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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. 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

  10. 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

  11. 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

  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. 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

  18. 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

  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. 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

  1. 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.

  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

    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

  10. 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

  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. 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

  20. 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

  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. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  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. 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

  5. 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

  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. 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

  19. Functionalized periodic mesoporous organosilicas for selective adsorption of proteins

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  20. 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. 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.

  5. 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

  6. 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.

  7. 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

  8. 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

  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. 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

  13. 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.

  14. 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.

  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. 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

  18. 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.

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

    SciTech Connect

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

    2009-03-20

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

  2. 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

  3. 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

  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. 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…

  10. 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

  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. 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.

  6. 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

  7. 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

  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. 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

  15. 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

  16. 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

  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. 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.

  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. 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

  4. 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

  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. 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

  10. 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

  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. 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

  17. 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.

  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

    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.

  1. 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

  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. 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

  4. 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

  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. 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.

  10. 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?

  11. 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

  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. 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

  1. 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

  2. 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

  3. 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

  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. 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

  7. 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

  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. 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.

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

    PubMed Central

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

    2016-01-01

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

  11. 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

  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. 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

  15. 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

  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. 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.

  1. 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

  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. 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

  5. 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

  6. 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.

  7. 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

  8. Model-building codes for membrane proteins.

    SciTech Connect

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

    2005-01-01

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

  9. 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

  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