24557139

  4. 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.

  5. 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. PMID:25950863

  6. Self-Assembly of Protein Nanofibrils Orchestrates Calcite Step Movement through Selective Nonchiral Interactions.

    PubMed

    So, Christopher R; Liu, Jinny; Fears, Kenan P; Leary, Dagmar H; Golden, Joel P; Wahl, Kathryn J

    2015-06-23

    The recognition of atomically distinct surface features by adsorbed biomolecules is central to the formation of surface-templated peptide or protein nanostructures. On mineral surfaces such as calcite, biomolecular recognition of, and self-assembly on, distinct atomic kinks and steps could additionally orchestrate changes to the overall shape and symmetry of a bulk crystal. In this work, we show through in situ atomic force microscopy (AFM) experiments that an acidic 20 kDa cement protein from the barnacle Megabalanus rosa (MRCP20) binds specifically to step edge atoms on {101̅4} calcite surfaces, remains bound and further assembles over time to form one-dimensional nanofibrils. Protein nanofibrils are continuous and organized at the nanoscale, exhibiting striations with a period of ca. 45 nm. These fibrils, templated by surface steps of a preferred geometry, in turn selectively dissolve underlying calcite features displaying the same atomic arrangement. To demonstrate this, we expose the protein solution to bare and fibril-associated rhombohedral etch pits to reveal that nanofibrils accelerate only the movement of fibril-forming steps when compared to undecorated steps exposed to the same solution conditions. Calcite mineralized in the presence of MRCP20 results in asymmetric crystals defined by frustrated faces with shared mirror symmetry, suggesting a similar step-selective behavior by MRCP20 in crystal growth. As shown here, selective surface interactions with step edge atoms lead to a cooperative regime of calcite modification, where templated long-range protein nanostructures shape crystals. PMID:25970003

  7. "Smart" molecularly imprinted monoliths for the selective capture and easy release of proteins.

    PubMed

    Wen, Liyin; Tan, Xinyi; Sun, Qi; Svec, Frantisek; Lv, Yongqin

    2016-08-01

    A new thermally switchable molecularly imprinted monolith for the selective capture and release of proteins has been designed. First, a generic poly(glycidyl methacrylate-co-ethylene dimethacrylate) monolith reacted with ethylenediamine followed by functionalization with 2-bromoisobutyryl bromide to introduce the initiator for atom transfer radical polymerization. Subsequently, a protein-imprinted poly(N-isopropylacrylamide) layer was grafted onto the surface of the monolithic matrix by atom transfer radical polymerization. Scanning electron microscopy and energy-dispersive X-ray spectroscopy of the cross-sections of imprinted monoliths confirmed the formation of dense poly(N-isopropylacrylamide) brushes on the pore surface. The imprinted monolith exhibited high specificity and selectivity toward its template protein myoglobin over competing proteins and a remarkably large maximum adsorption capacity of 1641 mg/g. Moreover, this "smart" imprinted monolith featured thermally responsive characteristics that enabled selective capture and easy release of proteins triggered only by change in temperature with water as the mobile phase and avoided use of stronger organic solvents or change in ionic strength and pH. PMID:27352958

  8. 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.

  9. Multilabel learning via random label selection for protein subcellular multilocations prediction.

    PubMed

    Wang, Xiao; Li, Guo-Zheng

    2013-01-01

    Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multilocation proteins to multiple proteins with single location, which does not take correlations among different subcellular locations into account. In this paper, a novel method named random label selection (RALS) (multilabel learning via RALS), which extends the simple binary relevance (BR) method, is proposed to learn from multilocation proteins in an effective and efficient way. RALS does not explicitly find the correlations among labels, but rather implicitly attempts to learn the label correlations from data by augmenting original feature space with randomly selected labels as its additional input features. Through the fivefold cross-validation test on a benchmark data set, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark data sets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multilocations of proteins. The prediction web server is available at >http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage. PMID:23929867

  10. Signal Peptide-Binding Drug as a Selective Inhibitor of Co-Translational Protein Translocation

    PubMed Central

    Vermeire, Kurt; Bell, Thomas W.; Van Puyenbroeck, Victor; Giraut, Anne; Noppen, Sam; Liekens, Sandra; Schols, Dominique; Hartmann, Enno

    2014-01-01

    In eukaryotic cells, surface expression of most type I transmembrane proteins requires translation and simultaneous insertion of the precursor protein into the endoplasmic reticulum (ER) membrane for subsequent routing to the cell surface. This co-translational translocation pathway is initiated when a hydrophobic N-terminal signal peptide (SP) on the nascent protein emerges from the ribosome, binds the cytosolic signal recognition particle (SRP), and targets the ribosome-nascent chain complex to the Sec61 translocon, a universally conserved protein-conducting channel in the ER-membrane. Despite their common function in Sec61 targeting and ER translocation, SPs have diverse but unique primary sequences. Thus, drugs that recognise SPs could be exploited to inhibit translocation of specific proteins into the ER. Here, through flow cytometric analysis the small-molecule macrocycle cyclotriazadisulfonamide (CADA) is identified as a highly selective human CD4 (hCD4) down-modulator. We show that CADA inhibits CD4 biogenesis and that this is due to its ability to inhibit co-translational translocation of CD4 into the lumen of the ER, both in cells as in a cell-free in vitro translation/translocation system. The activity of CADA maps to the cleavable N-terminal SP of hCD4. Moreover, through surface plasmon resonance analysis we were able to show direct binding of CADA to the SP of hCD4 and identify this SP as the target of our drug. Furthermore, CADA locks the SP in the translocon during a post-targeting step, possibly in a folded state, and prevents the translocation of the associated protein into the ER lumen. Instead, the precursor protein is routed to the cytosol for degradation. These findings demonstrate that a synthetic, cell-permeable small-molecule can be developed as a SP-binding drug to selectively inhibit protein translocation and to reversibly regulate the expression of specific target proteins. PMID:25460167

  11. Bioinorganic Chemical Modeling of Dioxygen-Activating Copper Proteins.

    ERIC Educational Resources Information Center

    Karlin, Kenneth D.; Gultneh, Yilma

    1985-01-01

    Discusses studies done in modeling the copper centers in the proteins hemocyanin (a dioxygen carrier), tyrosinase, and dopamine beta-hydroxylase. Copper proteins, model approach in copper bioinorganic chemistry, characterization of reversible oxygen carriers and dioxygen-metal complexes, a copper mono-oxygenase model reaction, and other topics are…

  12. 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…

  13. BeEP Server: using evolutionary information for quality assessment of protein structure models

    PubMed Central

    Palopoli, Nicolas; Lanzarotti, Esteban; Parisi, Gustavo

    2013-01-01

    The BeEP Server (http://www.embnet.qb.fcen.uba.ar/embnet/beep.php) is an online resource aimed to help in the endgame of protein structure prediction. It is able to rank submitted structural models of a protein through an explicit use of evolutionary information, a criterion differing from structural or energetic considerations commonly used in other assessment programs. The idea behind BeEP (Best Evolutionary Pattern) is to benefit from the substitution pattern derived from structural constraints present in a set of homologous proteins adopting a given protein conformation. The BeEP method uses a model of protein evolution that takes into account the structure of a protein to build site-specific substitution matrices. The suitability of these substitution matrices is assessed through maximum likelihood calculations from which position-specific and global scores can be derived. These scores estimate how well the structural constraints derived from each structural model are represented in a sequence alignment of homologous proteins. Our assessment on a subset of proteins from the Critical Assessment of techniques for protein Structure Prediction (CASP) experiment has shown that BeEP is capable of discriminating the models and selecting one or more native-like structures. Moreover, BeEP is not explicitly parameterized to find structural similarities between models and given targets, potentially helping to explore the conformational ensemble of the native state. PMID:23729471

  14. Modeling Protein Aggregate Assembly and Structure

    NASA Astrophysics Data System (ADS)

    Guo, Jun-tao; Hall, Carol K.; Xu, Ying; Wetzel, Ronald

    One might say that "protein science" got its start in the domestic arts, built around the abilities of proteins to aggregate in response to environmental stresses such as heating (boiled eggs), heating and cooling (gelatin), and pH (cheese). Characterization of proteins in the late nineteenth century likewise focused on the ability of proteins to precipitate in response to certain salts and to aggregate in response to heating. Investigations by Chick and Martin (Chick and Martin, 1910) showed that the inactivating response of proteins to heat or solvent treatment is a two-step process involving separate denaturation and precipitation steps. Monitoring the coagulation and flocculation responses of proteins to heat and other stresses remained a major approach to understanding protein structure for decades, with solubility, or susceptibility to aggregation, serving as a kind of benchmark against which results of other methods, such as viscosity, chemical susceptibility, immune activity, crystallizability, and susceptibility to proteolysis, were compared (Mirsky and Pauling, 1936;Wu, 1931). Toward the middle of the last century, protein aggregation studies were largely left behind, as improved methods allowed elucidation of the primary sequence of proteins, reversible unfolding studies, and ultimately high-resolution structures. Curiously, the field of protein science, and in particular protein folding, is now gravitating back to a closer look at protein aggregation and protein aggregates. Unfortunately, the means developed during the second half of the twentieth century for studying native, globular proteins have not proved immediately amenable to the study of aggregate structures. Great progress is being made, however, to modify classical methods, including NMR and X-ray diffraction, as well as to develop newer techniques, that together should continue to expand our picture of aggregate structure (Kheterpal and Wetzel, 2006; Wetzel, 1999).

  15. Selective and programmed cleavage of GPI-anchored proteins from the surface membrane by phospholipase C.

    PubMed

    Müller, Alexandra; Klöppel, Christine; Smith-Valentine, Megan; Van Houten, Judith; Simon, Martin

    2012-01-01

    Many surface proteins of eukaryotic cells are tethered to the membrane by a GPI-anchor which is enzymatically cleavable. Here, we investigate cleavage and release of different GPI-proteins by phospholipase C from the outer membrane of the ciliate Paramecium tetraurelia. Our data indicate that different GPI-proteins are not equally cleaved as proteins of the surface antigen family are preferentially released in vitro compared to several smaller GPI-proteins. Likewise, the analysis of culture medium indicates exclusive in vivo release of surface antigens by two phospholipase C isoforms (PLC2 and PLC6). This suggests that phospholipase C shows affinity for select groups of GPI-anchored proteins. Our data also reveal an up-regulation of PLC isoforms in GPI-anchored protein cleavage during antigenic switching. As a consequence, silencing of these PLCs leads to a drastic decrease of antigen concentration in the medium. These results suggest a higher order of GPI-regulation by phospholipase C as cleavage occurs programmed and specific for single GPI-proteins instead of an unspecific shedding of the entire surface membrane GPI-content. PMID:22024023

  16. Selective polyamine-binding proteins. Spermine binding by an androgen-sensitive phosphoprotein.

    PubMed

    Liang, T; Mezzetti, G; Chen, C; Liao, S

    1978-09-01

    Rat ventral prostate contains an acidic protein which can bind spermine selectively. The relative binding affinities of various aliphatic amines for the protein are, in decreasing order, spermine greater than thermine greater than greater than putrecine greater than 1,10-diaminodecane, cadaverine and 1,12-diaminododecane. The binding protein has an isoelectric point at pH 4.3 and a sedimentation coefficient of 3 S. Its molecular weight is approx. 30 000. Histones and nuclear chromatin preparations of the prostate can interact with the binding protein. The spermine-binding activity of the purified prostate protein can be inactivated by treatment with intestinal alkaline phosphatases. The phosphatase treated preparation can then be reactivated by beef heart protein kinase in the presence of cyclic AMP and ATP. The spermine-binding activity of the prostate cytosol protein fraction decreases after castration, but increases very rapidly after the castrated rats are injected with 5alpha-dihydrotestosterone. This finding raises the possibility that, in the postate, certain androgen actions may be dependent on the androgen-induced increase in the acidic protein binding of polyamines and their translocation to a functional cellular site such as nuclear chromatin. In the prostate cytosol, spermine also binds to 4-S tRNAs and to a unique RNA which has a sedimentation coefficient of 1.5 S. PMID:28786

  17. Carbon-Decorated TiO2 Nanotube Membranes: A Renewable Nanofilter for Charge-Selective Enrichment of Proteins.

    PubMed

    Xu, Jingwen; Yang, Lingling; Han, Yuyao; Wang, Yongmei; Zhou, Xuemei; Gao, Zhida; Song, Yan-Yan; Schmuki, Patrik

    2016-08-31

    In this work, we design a TiO2 nanomembrane (TiNM) that can be used as a nanofilter platform for selective enrichment of specific proteins. After a first use, the photocatalytic properties of TiO2 allow the decomposition of unwanted remnants on the substrate and thus make the platform reusable. To construct this platform, we fabricate a free-standing TiO2 nanotube array and remove the bottom oxide to form a both-end-open TiNM. By pyrolysis of the natural tube wall contamination, the walls become decorated with graphitic carbon patches (C/TiNM). Owing to the large surface area, the amphiphilic nature and the charge-adjustable character, this C/TiNM can be used to extract and enrich hydrophobic charged biomolecules. Using human serum albumin (HSA) as a model protein as well as protein mixtures, we show that the composite membrane exhibits a highly enhanced loading capacity and protein selectivity and is reusable after a short UV treatment. PMID:27509326

  18. Structural Basis for Receptor Activity-Modifying Protein-Dependent Selective Peptide Recognition by a G Protein-Coupled Receptor.

    PubMed

    Booe, Jason M; Walker, Christopher S; Barwell, James; Kuteyi, Gabriel; Simms, John; Jamaluddin, Muhammad A; Warner, Margaret L; Bill, Roslyn M; Harris, Paul W; Brimble, Margaret A; Poyner, David R; Hay, Debbie L; Pioszak, Augen A

    2015-06-18

    Association of receptor activity-modifying proteins (RAMP1-3) with the G protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) enables selective recognition of the peptides calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) that have diverse functions in the cardiovascular and lymphatic systems. How peptides selectively bind GPCR:RAMP complexes is unknown. We report crystal structures of CGRP analog-bound CLR:RAMP1 and AM-bound CLR:RAMP2 extracellular domain heterodimers at 2.5 and 1.8 Å resolutions, respectively. The peptides similarly occupy a shared binding site on CLR with conformations characterized by a β-turn structure near their C termini rather than the α-helical structure common to peptides that bind related GPCRs. The RAMPs augment the binding site with distinct contacts to the variable C-terminal peptide residues and elicit subtly different CLR conformations. The structures and accompanying pharmacology data reveal how a class of accessory membrane proteins modulate ligand binding of a GPCR and may inform drug development targeting CLR:RAMP complexes. PMID:25982113

  19. Structural Basis for Receptor Activity-Modifying Protein-Dependent Selective Peptide Recognition by a G Protein-Coupled Receptor

    PubMed Central

    Booe, Jason M.; Walker, Christopher S.; Barwell, James; Kuteyi, Gabriel; Simms, John; Jamaluddin, Muhammad A.; Warner, Margaret L.; Bill, Roslyn M.; Harris, Paul W.; Brimble, Margaret A.; Poyner, David R.; Hay, Debbie L.; Pioszak, Augen A.

    2015-01-01

    Summary Association of receptor activity-modifying proteins (RAMP1-3) with the G protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) enables selective recognition of the peptides calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) that have diverse functions in the cardiovascular and lymphatic systems. How peptides selectively bind GPCR:RAMP complexes is unknown. We report crystal structures of CGRP analog-bound CLR:RAMP1 and AM-bound CLR:RAMP2 extracellular domain heterodimers at 2.5 and 1.8 Å resolutions, respectively. The peptides similarly occupy a shared binding site on CLR with conformations characterized by a β-turn structure near their C termini rather than the α-helical structure common to peptides that bind related GPCRs. The RAMPs augment the binding site with distinct contacts to the variable C-terminal peptide residues and elicit subtly different CLR conformations. The structures and accompanying pharmacology data reveal how a class of accessory membrane proteins modulate ligand binding of a GPCR and may inform drug development targeting CLR:RAMP complexes. PMID:25982113

  20. Selected aspects of modelling monetary transmission mechanism by BVAR model

    NASA Astrophysics Data System (ADS)

    Vaněk, Tomáš; Dobešová, Anna; Hampel, David

    2013-10-01

    In this paper we use the BVAR model with the specifically defined prior to evaluate data including high-lag dependencies. The results are compared to both restricted and common VAR model. The data depicts the monetary transmission mechanism in the Czech Republic and Slovakia from January 2002 to February 2013. The results point to the inadequacy of the common VAR model. The restricted VAR model and the BVAR model appear to be similar in the sense of impulse responses.

  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. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    PubMed

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-01-01

    Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks using disease-related selected genes has garnered much attention. Support vector machines (SVMs) are commonly used to classify patients, and a number of useful tools such as lasso, elastic net, SCAD, or other regularization methods can be combined with SVM models to select genes that are related to a disease. In the current study, we propose a new Net-SVM model that is different from other SVM models as it is combined with L1/2-norm regularization, which has good performance with high-dimensional and low-sample size microarray data for cancer classification, gene selection, and PPI network construction. Both simulation studies and real data experiments demonstrated that our proposed method outperformed other regularization methods such as lasso, SCAD, and elastic net. In conclusion, our model may help to select fewer but more relevant genes, and can be used to construct simple and informative PPI networks that are highly relevant to cancer. PMID:27525863

  3. The role of negative selection in protein evolution revealed through the energetics of the native state ensemble.

    PubMed

    Hoffmann, Jordan; Wrabl, James O; Hilser, Vincent J

    2016-04-01

    Knowing the determinants of conformational specificity is essential for understanding protein structure, stability, and fold evolution. To address this issue, a novel statistical measure of energetic compatibility between sequence and structure was developed using an experimentally validated model of the energetics of the native state ensemble. This approach successfully matched sequences from a diverse subset of the human proteome to their respective folds. Unexpectedly, significant energetic compatibility between ostensibly unrelated sequences and structures was also observed. Interrogation of these matches revealed a general framework for understanding the origins of conformational specificity within a proteome: specificity is a complex function of both the ability of a sequence to adopt folds other than the native, and ability of a fold to accommodate sequences other than the native. The regional variation in energetic compatibility indicates that the compatibility is dominated by incompatibility of sequence for alternative fold segments, suggesting that evolution of protein sequences has involved substantial negative selection, with certain segments serving as "gatekeepers" that presumably prevent alternative structures. Beyond these global trends, a size dependence exists in the degree to which the energetic compatibility is determined from negative selection, with smaller proteins displaying more negative selection. This partially explains how short sequences can adopt unique folds, despite the higher probability in shorter proteins for small numbers of mutations to increase compatibility with other folds. In providing evolutionary ground rules for the thermodynamic relationship between sequence and fold, this framework imparts valuable insight for rational design of unique folds or fold switches. Proteins 2016; 84:435-447. © 2016 Wiley Periodicals, Inc. PMID:26800099

  4. A nonionic surfactant-decorated liquid crystal sensor for sensitive and selective detection of proteins.

    PubMed

    Wang, Yi; Hu, Qiongzheng; Tian, Tongtong; Gao, Yan'an; Yu, Li

    2016-09-21

    Proteins are responsible for most biochemical events in human body. It is essential to develop sensitive and selective methods for the detection of proteins. In this study, liquid crystal (LC)-based sensor for highly selective and sensitive detection of lysozyme, concanavalin A (Con A), and bovine serum albumin (BSA) was constructed by utilizing the LC interface decorated with a nonionic surfactant, dodecyl β-d-glucopyranoside. A change of the LC optical images from bright to dark appearance was observed after transferring dodecyl β-d-glucopyranoside onto the aqueous/LC interface due to the formation of stable self-assembled surfactant monolayer, regardless of pH and ion concentrations studied in a wide range. The optical images turned back from dark to bright appearance after addition of lysozyme, Con A and BSA, respectively. Noteworthy is that these proteins can be further distinguished by adding enzyme inhibitors and controlling incubation temperature of the protein solutions based on three different interaction mechanisms between proteins and dodecyl β-d-glucopyranoside, viz. enzymatic hydrolysis, specific saccharide binding, and physical absorption. The LC-based sensor decorated with dodecyl β-d-glucopyranoside shows high sensitivity for protein detection. The limit of detection (LOD) for lysozyme, Con A and BSA reaches around 0.1 μg/mL, 0.01 μg/mL and 0.001 μg/mL, respectively. These results might provide new insights into increasing selectivity and sensitivity of LC-based sensors for the detection of proteins. PMID:27590553

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

    PubMed

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

    2015-02-01

    PKDREJ is a testis-specific protein thought to be located on the sperm surface. Functional studies in the mouse revealed that loss of PKDREJ has effects on sperm transport and the ability to undergo an induced acrosome reaction. Thus, PKDREJ has been considered a potential target of post-copulatory sexual selection in the form of sperm competition. Proteins involved in reproductive processes often show accelerated evolution. In many cases, this rapid divergence is promoted by positive selection which may be driven, at least in part, by post-copulatory sexual selection. We analysed the evolution of the PKDREJ protein in primates and rodents and assessed whether PKDREJ divergence is associated with testes mass relative to body mass, which is a reliable proxy of sperm competition levels. Evidence of an association between the evolutionary rate of the PKDREJ gene and testes mass relative to body mass was not found in primates. Among rodents, evidence of positive selection was detected in the Pkdrej gene in the family Cricetidae but not in Muridae. We then assessed whether Pkdrej divergence is associated with episodes of sperm competition in these families. We detected a positive significant correlation between the evolutionary rates of Pkdrej and testes mass relative to body mass in cricetids. These findings constitute the first evidence of post-copulatory sexual selection influencing the evolution of a protein that participates in the mechanisms regulating sperm transport and the acrosome reaction, strongly suggesting that positive selection may act on these fertilization steps, leading to advantages in situations of sperm competition. PMID:25304980

  6. Detection of G Protein-selective G Protein-coupled Receptor (GPCR) Conformations in Live Cells*

    PubMed Central

    Malik, Rabia U.; Ritt, Michael; DeVree, Brian T.; Neubig, Richard R.; Sunahara, Roger K.; Sivaramakrishnan, Sivaraj

    2013-01-01

    Although several recent studies have reported that GPCRs adopt multiple conformations, it remains unclear how subtle conformational changes are translated into divergent downstream responses. In this study, we report on a novel class of FRET-based sensors that can detect the ligand/mutagenic stabilization of GPCR conformations that promote interactions with G proteins in live cells. These sensors rely on the well characterized interaction between a GPCR and the C terminus of a Gα subunit. We use these sensors to elucidate the influence of the highly conserved (E/D)RY motif on GPCR conformation. Specifically, Glu/Asp but not Arg mutants of the (E/D)RY motif are known to enhance basal GPCR signaling. Hence, it is unclear whether ionic interactions formed by the (E/D)RY motif (ionic lock) are necessary to stabilize basal GPCR states. We find that mutagenesis of the β2-AR (E/D)RY ionic lock enhances interaction with Gs. However, only Glu/Asp but not Arg mutants increase G protein activation. In contrast, mutagenesis of the opsin (E/D)RY ionic lock does not alter its interaction with transducin. Instead, opsin-specific ionic interactions centered on residue Lys-296 are both necessary and sufficient to promote interactions with transducin. Effective suppression of β2-AR basal activity by inverse agonist ICI 118,551 requires ionic interactions formed by the (E/D)RY motif. In contrast, the inverse agonist metoprolol suppresses interactions with Gs and promotes Gi binding, with concomitant pertussis toxin-sensitive inhibition of adenylyl cyclase activity. Taken together, these studies validate the use of the new FRET sensors while revealing distinct structural mechanisms for ligand-dependent GPCR function. PMID:23629648

  7. Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors.

    PubMed

    Bharatham, Kavitha; Bharatham, Nagakumar; Lee, Keun Woo

    2007-05-01

    A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 microM, was selected as a training set. Hypol, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypol) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypol performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypol model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors. PMID:17615669

  8. Ensemble-based evaluation for protein structure models

    PubMed Central

    Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

    2016-01-01

    Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation: https://bitbucket.org/mjamroz/flexscore Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307633

  9. Proteins.

    ERIC Educational Resources Information Center

    Doolittle, Russell F.

    1985-01-01

    Examines proteins which give rise to structure and, by virtue of selective binding to other molecules, make genes. Binding sites, amino acids, protein evolution, and molecular paleontology are discussed. Work with encoding segments of deoxyribonucleic acid (exons) and noncoding stretches (introns) provides new information for hypotheses. (DH)

  10. A residue level protein-protein interaction model in electrolyte solutions

    NASA Astrophysics Data System (ADS)

    Song, Xueyu

    2014-03-01

    The osmotic second virial coefficients B2 are directly related to the solubility of protein molecules in electrolyte solutions and can be useful to narrow down the search parameter space of protein crystallization conditions. Using a residue level model of protein-protein interaction in electrolyte solutions B2 of bovine pancreatic trypsin inhibitor and lysozyme in various solution conditions such as salt concentration, pH and temperature are calculated using an extended Fast Multipole Methods in combination with the boundary element formulation. Overall, the calculated B2 are well correlated with the experimental observations for various solution conditions. In combination with our previous work on the binding affinity calculations of protein complexes it is demonstrated that our residue level model can be used as a reliable model to describe protein-protein interaction in solutions.

  11. Assessment of the reactivity of selected isoflavones against proteins in comparison to quercetin.

    PubMed

    Rawel, Harshadrai M; Ranters, Holger; Rohn, Sascha; Kroll, Jürgen

    2004-08-11

    Selected isoflavones (genistein, daidzein, formononetin, prunetin, biochanin A, and two synthetic isoflavones) were allowed to interact with soy and whey proteins. The reaction products were analyzed in terms of covalent binding at the nucleophilic side chains of proteins. Changes in molecular properties of the proteins derivatives were documented by SDS-PAGE, IEF, and SELDI-TOF-MS. The structural changes induced were studied using circular dichroism. The in vitro digestibility was assessed with trypsin. The results show that the occurrence of the catechol moiety, that is, the two adjacent (ortho) aromatic hydroxyl groups on ring B of the flavonoid structural skeleton appears to be prerequisite condition for covalent binding to proteins. The catechol moiety on ring A was less reactive. Its absence lead to a slight or no significant reaction, although noncovalent interactions may still be possible, even when lacking this structural element. A comparison of the data is also made with quercetin representing the flavonols. PMID:15291506

  12. Selective adsorption of proteins on single-wall carbon nanotubes by using a protective surfactant.

    PubMed

    Knyazev, Anton; Louise, Loïc; Veber, Michèle; Langevin, Dominique; Filoramo, Arianna; Prina-Mello, Adriele; Campidelli, Stéphane

    2011-12-16

    The dispersion of highly hydrophobic carbon materials such as carbon nanotubes in biological media is a challenging issue. Indeed, the nonspecific adsorption of proteins occurs readily when the nanotubes are introduced in biological media; therefore, a methodology to control adsorption is in high demand. To address this issue, we developed a bifunctional linker derived from pyrene that selectively enables or prevents the adsorption of proteins on single-wall carbon nanotubes (SWNTs). We demonstrated that it is possible to decrease or completely suppress the adsorption of proteins on the nanotube sidewall by using proper functionalization (either covalent or noncovalent). By subsequently activating the functional groups on the nanotube derivatives, protein adsorption can be recovered and, therefore, controlled. Our approach is simple, straightforward, and potentially suitable for other biomolecules that contain thio or amino groups available for coupling. PMID:22095560

  13. Mushroom tyrosinase oxidizes tyrosine-rich sequences to allow selective protein functionalization.

    PubMed

    Long, Marcus J C; Hedstrom, Lizbeth

    2012-08-13

    We show that mushroom tyrosinase catalyzes the formation of reactive o-quinones on unstructured, tyrosine-rich sequences such as hemagglutinin (HA) tags (YPYDVPDYA). In the absence of exogenous nucleophiles and at low protein concentrations, the o-quinone decomposes with fragmentation of the HA tag. At higher protein concentrations (>5 mg mL⁻¹), crosslinking is observed. Besthorn's reagent intercepts the o-quinone to give a characteristic pink complex that can be observed directly on a denaturing SDS-PAGE gel. Similar labeled species can be formed by using other nucleophiles such as Cy5-hydrazide. These reactions are selective for proteins bearing HA and other unstructured poly-tyrosine-containing tags and can be performed in lysates to create specifically tagged proteins. PMID:22807021

  14. Construction of antibody-like nanoparticles for selective protein sequestration in living cells.

    PubMed

    Liu, Yibin; Fang, Simin; Zhai, Junqiu; Zhao, Meiping

    2015-04-28

    We demonstrate the successful construction of fluorescently labeled magnetic antibody-like nanoparticles (ANPs) via a facile one-step surface-initiated in situ molecular imprinting approach over silica coated magnetite (Fe3O4@SiO2) core-shell nanocomposites. The as-prepared ANPs had a highly compact structure with an overall size of 83 ± 5 nm in diameter and showed excellent aqueous dispersion stability. With the predetermined high specificity to the target protein and high biocompatibility, the ANPs enabled rapid, efficient, selective and optically trackable sequestration of target proteins within living cells. This work represents the first example of fully artificially engineered multifunctional ANPs for the intracellular protein-sequestration without disruption of the cells. The established approach may be further extended to generate ANPs for various proteins of interest and provide useful tools for related biological research and biomedical applications. PMID:25812011

  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. Mechanical Modeling and Computer Simulation of Protein Folding

    ERIC Educational Resources Information Center

    Prigozhin, Maxim B.; Scott, Gregory E.; Denos, Sharlene

    2014-01-01

    In this activity, science education and modern technology are bridged to teach students at the high school and undergraduate levels about protein folding and to strengthen their model building skills. Students are guided from a textbook picture of a protein as a rigid crystal structure to a more realistic view: proteins are highly dynamic…

  17. Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: Approaches with minimal redundancy maximal relevance feature selection.

    PubMed

    Jiao, Ya-Sen; Du, Pu-Feng

    2016-08-01

    Recently, several efforts have been made in predicting Golgi-resident proteins. However, it is still a challenging task to identify the type of a Golgi-resident protein. Precise prediction of the type of a Golgi-resident protein plays a key role in understanding its molecular functions in various biological processes. In this paper, we proposed to use a mutual information based feature selection scheme with the general form Chou's pseudo-amino acid compositions to predict the Golgi-resident protein types. The positional specific physicochemical properties were applied in the Chou's pseudo-amino acid compositions. We achieved 91.24% prediction accuracy in a jackknife test with 49 selected features. It has the best performance among all the present predictors. This result indicates that our computational model can be useful in identifying Golgi-resident protein types. PMID:27155042

  18. 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.

  19. The effect of geometrical presentation of multimodal cation-exchange ligands on selective recognition of hydrophobic regions on protein surfaces.

    PubMed

    Woo, James; Parimal, Siddharth; Brown, Matthew R; Heden, Ryan; Cramer, Steven M

    2015-09-18

    The effects of spatial organization of hydrophobic and charged moieties on multimodal (MM) cation-exchange ligands were examined by studying protein retention behavior on two commercial chromatographic media, Capto™ MMC and Nuvia™ cPrime™. Proteins with extended regions of surface-exposed aliphatic residues were found to have enhanced retention on the Capto MMC system as compared to the Nuvia cPrime resin. The results further indicated that while the Nuvia cPrime ligand had a strong preference for interactions with aromatic groups, the Capto MMC ligand appeared to interact with both aliphatic and aromatic clusters on the protein surfaces. These observations were formalized into a new set of protein surface property descriptors, which quantified the local distribution of electrostatic and hydrophobic potentials as well as distinguishing between aromatic and aliphatic properties. Using these descriptors, high-performing quantitative structure-activity relationship (QSAR) models (R(2)>0.88) were generated for both the Capto MMC and Nuvia cPrime datasets at pH 5 and pH 6. Descriptors of electrostatic properties were generally common across the four models; however both Capto MMC models included descriptors that quantified regions of aliphatic-based hydrophobicity in addition to aromatic descriptors. Retention was generally reduced by lowering the ligand densities on both MM resins. Notably, elution order was largely unaffected by the change in surface density, but smaller and more aliphatic proteins tended to be more affected by this drop in ligand density. This suggests that modulating the exposure, shape and density of the hydrophobic moieties in multimodal chromatographic systems can alter the preference for surface exposed aliphatic or aromatic residues, thus providing an additional dimension for modulating the selectivity of MM protein separation systems. PMID:26292626

  20. 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.

  1. Ir Spectroscopy on Peptides and Proteins after Ion Mobility Selection and in Liquid Helium Droplets

    NASA Astrophysics Data System (ADS)

    von Helden, Gert

    2015-06-01

    IR spectroscopy has become a frequently used tool to characterize gas-phase peptides and proteins. In many experiments, ions are m/z selected, irradiated by intense and tunable IR light and fragmentation is monitored as a function of IR wavelength. The presence of different conformers can, however, complicate the interpretation, as the resulting spectra represent the sum of the spectra of the individual components. We constructed a setup, in which ion mobility methods are used to obtain m/z selected ions of defined shape on which are then further investigated by IR spectroscopy. First results on peptide aggregates are presented and for some of those, the IR spectra show a transition from helical or random coil to beta sheet structures. In a different experiment, peptide or protein ions are captures in liquid helium droplets prior to IR spectroscopic investigation. The conditions inside a helium droplet are isothermal at 0.38 K and the interaction between the helium matrix and the molecules are weak so that only small perturbations on the molecule are expected. IR spectra for m/z selected peptides with up to 10 aminoacids and proteins containing more than 100 aminoacids have been measured. The spectra of the smaller species show resolved bands of individual oscillators, which can be used for structure assignment. For the larger species, band envelopes are obtained and for the case of highly charged proteins, a transition form helical to extended structures is observed.

  2. Microfluidics-Based Selection of Red-Fluorescent Proteins with Decreased Rates of Photobleaching

    PubMed Central

    Dean, Kevin M.; Lubbeck, Jennifer L.; Davis, Lloyd M.; Regmi, Chola K.; Chapagain, Prem P.; Gerstman, Bernard S.; Jimenez, Ralph; Palmer, Amy E.

    2014-01-01

    Fluorescent proteins offer exceptional labeling specificity in living cells and organisms. Unfortunately, their photophysical properties remain far from ideal for long-term imaging of low-abundance cellular constituents, in large part because of their poor photostability. Despite widespread engineering efforts, improving the photostability of fluorescent proteins remains challenging due to lack of appropriate high-throughput selection methods. Here, we use molecular dynamics guided mutagenesis in conjunction with a recently developed microfluidic-based platform, which sorts cells based on their fluorescence photostability, to identify red fluorescent proteins with decreased photobleaching from a HeLa cell-based library. The identified mutant, named Kriek, has 2.5- and 4-fold higher photostability than its progenitor, mCherry, under widefield and confocal illumination, respectively. Furthermore, the results provide insight into mechanisms for enhancing photostability and their connections with other photophysical processes, thereby providing direction for ongoing development of fluorescent proteins with improved single-molecule and low-copy imaging capabilities. Insight, innovation, integration Fluorescent proteins enable imaging in situ, throughout the visible spectrum, with superb molecular specificity and single-molecule sensitivity. Unfortunately, when compared to leading small-molecule fluorophores (e.g., Cy3), fluorescent proteins, suffer from accelerated photobleaching and poor integrated photon output. This results from a lack of appropriate high-throughput methods for improving the photostability of fluorescent proteins, as well as a poor molecular understanding of fluorescent protein photobleaching. Here, we report the first application of a recently developed microfluidic cell-sorter to identify fluorescent proteins from a mCherry-derived library with improved photostability. The results provide insight into fluorescent protein photophysics, greatly

  3. Size-selective fractionation and visual mapping of allergen protein chemistry in Arachis hypogaea.

    PubMed

    Hebling, Christine M; Ross, Mark M; Callahan, John H; McFarland, Melinda A

    2012-11-01

    Peanuts (Arachis hypogaea) in addition to milk, eggs, fish, crustaceans, wheat, tree nuts, and soybean are commonly referred to as the "big eight" foods that contribute to the majority of food allergies worldwide. Despite the severity of allergic reactions and growing prevalence in children and adults, there is no cure for peanut allergy, leaving avoidance as the primary mode of treatment. To improve analytical methods for peanut allergen detection, researchers must overcome obstacles involved in handling complex food matrices while attempting to decipher the chemistry that underlies allergen protein interactions. To address such challenges, we conducted a global proteome characterization of raw peanuts using a sophisticated GELFrEE-PAGE-LC-MS/MS platform consisting of gel-based protein fractionation followed by mass spectrometric identification. The in-solution mass-selective protein fractionation: (1) enhances the number of unique peptide identifications, (2) provides a visual map of protein isoforms, and (3) aids in the identification of disulfide-linked protein complexes. GELFrEE-PAGE-LC-MS/MS not only overcomes many of the challenges involved in the study of plant proteomics, but enriches the understanding of peanut protein chemistry, which is typically unattainable in a traditional bottom-up proteomic analysis. A global understanding of protein chemistry in Arachis hypogaea ultimately will aid the development of improved methods for allergen detection in food. PMID:23020697

  4. Caught in Action: Selecting Peptide Aptamers Against Intrinsically Disordered Proteins in Live Cells

    PubMed Central

    Cobbert, Jacqueline D.; DeMott, Christopher; Majumder, Subhabrata; Smith, Eric A.; Reverdatto, Sergey; Burz, David S.; McDonough, Kathleen A.; Shekhtman, Alexander

    2015-01-01

    Intrinsically disordered proteins (IDPs) or unstructured segments within proteins play an important role in cellular physiology and pathology. Low cellular concentration, multiple binding partners, frequent post-translational modifications and the presence of multiple conformations make it difficult to characterize IDP interactions in intact cells. We used peptide aptamers selected by using the yeast-two-hybrid scheme and in-cell NMR to identify high affinity binders to transiently structured IDP and unstructured segments at atomic resolution. Since both the selection and characterization of peptide aptamers take place inside the cell, only physiologically relevant conformations of IDPs are targeted. The method is validated by using peptide aptamers selected against the prokaryotic ubiquitin-like protein, Pup, of the mycobacterium proteasome. The selected aptamers bind to distinct sites on Pup and have vastly different effects on rescuing mycobacterial proteasome substrate and on the survival of the Bacille-Calmette-Guèrin, BCG, strain of M. bovis. This technology can be applied to study the elusive action of IDPs under near physiological conditions. PMID:25801767

  5. Caught in action: selecting peptide aptamers against intrinsically disordered proteins in live cells.

    PubMed

    Cobbert, Jacqueline D; DeMott, Christopher; Majumder, Subhabrata; Smith, Eric A; Reverdatto, Sergey; Burz, David S; McDonough, Kathleen A; Shekhtman, Alexander

    2015-01-01

    Intrinsically disordered proteins (IDPs) or unstructured segments within proteins play an important role in cellular physiology and pathology. Low cellular concentration, multiple binding partners, frequent post-translational modifications and the presence of multiple conformations make it difficult to characterize IDP interactions in intact cells. We used peptide aptamers selected by using the yeast-two-hybrid scheme and in-cell NMR to identify high affinity binders to transiently structured IDP and unstructured segments at atomic resolution. Since both the selection and characterization of peptide aptamers take place inside the cell, only physiologically relevant conformations of IDPs are targeted. The method is validated by using peptide aptamers selected against the prokaryotic ubiquitin-like protein, Pup, of the mycobacterium proteasome. The selected aptamers bind to distinct sites on Pup and have vastly different effects on rescuing mycobacterial proteasome substrate and on the survival of the Bacille-Calmette-Guèrin, BCG, strain of M. bovis. This technology can be applied to study the elusive action of IDPs under near physiological conditions. PMID:25801767

  6. Time-shared experiments for efficient assignment of triple-selectively labeled proteins

    PubMed Central

    Löhr, Frank; Laguerre, Aisha; Bock, Christoph; Reckel, Sina; Connolly, Peter J.; Abdul-Manan, Norzehan; Tumulka, Franz; Abele, Rupert; Moore, Jonathan M.; Dötsch, Volker

    2014-01-01

    Combinatorial triple-selective labeling facilitates the NMR assignment process for proteins that are subject to signal overlap and insufficient signal-to-noise in standard triple-resonance experiments. Aiming at maximum amino-acid type and sequence-specific information, the method represents a trade-off between the number of selectively labeled samples that have to be prepared and the number of spectra to be recorded per sample. In order to address the demand of long measurement times, we here propose pulse sequences in which individual phase-shifted transients are stored separately and recombined later to produce several 2D HN(CX) type spectra that are usually acquired sequentially. Sign encoding by the phases of 13C 90° pulses allows to either select or discriminate against 13C’ or 13Cα spins coupled to 15N. As a result, 1H-15N correlation maps of the various isotopomeric species present in triple-selectively labeled proteins are deconvoluted which in turn reduces problems due to spectral overlap. The new methods are demonstrated with four different membrane proteins with rotational correlation times ranging from 18 to 52 ns. PMID:25442777

  7. Modeling Selection and Extinction Mechanisms of Biological Systems

    NASA Astrophysics Data System (ADS)

    Amirjanov, Adil

    In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

  8. Modeling quality attributes and metrics for web service selection

    NASA Astrophysics Data System (ADS)

    Oskooei, Meysam Ahmadi; Daud, Salwani binti Mohd; Chua, Fang-Fang

    2014-06-01

    Since the service-oriented architecture (SOA) has been designed to develop the system as a distributed application, the service selection has become a vital aspect of service-oriented computing (SOC). Selecting the appropriate web service with respect to quality of service (QoS) through using mathematical solution for optimization of problem turns the service selection problem into a common concern for service users. Nowadays, number of web services that provide the same functionality is increased and selection of services from a set of alternatives which differ in quality parameters can be difficult for service consumers. In this paper, a new model for QoS attributes and metrics is proposed to provide a suitable solution for optimizing web service selection and composition with low complexity.

  9. 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

  10. Enhanced Photoelectrochemical Proximity Assay for Highly Selective Protein Detection in Biological Matrixes.

    PubMed

    Wen, Guangming; Ju, Huangxian

    2016-08-16

    This work proposes the first photoelectrochemical proximity assay (PECPA) method via the sensitization of CdTe quantum dots (QDs) on photoelectrochemical response of ITO/TiO2/CdS electrode for highly selective and sensitive detection of proteins. This detection was performed on a sensing interface formed via the hybridization of capture DNA immobilized on ITO/TiO2/CdS electrode with labeled antibody-DNA (DNA-Ab1). Upon the recognition of Ab1 to target protein, the immunocomplex of DNA-Ab1, target, and the detection antibody-DNA (DNA-Ab2) was formed, which led to the proximity hybridization of the DNA in DNA-Ab2, capture DNA, and signal DNA-CdTe QDs, and brought CdTe QDs to the ITO/TiO2/CdS electrode to produce a sensitized photocurrent. The photocurrent intensity increased with the increasing concentration of the specific target protein. Using insulin as a target, this sensitized method showed a detectable range of 10 fM to 10 nM and a detection limit of 3.0 fM without the need of a washing step. It possessed high selectivity and good accuracy for detection of proteins in biological matrixes. This method is extremely flexible and can be extended to varieties of protein targets. PMID:27464227

  11. 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).

  12. Activation of the A2A adenosine G-protein-coupled receptor by conformational selection.

    PubMed

    Ye, Libin; Van Eps, Ned; Zimmer, Marco; Ernst, Oliver P; Prosser, R Scott

    2016-05-12

    Conformational selection and induced fit are two prevailing mechanisms to explain the molecular basis for ligand-based activation of receptors. G-protein-coupled receptors are the largest class of cell surface receptors and are important drug targets. A molecular understanding of their activation mechanism is critical for drug discovery and design. However, direct evidence that addresses how agonist binding leads to the formation of an active receptor state is scarce. Here we use (19)F nuclear magnetic resonance to quantify the conformational landscape occupied by the adenosine A2A receptor (A2AR), a prototypical class A G-protein-coupled receptor. We find an ensemble of four states in equilibrium: (1) two inactive states in millisecond exchange, consistent with a formed (state S1) and a broken (state S2) salt bridge (known as 'ionic lock') between transmembrane helices 3 and 6; and (2) two active states, S3 and S3', as identified by binding of a G-protein-derived peptide. In contrast to a recent study of the β2-adrenergic receptor, the present approach allowed identification of a second active state for A2AR. Addition of inverse agonist (ZM241385) increases the population of the inactive states, while full agonists (UK432097 or NECA) stabilize the active state, S3', in a manner consistent with conformational selection. In contrast, partial agonist (LUF5834) and an allosteric modulator (HMA) exclusively increase the population of the S3 state. Thus, partial agonism is achieved here by conformational selection of a distinct active state which we predict will have compromised coupling to the G protein. Direct observation of the conformational equilibria of ligand-dependent G-protein-coupled receptor and deduction of the underlying mechanisms of receptor activation will have wide-reaching implications for our understanding of the function of G-protein-coupled receptor in health and disease. PMID:27144352

  13. Design and synthesis of protein kinase C epsilon selective diacylglycerol lactones (DAG-lactones).

    PubMed

    Ann, Jihyae; Yoon, Suyoung; Baek, Jisoo; Kim, Da Hye; Lewin, Nancy E; Hill, Colin S; Blumberg, Peter M; Lee, Jeewoo

    2015-01-27

    DAG-lactones afford a synthetically accessible, high affinity platform for probing structure activity relationships at the C1 regulatory domain of protein kinase C (PKC). Given the central role of PKC isoforms in cellular signaling, along with their differential biological activities, a critical objective is the design of isoform selective ligands. Here, we report the synthesis of a series of DAG-lactones varying in their side chains, with a particular focus on linoleic acid derivatives. We evaluated their selectivity for PKC epsilon versus PKC alpha both under standard lipid conditions (100% phosphatidylserine, PS) as well as in the presence of a nuclear membrane mimetic lipid mixture (NML). We find that selectivity for PKC epsilon versus PKC alpha tended to be enhanced in the presence of the nuclear membrane mimetic lipid mixture and, for our lead compound, report a selectivity of 32-fold. PMID:25437619

  14. 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

  15. Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

    PubMed Central

    Kundrotas, Petras J.; Vakser, Ilya A.

    2010-01-01

    The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Å, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Åmodeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes. PMID:20369011

  16. Protein adsorption on nanoparticles: model development using computer simulation.

    PubMed

    Shao, Qing; Hall, Carol K

    2016-10-19

    The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler-Guggenheim and Hill-de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles. PMID:27546610

  17. 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.

  18. Dynamic selection of models for a ventilator-management advisor.

    PubMed Central

    Rutledge, G. W.

    1993-01-01

    A ventilator-management advisor (VMA) is a computer program that monitors patients who are treated with a mechanical ventilator. A VMA implements a patient-specific physiologic model to interpret patient data and to predict the effects of alternative control settings for the ventilator. Because a VMA evaluates its physiologic model repeatedly during each cycle of data interpretation, highly complex models may require more computation time than is available in this time-critical application. On the other hand, less complex models may be inaccurate if they are unable to represent a patient's physiologic abnormalities. For each patient, a VMA should select a model that balances the tradeoff of prediction accuracy and computation-time complexity. I present a method to select models that are at an appropriate level of detail for time-constrained decision tasks. The method is based on a local search in a graph of models (GoM) for a model that maximizes the tradeoff of computation-time complexity and prediction accuracy. For each model under consideration, a belief network computes a probability of model adequacy given the qualitative prior information, and the goodness of fit of the model to the data provides a measure of the conditional probability of adequacy given the quantitative observations. I apply this method to the problem of model selection for a VMA. I describe an implementation of a graph of physiologic models that range in complexity from VentPlan, a simple model with 3 compartments, to VentSim, a multicompartment model with detailed airway, circulation and mechanical ventilator components.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:8130492

  19. Selection and demographic history shape the molecular evolution of the gamete compatibility protein bindin in Pisaster sea stars.

    PubMed

    Popovic, Iva; Marko, Peter B; Wares, John P; Hart, Michael W

    2014-05-01

    Reproductive compatibility proteins have been shown to evolve rapidly under positive selection leading to reproductive isolation, despite the potential homogenizing effects of gene flow. This process has been implicated in both primary divergence among conspecific populations and reinforcement during secondary contact; however, these two selective regimes can be difficult to discriminate from each other. Here, we describe the gene that encodes the gamete compatibility protein bindin for three sea star species in the genus Pisaster. First, we compare the full-length bindin-coding sequence among all three species and analyze the evolutionary relationships between the repetitive domains of the variable second bindin exon. The comparison suggests that concerted evolution of repetitive domains has an effect on bindin divergence among species and bindin variation within species. Second, we characterize population variation in the second bindin exon of two species: We show that positive selection acts on bindin variation in Pisaster ochraceus but not in Pisaster brevispinus, which is consistent with higher polyspermy risk in P. ochraceus. Third, we show that there is no significant genetic differentiation among populations and no apparent effect of sympatry with congeners that would suggest selection based on reinforcement. Fourth, we combine bindin and cytochrome c oxidase 1 data in isolation-with-migration models to estimate gene flow parameter values and explore the historical demographic context of our positive selection results. Our findings suggest that positive selection on bindin divergence among P. ochraceus alleles can be accounted for in part by relatively recent northward population expansions that may be coupled with the potential homogenizing effects of concerted evolution. PMID:24967076

  20. 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

  1. 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.

  2. Identification and structure-function analysis of subfamily selective G protein-coupled receptor kinase inhibitors.

    PubMed

    Homan, Kristoff T; Larimore, Kelly M; Elkins, Jonathan M; Szklarz, Marta; Knapp, Stefan; Tesmer, John J G

    2015-01-16

    Selective inhibitors of individual subfamilies of G protein-coupled receptor kinases (GRKs) would serve as useful chemical probes as well as leads for therapeutic applications ranging from heart failure to Parkinson's disease. To identify such inhibitors, differential scanning fluorimetry was used to screen a collection of known protein kinase inhibitors that could increase the melting points of the two most ubiquitously expressed GRKs: GRK2 and GRK5. Enzymatic assays on 14 of the most stabilizing hits revealed that three exhibit nanomolar potency of inhibition for individual GRKs, some of which exhibiting orders of magnitude selectivity. Most of the identified compounds can be clustered into two chemical classes: indazole/dihydropyrimidine-containing compounds that are selective for GRK2 and pyrrolopyrimidine-containing compounds that potently inhibit GRK1 and GRK5 but with more modest selectivity. The two most potent inhibitors representing each class, GSK180736A and GSK2163632A, were cocrystallized with GRK2 and GRK1, and their atomic structures were determined to 2.6 and 1.85 Å spacings, respectively. GSK180736A, developed as a Rho-associated, coiled-coil-containing protein kinase inhibitor, binds to GRK2 in a manner analogous to that of paroxetine, whereas GSK2163632A, developed as an insulin-like growth factor 1 receptor inhibitor, occupies a novel region of the GRK active site cleft that could likely be exploited to achieve more selectivity. However, neither compound inhibits GRKs more potently than their initial targets. This data provides the foundation for future efforts to rationally design even more potent and selective GRK inhibitors. PMID:25238254

  3. Characterization of quinone derived protein adducts and their selective identification using redox cycling based chemiluminescence assay.

    PubMed

    Elgawish, Mohamed Saleh; Kishikawa, Naoya; Ohyama, Kaname; Kuroda, Naotaka

    2015-07-17

    The cytotoxic mechanism of many quinones has been correlated to covalent modification of cellular proteins. However, the identification of relevant proteins targets is essential but challenging goals. To better understand the quinones cytotoxic mechanism, human serum albumin (HSA) was incubated in vitro with different concentration of menadione (MQ). In this respect, the initial nucleophilic addition of proteins to quinone converts the conjugates to redox-cycling quinoproteins with altered conformation and secondary structure and extended life span than the short lived, free quinones. The conjugation of MQ with nucleophilic sites likewise, free cysteine as well as ɛ-amino group of lysine residue of HSA has been found to be in concentration dependent manner. The conventional methods for modified proteins identification in complex mixtures are complicated and time consuming. Herein, we describe a highly selective, sensitive, simple, and fast strategy for quinoproteins identification. The suggested strategy exploited the unique redox-cycling capability of quinoproteins in presence of a reductant, dithiothreitol (DTT), to generate reactive oxygen species (ROS) that gave sufficient chemiluminescence (CL) when mixed with luminol. The CL approach is highly selective and sensitive to detect the quinoproteins in ten-fold molar excess of native proteins without adduct enrichment. The approach was also coupled with gel filtration chromatography (GFC) and used to identify adducts in complex mixture of proteins in vitro as well as in rat plasma after MQ administration. Albumin was identified as the main protein in human and rat plasma forming adduct with MQ. Overall, the identification of quinoproteins will encourage further studies of toxicological impact of quinones on human health. PMID:26044383

  4. Routes to covalent catalysis by reactive selection for nascent protein nucleophiles.

    PubMed

    Reshetnyak, Andrey V; Armentano, Maria Francesca; Ponomarenko, Natalia A; Vizzuso, Domenica; Durova, Oxana M; Ziganshin, Rustam; Serebryakova, Marina; Govorun, Vadim; Gololobov, Gennady; Morse, Herbert C; Friboulet, Alain; Makker, Sudesh P; Gabibov, Alexander G; Tramontano, Alfonso

    2007-12-26

    Reactivity-based selection strategies have been used to enrich combinatorial libraries for encoded biocatalysts having revised substrate specificity or altered catalytic activity. This approach can also assist in artificial evolution of enzyme catalysis from protein templates without bias for predefined catalytic sites. The prevalence of covalent intermediates in enzymatic mechanisms suggests the universal utility of the covalent complex as the basis for selection. Covalent selection by phosphonate ester exchange was applied to a phage display library of antibody variable fragments (scFv) to sample the scope and mechanism of chemical reactivity in a naive molecular library. Selected scFv segregated into structurally related covalent and noncovalent binders. Clones that reacted covalently utilized tyrosine residues exclusively as the nucleophile. Two motifs were identified by structural analysis, recruiting distinct Tyr residues of the light chain. Most clones employed Tyr32 in CDR-L1, whereas a unique clone (A.17) reacted at Tyr36 in FR-L2. Enhanced phosphonylation kinetics and modest amidase activity of A.17 suggested a primitive catalytic site. Covalent selection may thus provide access to protein molecules that approximate an early apparatus for covalent catalysis. PMID:18044899

  5. 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

  6. Robust model selection and the statistical classification of languages

    NASA Astrophysics Data System (ADS)

    García, J. E.; González-López, V. A.; Viola, M. L. L.

    2012-10-01

    In this paper we address the problem of model selection for the set of finite memory stochastic processes with finite alphabet, when the data is contaminated. We consider m independent samples, with more than half of them being realizations of the same stochastic process with law Q, which is the one we want to retrieve. We devise a model selection procedure such that for a sample size large enough, the selected process is the one with law Q. Our model selection strategy is based on estimating relative entropies to select a subset of samples that are realizations of the same law. Although the procedure is valid for any family of finite order Markov models, we will focus on the family of variable length Markov chain models, which include the fixed order Markov chain model family. We define the asymptotic breakdown point (ABDP) for a model selection procedure, and we show the ABDP for our procedure. This means that if the proportion of contaminated samples is smaller than the ABDP, then, as the sample size grows our procedure selects a model for the process with law Q. We also use our procedure in a setting where we have one sample conformed by the concatenation of sub-samples of two or more stochastic processes, with most of the subsamples having law Q. We conducted a simulation study. In the application section we address the question of the statistical classification of languages according to their rhythmic features using speech samples. This is an important open problem in phonology. A persistent difficulty on this problem is that the speech samples correspond to several sentences produced by diverse speakers, corresponding to a mixture of distributions. The usual procedure to deal with this problem has been to choose a subset of the original sample which seems to best represent each language. The selection is made by listening to the samples. In our application we use the full dataset without any preselection of samples. We apply our robust methodology estimating

  7. Bayesian Nonlinear Model Selection for Gene Regulatory Networks

    PubMed Central

    Ni, Yang; Stingo, Francesco C.; Baladandayuthapani, Veerabhadran

    2015-01-01

    Summary Gene regulatory networks represent the regulatory relationships between genes and their products and are important for exploring and defining the underlying biological processes of cellular systems. We develop a novel framework to recover the structure of nonlinear gene regulatory networks using semiparametric spline-based directed acyclic graphical models. Our use of splines allows the model to have both flexibility in capturing nonlinear dependencies as well as control of overfitting via shrinkage, using mixed model representations of penalized splines. We propose a novel discrete mixture prior on the smoothing parameter of the splines that allows for simultaneous selection of both linear and nonlinear functional relationships as well as inducing sparsity in the edge selection. Using simulation studies, we demonstrate the superior performance of our methods in comparison with several existing approaches in terms of network reconstruction and functional selection. We apply our methods to a gene expression dataset in glioblastoma multiforme, which reveals several interesting and biologically relevant nonlinear relationships. PMID:25854759

  8. Selective expression of prion protein in peripheral tissues of the adult mouse.

    PubMed

    Ford, M J; Burton, L J; Morris, R J; Hall, S M

    2002-01-01

    The level of expression of normal cellular prion protein, PrP(c) (cellular prion protein), controls both the rate and the route of neuroinvasive infection, from peripheral entry portal to the CNS. Paradoxically, an overview of the distribution of PrP(c) within tissues outside the CNS is lacking. We have used novel antibodies that recognise cellular prion protein in glutaraldehyde-fixed tissue (in order to optimise immunohistochemical labelling of this conformationally labile protein), in combination with in situ hybridisation, to examine the expression of PrP(c) in peripheral tissues of the adult mouse. We found that although prion protein is expressed in many tissues, it is expressed at high levels only in discrete subpopulations of cells. Prominent amongst these are elements of the "hardwired neuroimmune network" that integrate the body's immune defence and neuroendocrine systems under CNS control. These prion protein-expressing elements include small diameter afferent nerves in the skin and the lamina propria of the aerodigestive tract, sympathetic ganglia and nerves, antigen presenting and processing cells (both follicular and non-follicular dendritic cells) and sub-populations of lymphocytes particularly in skin, gut- and bronchus-associated lymphoid tissues. Prion protein is also expressed in the parasympathetic and enteric nervous systems, in the dispersed neuroendocrine system, and in peripheral nervous system axons and their associated Schwann cells. This selective expression of cellular prion protein provides a variety of alternative routes for the propagation and transport of prion infection entering from peripheral sites, either naturally (via the aerodigestive tract or abraded skin) or experimentally (by intraperitoneal injection) to the brain. Key regulatory cells that express prion protein, and in particular enteroendocrine cells in the mucosal wall of the gut, and dendritic cells that convey pathogens from epithelial layers to secondary lymphoid

  9. Balancing selection at the prion protein gene consistent with prehistoric kurulike epidemics.

    PubMed

    Mead, Simon; Stumpf, Michael P H; Whitfield, Jerome; Beck, Jonathan A; Poulter, Mark; Campbell, Tracy; Uphill, James B; Goldstein, David; Alpers, Michael; Fisher, Elizabeth M C; Collinge, John

    2003-04-25

    Kuru is an acquired prion disease largely restricted to the Fore linguistic group of the Papua New Guinea Highlands, which was transmitted during endocannibalistic feasts. Heterozygosity for a common polymorphism in the human prion protein gene (PRNP) confers relative resistance to prion diseases. Elderly survivors of the kuru epidemic, who had multiple exposures at mortuary feasts, are, in marked contrast to younger unexposed Fore, predominantly PRNP 129 heterozygotes. Kuru imposed strong balancing selection on the Fore, essentially eliminating PRNP 129 homozygotes. Worldwide PRNP haplotype diversity and coding allele frequencies suggest that strong balancing selection at this locus occurred during the evolution of modern humans. PMID:12690204

  10. 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

  11. Mechanical strength of 17,134 model proteins and cysteine slipknots.

    PubMed

    Sikora, Mateusz; Sułkowska, Joanna I; Cieplak, Marek

    2009-10-01

    A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations. PMID:19876372

  12. 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.

  13. Tracking Membrane Protein Association in Model Membranes

    PubMed Central

    Reffay, Myriam; Gambin, Yann; Benabdelhak, Houssain; Phan, Gilles; Taulier, Nicolas; Ducruix, Arnaud; Hodges, Robert S.; Urbach, Wladimir

    2009-01-01

    Membrane proteins are essential in the exchange processes of cells. In spite of great breakthrough in soluble proteins studies, membrane proteins structures, functions and interactions are still a challenge because of the difficulties related to their hydrophobic properties. Most of the experiments are performed with detergent-solubilized membrane proteins. However widely used micellar systems are far from the biological two-dimensions membrane. The development of new biomimetic membrane systems is fundamental to tackle this issue. We present an original approach that combines the Fluorescence Recovery After fringe Pattern Photobleaching technique and the use of a versatile sponge phase that makes it possible to extract crucial informations about interactions between membrane proteins embedded in the bilayers of a sponge phase. The clear advantage lies in the ability to adjust at will the spacing between two adjacent bilayers. When the membranes are far apart, the only possible interactions occur laterally between proteins embedded within the same bilayer, whereas when membranes get closer to each other, interactions between proteins embedded in facing membranes may occur as well. After validating our approach on the streptavidin-biotinylated peptide complex, we study the interactions between two membrane proteins, MexA and OprM, from a Pseudomonas aeruginosa efflux pump. The mode of interaction, the size of the protein complex and its potential stoichiometry are determined. In particular, we demonstrate that: MexA is effectively embedded in the bilayer; MexA and OprM do not interact laterally but can form a complex if they are embedded in opposite bilayers; the population of bound proteins is at its maximum for bilayers separated by a distance of about 200 Å, which is the periplasmic thickness of Pseudomonas aeruginosa. We also show that the MexA-OprM association is enhanced when the position and orientation of the protein is restricted by the bilayers. We

  14. 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.

  15. Phenotypic and genotypic characterization of influenza virus mutants selected with the sialidase fusion protein DAS181

    PubMed Central

    Triana-Baltzer, Gallen B.; Sanders, Rebecca L.; Hedlund, Maria; Jensen, Kellie A.; Aschenbrenner, Laura M.; Larson, Jeffrey L.; Fang, Fang

    2011-01-01

    Background Influenza viruses (IFVs) frequently achieve resistance to antiviral drugs, necessitating the development of compounds with novel mechanisms of action. DAS181 (Fludase®), a sialidase fusion protein, may have a reduced potential for generating drug resistance due to its novel host-targeting mechanism of action. Methods IFV strains B/Maryland/1/59 and A/Victoria/3/75 (H3N2) were subjected to >30 passages under increasing selective pressure with DAS181. The DAS181-selected IFV isolates were characterized in vitro and in mice. Results Despite extensive passaging, DAS181-selected viruses exhibited a very low level of resistance to DAS181, which ranged between 3- and 18-fold increase in EC50. DAS181-selected viruses displayed an attenuated phenotype in vitro, as exhibited by slower growth, smaller plaque size and increased particle to pfu ratios relative to wild-type virus. Further, the DAS181 resistance phenotype was unstable and was substantially reversed over time upon DAS181 withdrawal. In mice, the DAS181-selected viruses exhibited no greater virulence than their wild-type counterparts. Genotypic and phenotypic analysis of DAS181-selected viruses revealed mutations in the haemagglutinin (HA) and neuraminidase (NA) molecules and also changes in HA and NA function. Conclusions Results indicate that resistance to DAS181 is minimal and unstable. The DAS181-selected IFV isolates exhibit reduced fitness in vitro, likely due to altered HA and NA functions. PMID:21097900

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

    PubMed Central

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

    2014-01-01

    We propose a procedure associated with the idea of the E-M algorithm for model selection in the presence of missing data. The idea extends the concept of parameters to include both the model and the parameters under the model, and thus allows the model to be part of the E-M iterations. We develop the procedure, known as the E-MS algorithm, under the assumption that the class of candidate models is finite. Some special cases of the procedure are considered, including E-MS with the generalized information criteria (GIC), and E-MS with the adaptive fence (AF; Jiang et al. 2008). We prove numerical convergence of the E-MS algorithm as well as consistency in model selection of the limiting model of the E-MS convergence, for E-MS with GIC and E-MS with AF. We study the impact on model selection of different missing data mechanisms. Furthermore, we carry out extensive simulation studies on the finite-sample performance of the E-MS with comparisons to other procedures. The methodology is also illustrated on a real data analysis involving QTL mapping for an agricultural study on barley grains. PMID:26783375

  17. 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

  18. A CD36-related Transmembrane Protein Is Coordinated with an Intracellular Lipid-binding Protein in Selective Carotenoid Transport for Cocoon Coloration*

    PubMed Central

    Sakudoh, Takashi; Iizuka, Tetsuya; Narukawa, Junko; Sezutsu, Hideki; Kobayashi, Isao; Kuwazaki, Seigo; Banno, Yutaka; Kitamura, Akitoshi; Sugiyama, Hiromu; Takada, Naoko; Fujimoto, Hirofumi; Kadono-Okuda, Keiko; Mita, Kazuei; Tamura, Toshiki; Yamamoto, Kimiko; Tsuchida, Kozo

    2010-01-01

    The transport pathway of specific dietary carotenoids from the midgut lumen to the silk gland in the silkworm, Bombyx mori, is a model system for selective carotenoid transport because several genetic mutants with defects in parts of this pathway have been identified that manifest altered cocoon pigmentation. In the wild-type silkworm, which has both genes, Yellow blood (Y) and Yellow cocoon (C), lutein is transferred selectively from the hemolymph lipoprotein to the silk gland cells where it is accumulated into the cocoon. The Y gene encodes an intracellular carotenoid-binding protein (CBP) containing a lipid-binding domain known as the steroidogenic acute regulatory protein-related lipid transfer domain. Positional cloning and transgenic rescue experiments revealed that the C gene encodes Cameo2, a transmembrane protein gene belonging to the CD36 family genes, some of which, such as the mammalian SR-BI and the fruit fly ninaD, are reported as lipoprotein receptors or implicated in carotenoid transport for visual system. In C mutant larvae, Cameo2 expression was strongly repressed in the silk gland in a specific manner, resulting in colorless silk glands and white cocoons. The developmental profile of Cameo2 expression, CBP expression, and lutein pigmentation in the silk gland of the yellow cocoon strain were correlated. We hypothesize that selective delivery of lutein to specific tissue requires the combination of two components: 1) CBP as a carotenoid transporter in cytosol and 2) Cameo2 as a transmembrane receptor on the surface of the cells. PMID:20053988

  19. Lessons from making the Structural Classification of Proteins (SCOP) and their implications for protein structure modelling

    PubMed Central

    Andreeva, Antonina

    2016-01-01

    The Structural Classification of Proteins (SCOP) database has facilitated the development of many tools and algorithms and it has been successfully used in protein structure prediction and large-scale genome annotations. During the development of SCOP, numerous exceptions were found to topological rules, along with complex evolutionary scenarios and peculiarities in proteins including the ability to fold into alternative structures. This article reviews cases of structural variations observed for individual proteins and among groups of homologues, knowledge of which is essential for protein structure modelling. PMID:27284063

  20. Lessons from making the Structural Classification of Proteins (SCOP) and their implications for protein structure modelling.

    PubMed

    Andreeva, Antonina

    2016-06-15

    The Structural Classification of Proteins (SCOP) database has facilitated the development of many tools and algorithms and it has been successfully used in protein structure prediction and large-scale genome annotations. During the development of SCOP, numerous exceptions were found to topological rules, along with complex evolutionary scenarios and peculiarities in proteins including the ability to fold into alternative structures. This article reviews cases of structural variations observed for individual proteins and among groups of homologues, knowledge of which is essential for protein structure modelling. PMID:27284063

  1. MONNA, a potent and selective blocker for transmembrane protein with unknown function 16/anoctamin-1.

    PubMed

    Oh, Soo-Jin; Hwang, Seok Jin; Jung, Jonghoon; Yu, Kuai; Kim, Jeongyeon; Choi, Jung Yoon; Hartzell, H Criss; Roh, Eun Joo; Lee, C Justin

    2013-11-01

    Transmembrane protein with unknown function 16/anoctamin-1 (ANO1) is a protein widely expressed in mammalian tissues, and it has the properties of the classic calcium-activated chloride channel (CaCC). This protein has been implicated in numerous major physiological functions. However, the lack of effective and selective blockers has hindered a detailed study of the physiological functions of this channel. In this study, we have developed a potent and selective blocker for endogenous ANO1 in Xenopus laevis oocytes (xANO1) using a drug screening method we previously established (Oh et al., 2008). We have synthesized a number of anthranilic acid derivatives and have determined the correlation between biological activity and the nature and position of substituents in these derived compounds. A structure-activity relationship revealed novel chemical classes of xANO1 blockers. The derivatives contain a --NO₂ group on position 5 of a naphthyl group-substituted anthranilic acid, and they fully blocked xANO1 chloride currents with an IC₅₀ < 10 μM. The most potent blocker, N-((4-methoxy)-2-naphthyl)-5-nitroanthranilic acid (MONNA), had an IC₅₀ of 0.08 μM for xANO1. Selectivity tests revealed that other chloride channels such as bestrophin-1, chloride channel protein 2, and cystic fibrosis transmembrane conductance regulator were not appreciably blocked by 10∼30 μM MONNA. The potent and selective blockers for ANO1 identified here should permit pharmacological dissection of ANO1/CaCC function and serve as potential candidates for drug therapy of related diseases such as hypertension, cystic fibrosis, bronchitis, asthma, and hyperalgesia. PMID:23997117

  2. MONNA, a Potent and Selective Blocker for Transmembrane Protein with Unknown Function 16/Anoctamin-1

    PubMed Central

    Oh, Soo-Jin; Hwang, Seok Jin; Jung, Jonghoon; Yu, Kuai; Kim, Jeongyeon; Choi, Jung Yoon; Hartzell, H. Criss

    2013-01-01

    Transmembrane protein with unknown function 16/anoctamin-1 (ANO1) is a protein widely expressed in mammalian tissues, and it has the properties of the classic calcium-activated chloride channel (CaCC). This protein has been implicated in numerous major physiological functions. However, the lack of effective and selective blockers has hindered a detailed study of the physiological functions of this channel. In this study, we have developed a potent and selective blocker for endogenous ANO1 in Xenopus laevis oocytes (xANO1) using a drug screening method we previously established (Oh et al., 2008). We have synthesized a number of anthranilic acid derivatives and have determined the correlation between biological activity and the nature and position of substituents in these derived compounds. A structure-activity relationship revealed novel chemical classes of xANO1 blockers. The derivatives contain a −NO2 group on position 5 of a naphthyl group-substituted anthranilic acid, and they fully blocked xANO1 chloride currents with an IC50 < 10 μM. The most potent blocker, N-((4-methoxy)-2-naphthyl)-5-nitroanthranilic acid (MONNA), had an IC50 of 0.08 μM for xANO1. Selectivity tests revealed that other chloride channels such as bestrophin-1, chloride channel protein 2, and cystic fibrosis transmembrane conductance regulator were not appreciably blocked by 10∼30 μM MONNA. The potent and selective blockers for ANO1 identified here should permit pharmacological dissection of ANO1/CaCC function and serve as potential candidates for drug therapy of related diseases such as hypertension, cystic fibrosis, bronchitis, asthma, and hyperalgesia. PMID:23997117

  3. Secretory protein profiling reveals TNFα inactivation by selective and promiscuous Sec61 modulators

    PubMed Central

    Maifeld, Sarah V.; MacKinnon, Andrew L.; Garrison, Jennifer L.; Sharma, Ajay; Kunkel, Eric J.; Hegde, Ramanujan S.; Taunton, Jack

    2013-01-01

    Summary Cotransins are cyclic heptadepsipeptides that bind the Sec61 translocon to inhibit cotranslational translocation of a subset of secreted and type I transmembrane proteins. The few known cotransin-sensitive substrates are all targeted to the translocon by a cleavable signal sequence, previously shown to be a critical determinant of cotransin sensitivity. By profiling two cotransin variants against a panel of secreted and transmembrane proteins, we demonstrate that cotransin side-chain differences profoundly affect substrate selectivity. Among the most sensitive substrates we identified is the pro-inflammatory cytokine, tumor necrosis factor alpha (TNFα). Like all type II transmembrane proteins, TNFα is targeted to the translocon by its membrane-spanning domain, indicating that a cleavable signal sequence is not strictly required for cotransin sensitivity. Our results thus reveal an unanticipated breadth of translocon substrates whose expression is inhibited by Sec61 modulators. PMID:21944747

  4. Directed evolution of a G protein-coupled receptor for expression, stability, and binding selectivity

    PubMed Central

    Sarkar, Casim A.; Dodevski, Igor; Kenig, Manca; Dudli, Stefan; Mohr, Anja; Hermans, Emmanuel; Plückthun, Andreas

    2008-01-01

    We outline a powerful method for the directed evolution of integral membrane proteins in the inner membrane of Escherichia coli. For a mammalian G protein-coupled receptor, we arrived at a sequence with an order-of-magnitude increase in functional expression that still retains the biochemical properties of wild type. This mutant also shows enhanced heterologous expression in eukaryotes (12-fold in Pichia pastoris and 3-fold in HEK293T cells) and greater stability when solubilized and purified, indicating that the biophysical properties of the protein had been under the pressure of selection. These improvements arise from multiple small contributions, which would be difficult to assemble by rational design. In a second screen, we rapidly pinpointed a single amino acid substitution in wild type that abolishes antagonist binding while retaining agonist-binding affinity. These approaches may alleviate existing bottlenecks in structural studies of these targets by providing sufficient quantities of stable variants in defined conformational states. PMID:18812512

  5. 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. PMID:27059474

  6. 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.

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

    PubMed

    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

    2016-06-01

    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

  8. Selection and characterization of human antibody fragments specific for psoriasin - a cancer associated protein.

    PubMed

    Cyranka-Czaja, Anna; Wulhfard, Sarah; Neri, Dario; Otlewski, Jacek

    2012-03-01

    S100A7 (psoriasin) is a calcium-binding protein that is upregulated in many types of cancer and often associated with poor prognosis. Its role in carcinogenesis has been associated with the stimulation of VEGF and EGF activity. The recent research showed that psoriasin directly interacts with αvβ6 integrin, a protein related to the invasive phenotype of cancer. Moreover, this interaction promotes the αvβ6-dependent invasive activity. The important function of S100A7 in carcinoma development determines a great need for valuable tools enabling its detection, quantification and also activity inhibition. Here, we show the selection of S100A7 specific antibody fragments from the human scFv phage library ETH-2 Gold. We have selected antibody fragments specific for psoriasin, purified them and analyzed by BIAcore affinity measurements. The best clone was subjected to affinity maturation procedure yielding molecule with a subnanomolar affinity towards human S100A7 protein. Selected clone was expressed in a bivalent format and applied for immunostaining analysis, which confirmed the ability of the antigen recognition in physiological conditions. We therefore propose that obtained antibody, that is the first phage display-derived human antibody against psoriasin, can serve as a useful psoriasin binding platform in research, diagnostics and therapy of cancer. PMID:22342672

  9. 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

  10. 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

  11. Variable selection in strong hierarchical semiparametric models for longitudinal data

    PubMed Central

    Zeng, Xianbin; Ma, Shuangge; Qin, Yichen; Li, Yang

    2015-01-01

    In this paper, we consider the variable selection problem in semiparametric additive partially linear models for longitudinal data. Our goal is to identify relevant main effects and corresponding interactions associated with the response variable. Meanwhile, we enforce the strong hierarchical restriction on the model, that is, an interaction can be included in the model only if both the associated main effects are included. Based on B-splines basis approximation for the nonparametric components, we propose an iterative estimation procedure for the model by penalizing the likelihood with a partial group minimax concave penalty (MCP), and use BIC to select the tuning parameter. To further improve the estimation efficiency, we specify the working covariance matrix by maximum likelihood estimation. Simulation studies indicate that the proposed method tends to consistently select the true model and works efficiently in estimation and prediction with finite samples, especially when the true model obeys the strong hierarchy. Finally, the China Stock Market data are fitted with the proposed model to illustrate its effectiveness. PMID:27076867

  12. A model of selective masking in chromatic detection.

    PubMed

    Shepard, Timothy G; Swanson, Emily A; McCarthy, Comfrey L; Eskew, Rhea T

    2016-07-01

    Narrowly tuned, selective noise masking of chromatic detection has been taken as evidence for the existence of a large number of color mechanisms (i.e., higher order color mechanisms). Here we replicate earlier observations of selective masking of tests in the (L,M) plane of cone space when the noise is placed near the corners of the detection contour. We used unipolar Gaussian blob tests with three different noise color directions, and we show that there are substantial asymmetries in the detection contours-asymmetries that would have been missed with bipolar tests such as Gabor patches. We develop a new chromatic detection model, which is based on probability summation of linear cone combinations, and incorporates a linear contrast energy versus noise power relationship that predicts how the sensitivity of these mechanisms changes with noise contrast and chromaticity. With only six unipolar color mechanisms (the same number as the cardinal model), the new model accounts for the threshold contours across the different noise conditions, including the asymmetries and the selective effects of the noises. The key for producing selective noise masking in the (L,M) plane is having more than two mechanisms with opposed L- and M-cone inputs, in which case selective masking can be produced without large numbers of color mechanisms. PMID:27442723

  13. AKAP79 Selectively Enhances Protein Kinase C Regulation of GluR1 at a Ca2+-Calmodulin-dependent Protein Kinase II/Protein Kinase C Site*

    PubMed Central

    Tavalin, Steven J.

    2008-01-01

    Enhancement of AMPA receptor activity in response to synaptic plasticity inducing stimuli may arise, in part, through phosphorylation of the GluR1 AMPA receptor subunit at Ser-831. This site is a substrate for both Ca2+-calmodulin-dependent protein kinase II (CaMKII) and protein kinase C (PKC). However, neuronal protein levels of CaMKII may exceed those of PKC by an order of magnitude. Thus, it is unclear how PKC could effectively regulate this common target site. The multivalent neuronal scaffold A-kinase-anchoring protein 79 (AKAP79) is known to bind PKC and is linked to GluR1 by synapse-associated protein 97 (SAP97). Here, biochemical studies demonstrate that AKAP79 localizes PKC activity near the receptor, thus accelerating Ser-831 phosphorylation. Complementary electrophysiological studies indicate that AKAP79 selectively shifts the dose-dependence for PKC modulation of GluR1 receptor currents ∼20-fold, such that low concentrations of PKC are as effective as much higher CaMKII concentrations. By boosting PKC activity near a target substrate, AKAP79 provides a mechanism to overcome limitations in kinase abundance thereby ensuring faithful signal propagation and efficient modification of AMPA receptor-mediated responses. PMID:18305116

  14. Evolution of off-lattice model proteins under ligand binding constraints

    NASA Astrophysics Data System (ADS)

    Nelson, Erik D.; Grishin, Nick V.

    2016-08-01

    We investigate protein evolution using an off-lattice polymer model evolved to imitate the behavior of small enzymes. Model proteins evolve through mutations to nucleotide sequences (including insertions and deletions) and are selected to fold a