WorldWideScience

Sample records for binding holo-structure prediction

  1. Predicting protein ligand binding motions with the conformation explorer

    Directory of Open Access Journals (Sweden)

    Flores Samuel C

    2011-10-01

    Full Text Available Abstract Background Knowledge of the structure of proteins bound to known or potential ligands is crucial for biological understanding and drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods. Results We describe how to generate ligand binding conformations of proteins that move by hinge bending, the largest class of motions. First, we predict the location of the hinge between domains. Second, we apply an Euler rotation to one of the domains about the hinge point. Third, we compute a short-time dynamical trajectory using Molecular Dynamics to equilibrate the protein and ligand and correct unnatural atomic positions. Fourth, we score the generated structures using a novel fitness function which favors closed or holo structures. By iterating the second through fourth steps we systematically minimize the fitness function, thus predicting the conformational change required for small ligand binding for five well studied proteins. Conclusions We demonstrate that the method in most cases successfully predicts the holo conformation given only an apo structure.

  2. Computational prediction of heme-binding residues by exploiting residue interaction network.

    Directory of Open Access Journals (Sweden)

    Rong Liu

    Full Text Available Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly improved the prediction performance. We also compared the residue interaction networks of heme proteins before and after heme binding and found that the topological features can well characterize the heme-binding sites of apo structures as well as those of holo structures, which led to reliable performance improvement as we applied HemeNet to predicting the binding residues of proteins in the heme-free state. HemeNet web server is freely accessible at http://mleg.cse.sc.edu/hemeNet/.

  3. Computational prediction of heme-binding residues by exploiting residue interaction network.

    Science.gov (United States)

    Liu, Rong; Hu, Jianjun

    2011-01-01

    Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly improved the prediction performance. We also compared the residue interaction networks of heme proteins before and after heme binding and found that the topological features can well characterize the heme-binding sites of apo structures as well as those of holo structures, which led to reliable performance improvement as we applied HemeNet to predicting the binding residues of proteins in the heme-free state. HemeNet web server is freely accessible at http://mleg.cse.sc.edu/hemeNet/. PMID:21991319

  4. ProBiS-CHARMMing: Web Interface for Prediction and Optimization of Ligands in Protein Binding Sites.

    Science.gov (United States)

    Konc, Janez; Miller, Benjamin T; Štular, Tanja; Lešnik, Samo; Woodcock, H Lee; Brooks, Bernard R; Janežič, Dušanka

    2015-11-23

    Proteins often exist only as apo structures (unligated) in the Protein Data Bank, with their corresponding holo structures (with ligands) unavailable. However, apoproteins may not represent the amino-acid residue arrangement upon ligand binding well, which is especially problematic for molecular docking. We developed the ProBiS-CHARMMing web interface by connecting the ProBiS ( http://probis.cmm.ki.si ) and CHARMMing ( http://www.charmming.org ) web servers into one functional unit that enables prediction of protein-ligand complexes and allows for their geometry optimization and interaction energy calculation. The ProBiS web server predicts ligands (small compounds, proteins, nucleic acids, and single-atom ligands) that may bind to a query protein. This is achieved by comparing its surface structure against a nonredundant database of protein structures and finding those that have binding sites similar to that of the query protein. Existing ligands found in the similar binding sites are then transposed to the query according to predictions from ProBiS. The CHARMMing web server enables, among other things, minimization and potential energy calculation for a wide variety of biomolecular systems, and it is used here to optimize the geometry of the predicted protein-ligand complex structures using the CHARMM force field and to calculate their interaction energies with the corresponding query proteins. We show how ProBiS-CHARMMing can be used to predict ligands and their poses for a particular binding site, and minimize the predicted protein-ligand complexes to obtain representations of holoproteins. The ProBiS-CHARMMing web interface is freely available for academic users at http://probis.nih.gov.

  5. Computational Prediction of RNA-Binding Proteins and Binding Sites.

    Science.gov (United States)

    Si, Jingna; Cui, Jing; Cheng, Jin; Wu, Rongling

    2015-01-01

    Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%-8% of all proteins are RNA-binding proteins (RBPs). Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein-RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein-RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions.

  6. Computational Prediction of RNA-Binding Proteins and Binding Sites

    Directory of Open Access Journals (Sweden)

    Jingna Si

    2015-11-01

    Full Text Available Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%–8% of all proteins are RNA-binding proteins (RBPs. Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein–RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein–RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions.

  7. Predicting binding free energies in solution

    CERN Document Server

    Jensen, Jan H

    2015-01-01

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic for others. In paper I summarize some of the many factors that could easily contribute 1-3 kcal/mol errors at 298 K: three-body dispersion effects, molecular symmetry, anharmonicity, spurious imaginary frequencies, insufficient conformational sampling, wrong or changing ionization states, errors in the solvation free energy of ions, and explicit solvent (and ion) effects that are not well-represented by continuum models. While the paper is primarily a synthesis of previously published work there are two new results: the adaptation of Legendre transformed free energies to electronic structure theory and a use of water clusters that maximizes error cancellation in binding free energies computed using explicit solvent molecules. While I focus on binding free energies in aqueous solution the approach also a...

  8. Automated benchmarking of peptide-MHC class I binding predictions

    DEFF Research Database (Denmark)

    Trolle, Thomas; Metushi, Imir G.; Greenbaum, Jason;

    2015-01-01

    Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given...... the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding...

  9. Influence of binding energies of electrons on nuclear mass predictions

    Science.gov (United States)

    Tang, Jing; Niu, Zhong-Ming; Guo, Jian-You

    2016-07-01

    Nuclear mass contains a wealth of nuclear structure information, and has been widely employed to extract the nuclear effective interactions. The known nuclear mass is usually extracted from the experimental atomic mass by subtracting the masses of electrons and adding the binding energy of electrons in the atom. However, the binding energies of electrons are sometimes neglected in extracting the known nuclear masses. The influence of binding energies of electrons on nuclear mass predictions are carefully investigated in this work. If the binding energies of electrons are directly subtracted from the theoretical mass predictions, the rms deviations of nuclear mass predictions with respect to the known data are increased by about 200 keV for nuclei with Z, N ⩾ 8. Furthermore, by using the Coulomb energies between protons to absorb the binding energies of electrons, their influence on the rms deviations is significantly reduced to only about 10 keV for nuclei with Z, N ⩾ 8. However, the binding energies of electrons are still important for the heavy nuclei, about 150 keV for nuclei around Z = 100 and up to about 500 keV for nuclei around Z = 120. Therefore, it is necessary to consider the binding energies of electrons to reliably predict the masses of heavy nuclei at an accuracy of hundreds of keV. Supported by National Natural Science Foundation of China (11205004)

  10. Prediction of MHC class I binding peptides, using SVMHC

    Directory of Open Access Journals (Sweden)

    Elofsson Arne

    2002-09-01

    Full Text Available Abstract Background T-cells are key players in regulating a specific immune response. Activation of cytotoxic T-cells requires recognition of specific peptides bound to Major Histocompatibility Complex (MHC class I molecules. MHC-peptide complexes are potential tools for diagnosis and treatment of pathogens and cancer, as well as for the development of peptide vaccines. Only one in 100 to 200 potential binders actually binds to a certain MHC molecule, therefore a good prediction method for MHC class I binding peptides can reduce the number of candidate binders that need to be synthesized and tested. Results Here, we present a novel approach, SVMHC, based on support vector machines to predict the binding of peptides to MHC class I molecules. This method seems to perform slightly better than two profile based methods, SYFPEITHI and HLA_BIND. The implementation of SVMHC is quite simple and does not involve any manual steps, therefore as more data become available it is trivial to provide prediction for more MHC types. SVMHC currently contains prediction for 26 MHC class I types from the MHCPEP database or alternatively 6 MHC class I types from the higher quality SYFPEITHI database. The prediction models for these MHC types are implemented in a public web service available at http://www.sbc.su.se/svmhc/. Conclusions Prediction of MHC class I binding peptides using Support Vector Machines, shows high performance and is easy to apply to a large number of MHC class I types. As more peptide data are put into MHC databases, SVMHC can easily be updated to give prediction for additional MHC class I types. We suggest that the number of binding peptides needed for SVM training is at least 20 sequences.

  11. A systems biology approach to transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    Full Text Available BACKGROUND: The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates. METHODOLOGY/PRINCIPAL FINDINGS: We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data. CONCLUSIONS/SIGNIFICANCE: Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct

  12. Oxypred: Prediction and Classification of Oxygen-Binding Proteins

    Institute of Scientific and Technical Information of China (English)

    S.; Muthukrishnan; Aarti; Garg; G.P.S.; Raghava

    2007-01-01

    This study describes a method for predicting and classifying oxygen-binding pro- teins. Firstly, support vector machine (SVM) modules were developed using amino acid composition and dipeptide composition for predicting oxygen-binding pro- teins, and achieved maximum accuracy of 85.5% and 87.8%, respectively. Sec- ondly, an SVM module was developed based on amino acid composition, classify- ing the predicted oxygen-binding proteins into six classes with accuracy of 95.8%, 97.5%, 97.5%, 96.9%, 99.4%, and 96.0% for erythrocruorin, hemerythrin, hemo- cyanin, hemoglobin, leghemoglobin, and myoglobin proteins, respectively. Finally, an SVM module was developed using dipeptide composition for classifying the oxygen-binding proteins, and achieved maximum accuracy of 96.1%, 98.7%, 98.7%, 85.6%, 99.6%, and 93.3% for the above six classes, respectively. All modules were trained and tested by five-fold cross validation. Based on the above approach, a web server Oxypred was developed for predicting and classifying oxygen-binding proteins(available from http://www.imtech.res.in/raghava/oxypred/).

  13. Peptide binding predictions for HLA DR, DP and DQ molecules

    DEFF Research Database (Denmark)

    Wang, P.; Sidney, J.; Kim, Y.;

    2010-01-01

    their performance. CONCLUSION: We found that 1) prediction methodologies developed for HLA DR molecules perform equally well for DP or DQ molecules. 2) Prediction performances were significantly increased compared to previous reports due to the larger amounts of training data available. 3) The presence...... include all training data for maximum performance. 4) The recently developed NN-align prediction method significantly outperformed all other algorithms, including a naïve consensus based on all prediction methods. A new consensus method dropping the comparably weak ARB prediction method could outperform......BACKGROUND: MHC class II binding predictions are widely used to identify epitope candidates in infectious agents, allergens, cancer and autoantigens. The vast majority of prediction algorithms for human MHC class II to date have targeted HLA molecules encoded in the DR locus. This reflects...

  14. PRBP: Prediction of RNA-Binding Proteins Using a Random Forest Algorithm Combined with an RNA-Binding Residue Predictor.

    Science.gov (United States)

    Ma, Xin; Guo, Jing; Xiao, Ke; Sun, Xiao

    2015-01-01

    The prediction of RNA-binding proteins is an incredibly challenging problem in computational biology. Although great progress has been made using various machine learning approaches with numerous features, the problem is still far from being solved. In this study, we attempt to predict RNA-binding proteins directly from amino acid sequences. A novel approach, PRBP predicts RNA-binding proteins using the information of predicted RNA-binding residues in conjunction with a random forest based method. For a given protein, we first predict its RNA-binding residues and then judge whether the protein binds RNA or not based on information from that prediction. If the protein cannot be identified by the information associated with its predicted RNA-binding residues, then a novel random forest predictor is used to determine if the query protein is a RNA-binding protein. We incorporated features of evolutionary information combined with physicochemical features (EIPP) and amino acid composition feature to establish the random forest predictor. Feature analysis showed that EIPP contributed the most to the prediction of RNA-binding proteins. The results also showed that the information from the RNA-binding residue prediction improved the overall performance of our RNA-binding protein prediction. It is anticipated that the PRBP method will become a useful tool for identifying RNA-binding proteins. A PRBP Web server implementation is freely available at http://www.cbi.seu.edu.cn/PRBP/.

  15. AB-Bind: Antibody binding mutational database for computational affinity predictions.

    Science.gov (United States)

    Sirin, Sarah; Apgar, James R; Bennett, Eric M; Keating, Amy E

    2016-02-01

    Antibodies (Abs) are a crucial component of the immune system and are often used as diagnostic and therapeutic agents. The need for high-affinity and high-specificity antibodies in research and medicine is driving the development of computational tools for accelerating antibody design and discovery. We report a diverse set of antibody binding data with accompanying structures that can be used to evaluate methods for modeling antibody interactions. Our Antibody-Bind (AB-Bind) database includes 1101 mutants with experimentally determined changes in binding free energies (ΔΔG) across 32 complexes. Using the AB-Bind data set, we evaluated the performance of protein scoring potentials in their ability to predict changes in binding free energies upon mutagenesis. Numerical correlations between computed and observed ΔΔG values were low (r = 0.16-0.45), but the potentials exhibited predictive power for classifying variants as improved vs weakened binders. Performance was evaluated using the area under the curve (AUC) for receiver operator characteristic (ROC) curves; the highest AUC values for 527 mutants with |ΔΔG| > 1.0 kcal/mol were 0.81, 0.87, and 0.88 using STATIUM, FoldX, and Discovery Studio scoring potentials, respectively. Some methods could also enrich for variants with improved binding affinity; FoldX and Discovery Studio were able to correctly rank 42% and 30%, respectively, of the 80 most improved binders (those with ΔΔG < -1.0 kcal/mol) in the top 5% of the database. This modest predictive performance has value but demonstrates the continuing need to develop and improve protein energy functions for affinity prediction. PMID:26473627

  16. Prediction of DNA-binding specificity in zinc finger proteins

    Indian Academy of Sciences (India)

    Sumedha Roy; Shayoni Dutta; Kanika Khanna; Shruti Singla; Durai Sundar

    2012-07-01

    Zinc finger proteins interact via their individual fingers to three base pair subsites on the target DNA. The four key residue positions −1, 2, 3 and 6 on the alpha-helix of the zinc fingers have hydrogen bond interactions with the DNA. Mutating these key residues enables generation of a plethora of combinatorial possibilities that can bind to any DNA stretch of interest. Exploiting the binding specificity and affinity of the interaction between the zinc fingers and the respective DNA can help to generate engineered zinc fingers for therapeutic purposes involving genome targeting. Exploring the structure–function relationships of the existing zinc finger–DNA complexes can aid in predicting the probable zinc fingers that could bind to any target DNA. Computational tools ease the prediction of such engineered zinc fingers by effectively utilizing information from the available experimental data. A study of literature reveals many approaches for predicting DNA-binding specificity in zinc finger proteins. However, an alternative approach that looks into the physico-chemical properties of these complexes would do away with the difficulties of designing unbiased zinc fingers with the desired affinity and specificity. We present a physico-chemical approach that exploits the relative strengths of hydrogen bonding between the target DNA and all combinatorially possible zinc fingers to select the most optimum zinc finger protein candidate.

  17. Predicting accurate absolute binding energies in aqueous solution

    DEFF Research Database (Denmark)

    Jensen, Jan Halborg

    2015-01-01

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic. In this paper I summarize some of the many factors that could easily contribute 1-3 kcal......-represented by continuum models. While I focus on binding free energies in aqueous solution the approach also applies (with minor adjustments) to any free energy difference such as conformational or reaction free energy differences or activation free energies in any solvent....

  18. Automated benchmarking of peptide-MHC class I binding predictions

    DEFF Research Database (Denmark)

    Trolle, Thomas; Metushi, Imir G.; Greenbaum, Jason;

    2015-01-01

    the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding...... educated selections between participating tools. Of the four participating servers, NetMHCpan performed the best, followed by ANN, SMM and finally ARB. Availability and implementation: Up-to-date performance evaluations of each server can be found online at http://tools.iedb.org/auto_bench/mhci/weekly. All...

  19. Prediction of chloride ingress and binding in cement paste

    DEFF Research Database (Denmark)

    Geiker, Mette Rica; Nielsen, Erik Pram; Herforth, Duncan

    2007-01-01

    Finite Difference Model for the ingress of chlorides into concrete which takes into account its multi-component nature. The “composite theory” was then used to predict the diffusivity of each ion based on the phase assemblage present in the hydrated Portland cement paste. Agreement was found between...... in Portland cement pastes at any content of chloride, alkalis, sulfates and carbonate was verified experimentally and found to be equally valid when applied to other data in the literature. The thermodynamic model for predicting the phase equilibria in hydrated Portland cement was introduced into an existing...... profiles for the Cl/Ca ratio predicted by the model and those determined experimentally on 0.45 water/powder ratio Portland cement pastes exposed to 650 mM NaCl for 70 days. This confirms the assumption of essentially instantaneous binding where quasi-equilibrium is established locally. This does not imply...

  20. Prediction of Protein-DNA binding by Monte Carlo method

    Science.gov (United States)

    Deng, Yuefan; Eisenberg, Moises; Korobka, Alex

    1997-08-01

    We present an analysis and prediction of protein-DNA binding specificity based on the hydrogen bonding between DNA, protein, and auxillary clusters of water molecules. Zif268, glucocorticoid receptor, λ-repressor mutant, HIN-recombinase, and tramtrack protein-DNA complexes are studied. Hydrogen bonds are approximated by the Lennard-Jones potential with a cutoff distance between the hydrogen and the acceptor atoms set to 3.2 Åand an angular component based on a dipole-dipole interaction. We use a three-stage docking algorithm: geometric hashing that matches pairs of hydrogen bonding sites; (2) least-squares minimization of pairwise distances to filter out insignificant matches; and (3) Monte Carlo stochastic search to minimize the energy of the system. More information can be obtained from our first paper on this subject [Y.Deng et all, J.Computational Chemistry (1995)]. Results show that the biologically correct base pair is selected preferentially when there are two or more strong hydrogen bonds (with LJ potential lower than -0.20) that bind it to the protein. Predicted sequences are less stable in the case of weaker bonding sites. In general the inclusion of water bridges does increase the number of base pairs for which correct specificity is predicted.

  1. Convolutional neural network architectures for predicting DNA–protein binding

    Science.gov (United States)

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  2. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  3. Machine learning competition in immunology – Prediction of HLA class I binding peptides

    DEFF Research Database (Denmark)

    Zhang, Guang Lan; Ansari, Hifzur Rahman; Bradley, Phil;

    2011-01-01

    of peptide binding, therefore, determines the accuracy of the overall method. Computational predictions of peptide binding to HLA, both class I and class II, use a variety of algorithms ranging from binding motifs to advanced machine learning techniques ( [Brusic et al., 2004] and [Lafuente and Reche, 2009...

  4. Predictive model of cationic surfactant binding to humic substances

    NARCIS (Netherlands)

    Ishiguro, M.; Koopal, L.K.

    2011-01-01

    The humic substances (HS) have a high reactivity with other components in the natural environment. An important factor for the reactivity of HS is their negative charge. Cationic surfactants bind strongly to HS by electrostatic and specific interaction. Therefore, a surfactant binding model is devel

  5. NetMHCpan, a method for MHC class I binding prediction beyond humans

    DEFF Research Database (Denmark)

    Hoof, Ilka; Peters, B; Sidney, J;

    2009-01-01

    immunologists in interpreting cellular immune responses in large out-bred populations is demonstrated. Further, we used NetMHCpan-2.0 to predict potential binding peptides for the pig MHC class I molecule SLA-1*0401. Ninety-three percent of the predicted peptides were demonstrated to bind stronger than 500 n...

  6. Computational Prediction of Heme-Binding Residues by Exploiting Residue Interaction Network

    OpenAIRE

    Rong Liu; Jianjun Hu

    2011-01-01

    Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower ...

  7. A 3D-QSAR-driven approach to binding mode and affinity prediction

    DEFF Research Database (Denmark)

    Tosco, Paolo; Balle, Thomas

    2012-01-01

    A method for predicting the binding mode of a series of ligands is proposed. The procedure relies on three-dimensional quantitative structure-activity relationships (3D-QSAR) and does not require structural knowledge of the binding site. Candidate alignments are automatically built and ranked...... according to a consensus scoring function. 3D-QSAR analysis based on the selected binding mode enables affinity prediction of new drug candidates having less than 10 rotatable bonds....

  8. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng

    2015-12-03

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  9. High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.

    Science.gov (United States)

    Peng, Zhenling; Kurgan, Lukasz

    2015-10-15

    Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro, are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein-protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/.

  10. Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets.

    Science.gov (United States)

    Kokh, Daria B; Czodrowski, Paul; Rippmann, Friedrich; Wade, Rebecca C

    2016-08-01

    Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design. PMID:27399277

  11. Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

    DEFF Research Database (Denmark)

    Kim, Yohan; Sidney, John; Buus, Søren;

    2014-01-01

    Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance ar...

  12. An Overview of the Prediction of Protein DNA-Binding Sites

    Directory of Open Access Journals (Sweden)

    Jingna Si

    2015-03-01

    Full Text Available Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

  13. A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules

    OpenAIRE

    Bjoern Peters; Huynh-Hoa Bui; Sune Frankild; Morten Nielson; Claus Lundegaard; Emrah Kostem; Derek Basch; Kasper Lamberth; Mikkel Harndahl; Ward Fleri; Wilson, Stephen S; John Sidney; Ole Lund; Soren Buus; Alessandro Sette

    2006-01-01

    Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, an...

  14. A community resource benchmarking predictions of peptide binding to MHC-I molecules.

    OpenAIRE

    Bjoern Peters; Huynh-Hoa Bui; Sune Frankild; Morten Nielson; Claus Lundegaard; Emrah Kostem; Derek Basch; Kasper Lamberth; Mikkel Harndahl; Ward Fleri; Wilson, Stephen S; John Sidney; Ole Lund; Soren Buus; Alessandro Sette

    2006-01-01

    Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, an...

  15. A community resource benchmarking predictions of peptide binding to MHC-I molecules

    OpenAIRE

    Peters, B; Bui, HH; Pletscher-Frankild, Sune; Nielsen, Morten; Lundegaard, Claus; Kostem, E; Basch, D; Lamberth, K.; Harndahl, M.; Fleri, W.; Wilson, SS; Sidney, J; Lund, Ole; Buus, S.; Sette, Alessandro

    2006-01-01

    Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, an...

  16. Prediction of SAMPL3 Host-Guest Affinities with the Binding Energy Distribution Analysis Method (BEDAM)

    OpenAIRE

    Gallicchio, Emilio; Ronald M Levy

    2012-01-01

    BEDAM calculations are described to predict the free energies of binding of a series of anaesthetic drugs to a recently characterized acyclic cucurbituril host. The modeling predictions, conducted as part of the SAMPL3 host-guest affinity blind challenge, are generally in good quantitative agreement with the experimental measurements. The correlation coefficient between computed and measured binding free energies is 70% with high statistical significance. Multiple conformational stereoisomers...

  17. A community resource benchmarking predictions of peptide binding to MHC-I molecules

    DEFF Research Database (Denmark)

    Peters, B; Bui, HH; Pletscher-Frankild, Sune;

    2006-01-01

    of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, and chimpanzee MHC class I alleles. We use this data to establish a set of benchmark predictions with one...... neural network method and two matrix-based prediction methods extensively utilized in our groups. In general, the neural network outperforms the matrix-based predictions mainly due to its ability to generalize even on a small amount of data. We also retrieved predictions from tools publicly available...... of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current...

  18. Genome-wide prediction, display and refinement of binding sites with information theory-based models

    Directory of Open Access Journals (Sweden)

    Leeder J Steven

    2003-09-01

    Full Text Available Abstract Background We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. Results Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths

  19. A Novel Approach to Predict Core Residues on Cancer-Related DNA-Binding Domains

    OpenAIRE

    Ka-Chun Wong

    2016-01-01

    Protein–DNA interactions are involved in different cancer pathways. In particular, the DNA-binding domains of proteins can determine where and how gene regulatory regions are bound in different cell lines at different stages. Therefore, it is essential to develop a method to predict and locate the core residues on cancer-related DNA-binding domains. In this study, we propose a computational method to predict and locate core residues on DNA-binding domains. In particular, we have selected the ...

  20. Spatial distribution of predicted transcription factor binding sites in Drosophila ChIP peaks.

    Science.gov (United States)

    Pettie, Kade P; Dresch, Jacqueline M; Drewell, Robert A

    2016-08-01

    In the development of the Drosophila embryo, gene expression is directed by the sequence-specific interactions of a large network of protein transcription factors (TFs) and DNA cis-regulatory binding sites. Once the identity of the typically 8-10bp binding sites for any given TF has been determined by one of several experimental procedures, the sequences can be represented in a position weight matrix (PWM) and used to predict the location of additional TF binding sites elsewhere in the genome. Often, alignments of large (>200bp) genomic fragments that have been experimentally determined to bind the TF of interest in Chromatin Immunoprecipitation (ChIP) studies are trimmed under the assumption that the majority of the binding sites are located near the center of all the aligned fragments. In this study, ChIP/chip datasets are analyzed using the corresponding PWMs for the well-studied TFs; CAUDAL, HUNCHBACK, KNIRPS and KRUPPEL, to determine the distribution of predicted binding sites. All four TFs are critical regulators of gene expression along the anterio-posterior axis in early Drosophila development. For all four TFs, the ChIP peaks contain multiple binding sites that are broadly distributed across the genomic region represented by the peak, regardless of the prediction stringency criteria used. This result suggests that ChIP peak trimming may exclude functional binding sites from subsequent analyses.

  1. Prediction of MHC binding peptides and epitopes from alfalfa mosaic virus.

    Science.gov (United States)

    Gomase, Virendra S; Kale, Karbhari V; Chikhale, Nandkishor J; Changbhale, Smruti S

    2007-08-01

    Peptide fragments from alfalfa mosaic virus involved multiple antigenic components directing and empowering the immune system to protect the host from infection. MHC molecules are cell surface proteins, which take active part in host immune reactions and involvement of MHC class-I & II in response to almost all antigens. Coat protein of alfalfa mosaic virus contains 221 aa residues. Analysis found five MHC ligands in coat protein as 64-LSSFNGLGV-72; 86- RILEEDLIY-94; 96-MVFSITPSY-104; 100- ITPSYAGTF-108; 110- LTDDVTTED-118; having rescaled binding affinity and c-terminal cleavage affinity more than 0.5. The predicted binding affinity is normalized by the 1% fractil. The MHC peptide binding is predicted using neural networks trained on c-terminals of known epitopes. In analysis predicted MHC/peptide binding is a log transformed value related to the IC50 values in nM units. Total numbers of peptides found are 213. Predicted MHC binding regions act like red flags for antigen specific and generate immune response against the parent antigen. So a small fragment of antigen can induce immune response against whole antigen. This theme is implemented in designing subunit and synthetic peptide vaccines. The sequence analysis method allows potential drug targets to identify active sites against plant diseases. The method integrates prediction of peptide MHC class I binding; proteosomal c-terminal cleavage and TAP transport efficiency. PMID:17691913

  2. A Prediction Method of Binding Free Energy of Protein and Ligand

    Science.gov (United States)

    Yang, Kun; Wang, Xicheng

    2010-05-01

    Predicting the binding free energy is an important problem in bimolecular simulation. Such prediction would be great benefit in understanding protein functions, and may be useful for computational prediction of ligand binding strengths, e.g., in discovering pharmaceutical drugs. Free energy perturbation (FEP)/thermodynamics integration (TI) is a classical method to explicitly predict free energy. However, this method need plenty of time to collect datum, and that attempts to deal with some simple systems and small changes of molecular structures. Another one for estimating ligand binding affinities is linear interaction energy (LIE) method. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. However, it also is time-consuming work. In this paper, a new prediction method based on steered molecular dynamics (SMD) with direction optimization is developed to compute binding free energy. Jarzynski's equality is used to derive the PMF or free-energy. The results for two numerical examples are presented, showing that the method has good accuracy and efficiency. The novel method can also simulate whole binding proceeding and give some important structural information about development of new drugs.

  3. Major histocompatibility complex class I binding predictions as a tool in epitope discovery

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Buus, Søren;

    2010-01-01

    Over the last decade, in silico models of the major histocompatibility complex (MHC) class I pathway have developed significantly. Before, peptide binding could only be reliably modelled for a few major human or mouse histocompatibility molecules; now, high-accuracy predictions are available...... for any human leucocyte antigen (HLA) -A or -B molecule with known protein sequence. Furthermore, peptide binding to MHC molecules from several non-human primates, mouse strains and other mammals can now be predicted. In this review, a number of different prediction methods are briefly explained...

  4. A community resource benchmarking predictions of peptide binding to MHC-I molecules.

    Directory of Open Access Journals (Sweden)

    Bjoern Peters

    2006-06-01

    Full Text Available Recognition of peptides bound to major histocompatibility complex (MHC class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, and chimpanzee MHC class I alleles. We use this data to establish a set of benchmark predictions with one neural network method and two matrix-based prediction methods extensively utilized in our groups. In general, the neural network outperforms the matrix-based predictions mainly due to its ability to generalize even on a small amount of data. We also retrieved predictions from tools publicly available on the internet. While differences in the data used to generate these predictions hamper direct comparisons, we do conclude that tools based on combinatorial peptide libraries perform remarkably well. The transparent prediction evaluation on this dataset provides tool developers with a benchmark for comparison of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current practice of tool developers having to generate reference predictions themselves, which can lead to underestimating the performance of prediction methods they are not as familiar with as their own. The overall goal of this effort is to provide a transparent prediction evaluation allowing bioinformaticians to identify promising features of prediction methods and providing guidance to immunologists regarding the reliability of prediction tools.

  5. Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms

    Directory of Open Access Journals (Sweden)

    Feng Lin

    2007-11-01

    Full Text Available Abstract Background Peptides binding to Major Histocompatibility Complex (MHC class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides. In this paper, we propose two approaches using multi-objective evolutionary algorithms (MOEA for predicting peptides binding to MHC class II molecules. One uses the information from both binders and non-binders for self-discovery of motifs. The other, in addition, uses information from experimentally determined motifs for guided-discovery of motifs. Results The proposed methods are intended for finding peptides binding to MHC class II I-Ag7 molecule – a promiscuous binder to a large number of low affinity peptides. Cross-validation results across experiments on two motifs derived for I-Ag7 datasets demonstrate better generalization abilities and accuracies of the present method over earlier approaches. Further, the proposed method was validated and compared on two publicly available benchmark datasets: (1 an ensemble of qualitative HLA-DRB1*0401 peptide data obtained from five different sources, and (2 quantitative peptide data obtained for sixteen different alleles comprising of three mouse alleles and thirteen HLA alleles. The proposed method outperformed earlier methods on most datasets, indicating that it is well suited for finding peptides binding to MHC class II molecules. Conclusion We present two MOEA-based algorithms for finding motifs

  6. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

    Science.gov (United States)

    Kang, Juanjuan; Ru, Beibei; Zhou, Peng

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community.

  7. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides.

    Science.gov (United States)

    He, Bifang; Kang, Juanjuan; Ru, Beibei; Ding, Hui; Zhou, Peng; Huang, Jian

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community. PMID:27610387

  8. Prediction of the key binding site of odorant-binding protein of Holotrichia oblita Faldermann (Coleoptera: Scarabaeida).

    Science.gov (United States)

    Zhuang, X; Wang, Q; Wang, B; Zhong, T; Cao, Y; Li, K; Yin, J

    2014-06-01

    The scarab beetle Holotrichia oblita Faldermann (Coleoptera: Scarabaeidae) is a predominant underground pest in the northern parts of China, and its larvae (grubs) cause great economic losses because of its wide range of host plants and covert habitats. Environmentally friendly strategies for controlling adults would have novel and broad potential applications. One potential pest management measure is the regulation of olfactory chemoreception to control target insect pests. In the process of olfactory recognition, odorant-binding proteins (OBPs) are believed to carry hydrophobic odorants from the environment to the surface of olfactory receptor neurons. To obtain a better understanding of the relationship between OBP structures and their ligands, homology modelling and molecular docking have been conducted on the interaction between HoblOBP1 and hexyl benzoate in the present study. Based on the results, site-directed mutagenesis and binding experiments were combined to describe the binding sites of HoblOBP1 and to explore its ligand-binding mechanism. After homology modelling of HoblOBP1, it was found that the three-dimensional structure of HoblOBP1 consists of six α-helices and three disulphide bridges that connect the helices, and the hydrophobic pockets are both composed of five helices. Based on the docking study, we found that van der Waals interactions and hydrophobic interactions are both important in the bonding between HoblOBP1 and hexyl benzoate. Intramolecular residues formed the hydrogen bonds in the C terminus of the protein and the bonds are crucial for the ligand-binding specificity. Finally, MET48, ILE80 and TYR111 are binding sites predicted for HoblOBP1. Using site-directed mutagenesis and fluorescence assays, it was found that ligands could not be recognized by mutant of Tyr111. A possible explanation is that the compound could not be recognized by the mutant, and remains in the binding cavity because of the loss of the intramolecular

  9. Computational protocol for predicting the binding affinities of zinc containing metalloprotein-ligand complexes.

    Science.gov (United States)

    Jain, Tarun; Jayaram, B

    2007-06-01

    Zinc is one of the most important metal ions found in proteins performing specific functions associated with life processes. Coordination geometry of the zinc ion in the active site of the metalloprotein-ligand complexes poses a challenge in determining ligand binding affinities accurately in structure-based drug design. We report here an all atom force field based computational protocol for estimating rapidly the binding affinities of zinc containing metalloprotein-ligand complexes, considering electrostatics, van der Waals, hydrophobicity, and loss in conformational entropy of protein side chains upon ligand binding along with a nonbonded approach to model the interactions of the zinc ion with all the other atoms of the complex. We examined the sensitivity of the binding affinity predictions to the choice of Lennard-Jones parameters, partial atomic charges, and dielectric treatments adopted for system preparation and scoring. The highest correlation obtained was R2 = 0.77 (r = 0.88) for the predicted binding affinity against the experiment on a heterogenous dataset of 90 zinc containing metalloprotein-ligand complexes consisting of five unique protein targets. Model validation and parameter analysis studies underscore the robustness and predictive ability of the scoring function. The high correlation obtained suggests the potential applicability of the methodology in designing novel ligands for zinc-metalloproteins. The scoring function has been web enabled for free access at www.scfbio-iitd.res.in/software/drugdesign/bapplz.jsp as BAPPL-Z server (Binding Affinity Prediction of Protein-Ligand complexes containing Zinc metal ions).

  10. Blind prediction of host-guest binding affinities: A new SAMPL3 challenge

    OpenAIRE

    Muddana, Hari S.; Varnado, C. Daniel; Bielawski, Christopher W.; Urbach, Adam R.; Isaacs, Lyle; Geballe, Matthew T; Gilson, Michael K.

    2012-01-01

    The computational prediction of protein-ligand binding affinities is of central interest in early-stage drug-discovery, and there is a widely recognized need for improved methods. Low molecular weight receptors and their ligands—i.e. host-guest systems – represent valuable test-beds for such affinity prediction methods, because their small size makes for fast calculations and relatively facile numerical convergence. The SAMPL3 community exercise included the first ever blind prediction challe...

  11. Regression applied to protein binding site prediction and comparison with classification

    Directory of Open Access Journals (Sweden)

    Gala Jean-Luc

    2009-09-01

    Full Text Available Abstract Background The structural genomics centers provide hundreds of protein structures of unknown function. Therefore, developing methods enabling the determination of a protein function automatically is imperative. The determination of a protein function can be achieved by studying the network of its physical interactions. In this context, identifying a potential binding site between proteins is of primary interest. In the literature, methods for predicting a potential binding site location generally are based on classification tools. The aim of this paper is to show that regression tools are more efficient than classification tools for patches based binding site predictors. For this purpose, we developed a patches based binding site localization method usable with either regression or classification tools. Results We compared predictive performances of regression tools with performances of machine learning classifiers. Using leave-one-out cross-validation, we showed that regression tools provide better predictions than classification ones. Among regression tools, Multilayer Perceptron ranked highest in the quality of predictions. We compared also the predictive performance of our patches based method using Multilayer Perceptron with the performance of three other methods usable through a web server. Our method performed similarly to the other methods. Conclusion Regression is more efficient than classification when applied to our binding site localization method. When it is possible, using regression instead of classification for other existing binding site predictors will probably improve results. Furthermore, the method presented in this work is flexible because the size of the predicted binding site is adjustable. This adaptability is useful when either false positive or negative rates have to be limited.

  12. SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations

    Directory of Open Access Journals (Sweden)

    Marharyta Petukh

    2016-04-01

    Full Text Available Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.

  13. Accuracy of binding mode prediction with a cascadic stochastic tunneling method.

    Science.gov (United States)

    Fischer, Bernhard; Basili, Serena; Merlitz, Holger; Wenzel, Wolfgang

    2007-07-01

    We investigate the accuracy of the binding modes predicted for 83 complexes of the high-resolution subset of the ASTEX/CCDC receptor-ligand database using the atomistic FlexScreen approach with a simple forcefield-based scoring function. The median RMS deviation between experimental and predicted binding mode was just 0.83 A. Over 80% of the ligands dock within 2 A of the experimental binding mode, for 60 complexes the docking protocol locates the correct binding mode in all of ten independent simulations. Most docking failures arise because (a) the experimental structure clashed in our forcefield and is thus unattainable in the docking process or (b) because the ligand is stabilized by crystal water.

  14. Accuracy of binding mode prediction with a cascadic stochastic tunneling method.

    Science.gov (United States)

    Fischer, Bernhard; Basili, Serena; Merlitz, Holger; Wenzel, Wolfgang

    2007-07-01

    We investigate the accuracy of the binding modes predicted for 83 complexes of the high-resolution subset of the ASTEX/CCDC receptor-ligand database using the atomistic FlexScreen approach with a simple forcefield-based scoring function. The median RMS deviation between experimental and predicted binding mode was just 0.83 A. Over 80% of the ligands dock within 2 A of the experimental binding mode, for 60 complexes the docking protocol locates the correct binding mode in all of ten independent simulations. Most docking failures arise because (a) the experimental structure clashed in our forcefield and is thus unattainable in the docking process or (b) because the ligand is stabilized by crystal water. PMID:17427957

  15. A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction

    Directory of Open Access Journals (Sweden)

    Wang Renxiao

    2010-04-01

    Full Text Available Abstract Background Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propose a general knowledge-guided scoring (KGS strategy to tackle this problem. Our KGS strategy computes the binding constant of a given protein-ligand complex based on the known binding constant of an appropriate reference complex. A good training set that includes a sufficient number of protein-ligand complexes with known binding data needs to be supplied for finding the reference complex. The reference complex is required to share a similar pattern of key protein-ligand interactions to that of the complex of interest. Thus, some uncertain factors in protein-ligand binding may cancel out, resulting in a more accurate prediction of absolute binding constants. Results In our study, an automatic algorithm was developed for summarizing key protein-ligand interactions as a pharmacophore model and identifying the reference complex with a maximal similarity to the query complex. Our KGS strategy was evaluated in combination with two scoring functions (X-Score and PLP on three test sets, containing 112 HIV protease complexes, 44 carbonic anhydrase complexes, and 73 trypsin complexes, respectively. Our results obtained on crystal structures as well as computer-generated docking poses indicated that application of the KGS strategy produced more accurate predictions especially when X-Score or PLP alone did not perform well. Conclusions Compared to other targeted scoring functions, our KGS strategy does not require any re-parameterization or modification on current scoring methods, and its application is not tied to certain systems. The effectiveness of our KGS strategy is in theory proportional to the ever-increasing knowledge of experimental protein-ligand binding data. Our KGS strategy may serve as a more practical remedy for current scoring functions to improve their

  16. Limitations of Ab Initio Predictions of Peptide Binding to MHC Class II Molecules

    DEFF Research Database (Denmark)

    Zhang, Hao; Lund, Ole; Nielsen, Morten;

    2010-01-01

    Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based...... on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical...... methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results...

  17. Predicting the Impact of Missense Mutations on Protein-Protein Binding Affinity.

    Science.gov (United States)

    Li, Minghui; Petukh, Marharyta; Alexov, Emil; Panchenko, Anna R

    2014-04-01

    The crucial prerequisite for proper biological function is the protein's ability to establish highly selective interactions with macromolecular partners. A missense mutation that alters the protein binding affinity may cause significant perturbations or complete abolishment of the function, potentially leading to diseases. The availability of computational methods to evaluate the impact of mutations on protein-protein binding is critical for a wide range of biomedical applications. Here, we report an efficient computational approach for predicting the effect of single and multiple missense mutations on protein-protein binding affinity. It is based on a well-tested simulation protocol for structure minimization, modified MM-PBSA and statistical scoring energy functions with parameters optimized on experimental sets of several thousands of mutations. Our simulation protocol yields very good agreement between predicted and experimental values with Pearson correlation coefficients of 0.69 and 0.63 and root-mean-square errors of 1.20 and 1.90 kcal mol(-1) for single and multiple mutations, respectively. Compared with other available methods, our approach achieves high speed and prediction accuracy and can be applied to large datasets generated by modern genomics initiatives. In addition, we report a crucial role of water model and the polar solvation energy in estimating the changes in binding affinity. Our analysis also reveals that prediction accuracy and effect of mutations on binding strongly depends on the type of mutation and its location in a protein complex. PMID:24803870

  18. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  19. Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

    Science.gov (United States)

    Brown, Jodian A; Espiritu, Marie V; Abraham, Joel; Thorpe, Ian F

    2016-08-15

    The identification of ligand-binding sites is often the first step in drug targeting and design. To date there are numerous computational tools available to predict ligand binding sites. These tools can guide or mitigate the need for experimental methods to identify binding sites, which often require significant resources and time. Here, we evaluate four ligand-binding site predictor (LBSP) tools for their ability to predict allosteric sites within the Hepatitis C Virus (HCV) polymerase. Our results show that the LISE LBSP is able to identify all three target allosteric sites within the HCV polymerase as well as a known allosteric site in the Coxsackievirus polymerase. LISE was then employed to identify novel binding sites within the polymerases of the Dengue, West Nile, and Foot-and-mouth Disease viruses. Our results suggest that all three viral polymerases have putative sites that share structural or chemical similarities with allosteric pockets of the HCV polymerase. Thus, these binding locations may represent an evolutionarily conserved structural feature of several viral polymerases that could be exploited for the development of small molecule therapeutics. PMID:27262620

  20. Predicting RNA-binding sites of proteins using support vector machines and evolutionary information

    Directory of Open Access Journals (Sweden)

    Su Emily

    2008-12-01

    Full Text Available Abstract Background RNA-protein interaction plays an essential role in several biological processes, such as protein synthesis, gene expression, posttranscriptional regulation and viral infectivity. Identification of RNA-binding sites in proteins provides valuable insights for biologists. However, experimental determination of RNA-protein interaction remains time-consuming and labor-intensive. Thus, computational approaches for prediction of RNA-binding sites in proteins have become highly desirable. Extensive studies of RNA-binding site prediction have led to the development of several methods. However, they could yield low sensitivities in trade-off for high specificities. Results We propose a method, RNAProB, which incorporates a new smoothed position-specific scoring matrix (PSSM encoding scheme with a support vector machine model to predict RNA-binding sites in proteins. Besides the incorporation of evolutionary information from standard PSSM profiles, the proposed smoothed PSSM encoding scheme also considers the correlation and dependency from the neighboring residues for each amino acid in a protein. Experimental results show that smoothed PSSM encoding significantly enhances the prediction performance, especially for sensitivity. Using five-fold cross-validation, our method performs better than the state-of-the-art systems by 4.90%~6.83%, 0.88%~5.33%, and 0.10~0.23 in terms of overall accuracy, specificity, and Matthew's correlation coefficient, respectively. Most notably, compared to other approaches, RNAProB significantly improves sensitivity by 7.0%~26.9% over the benchmark data sets. To prevent data over fitting, a three-way data split procedure is incorporated to estimate the prediction performance. Moreover, physicochemical properties and amino acid preferences of RNA-binding proteins are examined and analyzed. Conclusion Our results demonstrate that smoothed PSSM encoding scheme significantly enhances the performance of RNA-binding

  1. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data

    Science.gov (United States)

    Ribay, Kathryn; Kim, Marlene T.; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

    2016-01-01

    Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR

  2. Calciomics:prediction and analysis of EF-hand calcium binding proteins by protein engineering

    Institute of Scientific and Technical Information of China (English)

    YANG; Jenny; Jie

    2010-01-01

    Ca2+ plays a pivotal role in the physiology and biochemistry of prokaryotic and mammalian organisms.Viruses also utilize the universal Ca2+ signal to create a specific cellular environment to achieve coexistence with the host,and to propagate.In this paper we first describe our development of a grafting approach to understand site-specific Ca2+ binding properties of EF-hand proteins with a helix-loop-helix Ca2+ binding motif,then summarize our prediction and identification of EF-hand Ca2+ binding sites on a genome-wide scale in bacteria and virus,and next report the application of the grafting approach to probe the metal binding capability of predicted EF-hand motifs within the streptococcal hemoprotein receptor(Shr) of Streptococcus pyrogenes and the nonstructural protein 1(nsP1) of Sindbis virus.When methods such as the grafting approach are developed in conjunction with prediction algorithms we are better able to probe continuous Ca2+-binding sites that have been previously underrepresented due to the limitation of conventional methodology.

  3. Prediction and experimental characterization of nsSNPs altering human PDZ-binding motifs.

    Directory of Open Access Journals (Sweden)

    David Gfeller

    Full Text Available Single nucleotide polymorphisms (SNPs are a major contributor to genetic and phenotypic variation within populations. Non-synonymous SNPs (nsSNPs modify the sequence of proteins and can affect their folding or binding properties. Experimental analysis of all nsSNPs is currently unfeasible and therefore computational predictions of the molecular effect of nsSNPs are helpful to guide experimental investigations. While some nsSNPs can be accurately characterized, for instance if they fall into strongly conserved or well annotated regions, the molecular consequences of many others are more challenging to predict. In particular, nsSNPs affecting less structured, and often less conserved regions, are difficult to characterize. Binding sites that mediate protein-protein or other protein interactions are an important class of functional sites on proteins and can be used to help interpret nsSNPs. Binding sites targeted by the PDZ modular peptide recognition domain have recently been characterized. Here we use this data to show that it is possible to computationally identify nsSNPs in PDZ binding motifs that modify or prevent binding to the proteins containing the motifs. We confirm these predictions by experimentally validating a selected subset with ELISA. Our work also highlights the importance of better characterizing linear motifs in proteins as many of these can be affected by genetic variations.

  4. TEPITOPEpan: extending TEPITOPE for peptide binding prediction covering over 700 HLA-DR molecules.

    Directory of Open Access Journals (Sweden)

    Lianming Zhang

    Full Text Available MOTIVATION: Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules. METHOD: We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE. RESULT: The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in

  5. Description and prediction of peptide-MHC binding: the 'human MHC project'

    DEFF Research Database (Denmark)

    Buus, S

    1999-01-01

    MHC molecules are crucially involved in controlling the specific immune system. They are highly polymorphic receptors sampling peptides from the cellular environment and presenting these peptides for scrutiny by immune cells. Recent advances in combinatorial peptide chemistry have improved the de...... the description and prediction of peptide-MHC binding. It is envisioned that a complete mapping of human immune reactivities will be possible....

  6. STarMir Tools for Prediction of microRNA Binding Sites.

    Science.gov (United States)

    Kanoria, Shaveta; Rennie, William; Liu, Chaochun; Carmack, C Steven; Lu, Jun; Ding, Ye

    2016-01-01

    MicroRNAs (miRNAs) are a class of endogenous short noncoding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high-throughput miRNA binding data from cross-linking immunoprecipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural, and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms (Liu et al., Nucleic Acids Res 41:e138, 2013). Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html . PMID:27665594

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

    Science.gov (United States)

    Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

    2015-12-15

    Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

  9. Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams

    Directory of Open Access Journals (Sweden)

    Fernandez-Fuentes Narcis

    2011-08-01

    Full Text Available Abstract Background Protein binding site prediction by computational means can yield valuable information that complements and guides experimental approaches to determine the structure of protein complexes. Predictions become even more relevant and timely given the current resolution of protein interaction maps, where there is a very large and still expanding gap between the available information on: (i which proteins interact and (ii how proteins interact. Proteins interact through exposed residues that present differential physicochemical properties, and these can be exploited to identify protein interfaces. Results Here we present VORFFIP, a novel method for protein binding site prediction. The method makes use of broad set of heterogeneous data and defined of residue environment, by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensemble classifier. Four sets of residue features (structural, energy terms, sequence conservation, and crystallographic B-factors used in different combinations together with three definitions of residue environment (Voronoi Diagrams, sequence sliding window, and Euclidian distance have been analyzed in order to maximize the performance of the method. Conclusions The integration of different forms information such as structural features, energy term, evolutionary conservation and crystallographic B-factors, improves the performance of binding site prediction. Including the information of neighbouring residues also improves the prediction of protein interfaces. Among the different approaches that can be used to define the environment of exposed residues, Voronoi Diagrams provide the most accurate description. Finally, VORFFIP compares favourably to other methods reported in the recent literature.

  10. Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods

    Directory of Open Access Journals (Sweden)

    Daniel Barry Roche

    2015-12-01

    Full Text Available Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP and the Continuous Automated Model EvaluatiOn (CAMEO projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

  11. Genome-wide de novo prediction of cis-regulatory binding sites in prokaryotes

    Science.gov (United States)

    Zhang, Shaoqiang; Xu, Minli; Su, Zhengchang

    2009-01-01

    Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We designed our algorithm to circumvent three identified difficulties for CRBS prediction using comparative genomics principles based on a new method for the selection of reference genomes, a new metric for measuring the similarity of CRBSs, and a new graph clustering procedure. When operon structures are correctly predicted, our algorithm can predict 81% of known individual binding sites belonging to 94% of known cis-regulatory motifs in the Escherichia coli K12 genome, while achieving high prediction specificity. Our algorithm has also achieved similar prediction accuracy in the Bacillus subtilis genome, suggesting that it is very robust, and thus can be applied to any other sequenced prokaryotic genome. When compared with the prior state-of-the-art algorithms, our algorithm outperforms them in both prediction sensitivity and specificity. PMID:19383880

  12. Predicting Polymerase Ⅱ Core Promoters by Cooperating Transcription Factor Binding Sites in Eukaryotic Genes

    Institute of Scientific and Technical Information of China (English)

    Xiao-Tu MA; Min-Ping QIAN; Hai-Xu TANG

    2004-01-01

    Several discriminate functions for predicting core promoters that based on the potential cooperation between transcription factor binding sites (TFBSs) are discussed. It is demonstrated that the promoter predicting accuracy is improved when the cooperation among TFBSs is taken into consideration.The core promoter region of a newly discovered gene CKLFSF1 is predicted to locate more than 1.5 kb far away from the 5′ end of the transcript and in the last intron of its upstream gene, which is experimentally confirmed later. The core promoters of 3402 human RefSeq sequences, obtained by extending the mRNAs in human genome sequences, are predicted by our algorithm, and there are about 60% of the predicted core promoters locating within the ± 500 bp region relative to the annotated transcription start site.

  13. The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

    Science.gov (United States)

    Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

    2011-07-01

    The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

  14. Theoretical prediction of the binding free energy for mutants of replication protein A.

    Science.gov (United States)

    Carra, Claudio; Saha, Janapriya; Cucinotta, Francis A

    2012-07-01

    The replication protein A (RPA) is a heterotrimeric (70, 32, and 14 kDa subunits), single stranded DNA (ssDNA) binding protein required for pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Studies based on deletions and mutations have identified the high affinity ssDNA binding domains in the 70 kDa subunit of RPA, regions A and B. Individually, the domain A and B have a low affinity for ssDNA, while tandems composed of AA, AB, BB, and BA sequences bind the ssDNA with moderate to high affinity. Single and double point mutations on polar residues in the binding domains leads to a reduction in affinity of RPA for ssDNA, in particular when two hydrophilic residues are involved. In view of these results, we performed a study based on molecular dynamics simulation aimed to reproduce the experimental change in binding free energy, ΔΔG, of RPA70 mutants to further elucidate the nature of the protein-ssDNA interaction. The MM-PB(GB)SA methods implemented in Amber10 and the code FoldX were used to estimate the binding free energy. The theoretical and experimental ΔΔG values correlate better when the results are obtained by MM-PBSA calculated on individual trajectories for each mutant. In these conditions, the correlation coefficient between experimental and theoretical ΔΔG reaches a value of 0.95 despite the overestimation of the energy change by one order of magnitude. The decomposition of the MM-GBSA energy per residue allows us to correlate the change of the affinity with the residue polarity and energy contribution to the binding. The method revealed reliable predictions of the change in the affinity in function of mutations, and can be used to identify new mutants with distinct binding properties. PMID:22160652

  15. Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SRSF1

    Directory of Open Access Journals (Sweden)

    Wang Xin

    2011-12-01

    secondary structure play complementary roles during binding site recognition by SRSF1. Conclusion In this study, we presented a computational model to predict the sequence consensus and optimal RNA secondary structure for protein-RNA binding regions. The successful implementation on SRSF1 CLIP-seq data demonstrates great potential to improve our understanding on the binding specificity of RNA binding proteins.

  16. Computational prediction of cAMP receptor protein (CRP) binding sites in cyanobacterial genomes

    Science.gov (United States)

    Xu, Minli; Su, Zhengchang

    2009-01-01

    Background Cyclic AMP receptor protein (CRP), also known as catabolite gene activator protein (CAP), is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The loss of CRPs in these species

  17. Computational prediction of cAMP receptor protein (CRP binding sites in cyanobacterial genomes

    Directory of Open Access Journals (Sweden)

    Su Zhengchang

    2009-01-01

    Full Text Available Abstract Background Cyclic AMP receptor protein (CRP, also known as catabolite gene activator protein (CAP, is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The

  18. Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

    Science.gov (United States)

    Brylinski, Michal

    2013-11-25

    A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely

  19. Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

    Science.gov (United States)

    Brylinski, Michal

    2013-11-25

    A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely

  20. Cloud computing approaches for prediction of ligand binding poses and pathways.

    Science.gov (United States)

    Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

    2015-01-22

    We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.

  1. Genome-wide de novo prediction of cis-regulatory binding sites in prokaryotes

    OpenAIRE

    Zhang, Shaoqiang; Xu, Minli; Li, Shan; Su, Zhengchang

    2009-01-01

    Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We desi...

  2. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  3. PiRaNhA: a server for the computational prediction of RNA-binding residues in protein sequences

    OpenAIRE

    Murakami, Yoichi; Ruth V Spriggs; Nakamura, Haruki; Jones, Susan

    2010-01-01

    The PiRaNhA web server is a publicly available online resource that automatically predicts the location of RNA-binding residues (RBRs) in protein sequences. The goal of functional annotation of sequences in the field of RNA binding is to provide predictions of high accuracy that require only small numbers of targeted mutations for verification. The PiRaNhA server uses a support vector machine (SVM), with position-specific scoring matrices, residue interface propensity, predicted residue acces...

  4. Combining features in a graphical model to predict protein binding sites.

    Science.gov (United States)

    Wierschin, Torsten; Wang, Keyu; Welter, Marlon; Waack, Stephan; Stanke, Mario

    2015-05-01

    Large efforts have been made in classifying residues as binding sites in proteins using machine learning methods. The prediction task can be translated into the computational challenge of assigning each residue the label binding site or non-binding site. Observational data comes from various possibly highly correlated sources. It includes the structure of the protein but not the structure of the complex. The model class of conditional random fields (CRFs) has previously successfully been used for protein binding site prediction. Here, a new CRF-approach is presented that models the dependencies of residues using a general graphical structure defined as a neighborhood graph and thus our model makes fewer independence assumptions on the labels than sequential labeling approaches. A novel node feature "change in free energy" is introduced into the model, which is then denoted by ΔF-CRF. Parameters are trained with an online large-margin algorithm. Using the standard feature class relative accessible surface area alone, the general graph-structure CRF already achieves higher prediction accuracy than the linear chain CRF of Li et al. ΔF-CRF performs significantly better on a large range of false positive rates than the support-vector-machine-based program PresCont of Zellner et al. on a homodimer set containing 128 chains. ΔF-CRF has a broader scope than PresCont since it is not constrained to protein subgroups and requires no multiple sequence alignment. The improvement is attributed to the advantageous combination of the novel node feature with the standard feature and to the adopted parameter training method.

  5. Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest

    Directory of Open Access Journals (Sweden)

    Hongjian Li

    2015-06-01

    Full Text Available Docking scoring functions can be used to predict the strength of protein-ligand binding. It is widely believed that training a scoring function with low-quality data is detrimental for its predictive performance. Nevertheless, there is a surprising lack of systematic validation experiments in support of this hypothesis. In this study, we investigated to which extent training a scoring function with data containing low-quality structural and binding data is detrimental for predictive performance. We actually found that low-quality data is not only non-detrimental, but beneficial for the predictive performance of machine-learning scoring functions, though the improvement is less important than that coming from high-quality data. Furthermore, we observed that classical scoring functions are not able to effectively exploit data beyond an early threshold, regardless of its quality. This demonstrates that exploiting a larger data volume is more important for the performance of machine-learning scoring functions than restricting to a smaller set of higher data quality.

  6. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Carson M Andorf

    Full Text Available BACKGROUND: Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners. METHODOLOGY: Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques. CONCLUSIONS: Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions. AVAILABILITY: We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

  7. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

    Directory of Open Access Journals (Sweden)

    Schroeder Michael

    2006-09-01

    Full Text Available Abstract Background Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. Results We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. Conclusion The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.

  8. MetaMHCpan, A Meta Approach for Pan-Specific MHC Peptide Binding Prediction.

    Science.gov (United States)

    Xu, Yichang; Luo, Cheng; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-01-01

    Recent computational approaches in bioinformatics can achieve high performance, by which they can be a powerful support for performing real biological experiments, making biologists pay more attention to bioinformatics than before. In immunology, predicting peptides which can bind to MHC alleles is an important task, being tackled by many computational approaches. However, this situation causes a serious problem for immunologists to select the appropriate method to be used in bioinformatics. To overcome this problem, we develop an ensemble prediction-based Web server, which we call MetaMHCpan, consisting of two parts: MetaMHCIpan and MetaMHCIIpan, for predicting peptides which can bind MHC-I and MHC-II, respectively. MetaMHCIpan and MetaMHCIIpan use two (MHC2SKpan and LApan) and four (TEPITOPEpan, MHC2SKpan, LApan, and MHC2MIL) existing predictors, respectively. MetaMHCpan is available at http://datamining-iip.fudan.edu.cn/MetaMHCpan/index.php/pages/view/info . PMID:27076335

  9. Development of computational methods for the prediction of protein structure, protein binding, and mutational effects using free energy calculations.

    OpenAIRE

    Becker, Caroline

    2014-01-01

    A molecular understanding of protein-protein or protein-ligand binding is of crucial importance for the design of proteins or ligands with defined binding characteristics. The comprehensive analysis of biomolecular binding and the coupled rational in silico design of protein-ligand interfaces requires both, accurate and computationally fast methods for the prediction of free energies. Accurate free energy methods usually involve atomistic molecular dynamics simulations that are computationall...

  10. Novel predicted RNA-binding domains associated with the translation machinery.

    Science.gov (United States)

    Aravind, L; Koonin, E V

    1999-03-01

    Two previously undetected domains were identified in a variety of RNA-binding proteins, particularly RNA-modifying enzymes, using methods for sequence profile analysis. A small domain consisting of 60-65 amino acid residues was detected in the ribosomal protein S4, two families of pseudouridine synthases, a novel family of predicted RNA methylases, a yeast protein containing a pseudouridine synthetase and a deaminase domain, bacterial tyrosyl-tRNA synthetases, and a number of uncharacterized, small proteins that may be involved in translation regulation. Another novel domain, designated PUA domain, after PseudoUridine synthase and Archaeosine transglycosylase, was detected in archaeal and eukaryotic pseudouridine synthases, archaeal archaeosine synthases, a family of predicted ATPases that may be involved in RNA modification, a family of predicted archaeal and bacterial rRNA methylases. Additionally, the PUA domain was detected in a family of eukaryotic proteins that also contain a domain homologous to the translation initiation factor eIF1/SUI1; these proteins may comprise a novel type of translation factors. Unexpectedly, the PUA domain was detected also in bacterial and yeast glutamate kinases; this is compatible with the demonstrated role of these enzymes in the regulation of the expression of other genes. We propose that the S4 domain and the PUA domain bind RNA molecules with complex folded structures, adding to the growing collection of nucleic acid-binding domains associated with DNA and RNA modification enzymes. The evolution of the translation machinery components containing the S4, PUA, and SUI1 domains must have included several events of lateral gene transfer and gene loss as well as lineage-specific domain fusions.

  11. MULTIPRED2: A computational system for large-scale identification of peptides predicted to bind to HLA supertypes and alleles

    DEFF Research Database (Denmark)

    Zhang, Guang Lan; DeLuca, David S.; Keskin, Derin B.;

    2011-01-01

    MULTIPRED2 is a computational system for facile prediction of peptide binding to multiple alleles belonging to human leukocyte antigen (HLA) class I and class II DR molecules. It enables prediction of peptide binding to products of individual HLA alleles, combination of alleles, or HLA supertypes...... groups in North America. MULTIPRED2 is an important tool to complement wet-lab experimental methods for identification of T-cell epitopes. It is available at http://cvc.dfci.harvard.edu/multipred2/....

  12. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2007-01-01

    by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic...... benchmark data set, and SMM-align prediction method (NetMHCII) are made publicly available....

  13. Binding mode and free energy prediction of fisetin/β-cyclodextrin inclusion complexes

    Science.gov (United States)

    Nutho, Bodee; Khuntawee, Wasinee; Rungnim, Chompoonut; Pongsawasdi, Piamsook; Wolschann, Peter; Karpfen, Alfred; Kungwan, Nawee

    2014-01-01

    Summary In the present study, our aim is to investigate the preferential binding mode and encapsulation of the flavonoid fisetin in the nano-pore of β-cyclodextrin (β-CD) at the molecular level using various theoretical approaches: molecular docking, molecular dynamics (MD) simulations and binding free energy calculations. The molecular docking suggested four possible fisetin orientations in the cavity through its chromone or phenyl ring with two different geometries of fisetin due to the rotatable bond between the two rings. From the multiple MD results, the phenyl ring of fisetin favours its inclusion into the β-CD cavity, whilst less binding or even unbinding preference was observed in the complexes where the larger chromone ring is located in the cavity. All MM- and QM-PBSA/GBSA free energy predictions supported the more stable fisetin/β-CD complex of the bound phenyl ring. Van der Waals interaction is the key force in forming the complexes. In addition, the quantum mechanics calculations with M06-2X/6-31G(d,p) clearly showed that both solvation effect and BSSE correction cannot be neglected for the energy determination of the chosen system. PMID:25550745

  14. Binding mode and free energy prediction of fisetin/β-cyclodextrin inclusion complexes

    Directory of Open Access Journals (Sweden)

    Bodee Nutho

    2014-11-01

    Full Text Available In the present study, our aim is to investigate the preferential binding mode and encapsulation of the flavonoid fisetin in the nano-pore of β-cyclodextrin (β-CD at the molecular level using various theoretical approaches: molecular docking, molecular dynamics (MD simulations and binding free energy calculations. The molecular docking suggested four possible fisetin orientations in the cavity through its chromone or phenyl ring with two different geometries of fisetin due to the rotatable bond between the two rings. From the multiple MD results, the phenyl ring of fisetin favours its inclusion into the β-CD cavity, whilst less binding or even unbinding preference was observed in the complexes where the larger chromone ring is located in the cavity. All MM- and QM-PBSA/GBSA free energy predictions supported the more stable fisetin/β-CD complex of the bound phenyl ring. Van der Waals interaction is the key force in forming the complexes. In addition, the quantum mechanics calculations with M06-2X/6-31G(d,p clearly showed that both solvation effect and BSSE correction cannot be neglected for the energy determination of the chosen system.

  15. Comparison of Performance of Docking, LIE, Metadynamics and QSAR in Predicting Binding Affinity of Benzenesulfonamides.

    Science.gov (United States)

    Raškevičius, Vytautas; Kairys, Visvaldas

    2015-01-01

    The design of inhibitors specific for one relevant carbonic anhydrase isozyme is the major challenge in the new therapeutic agents development. Comparative computational chemical structure and biological activity relationship studies on a series of carbonic anhydrase II inhibitors, benzenesulfonamide derivatives, bearing pyrimidine moieties are reported in this paper using docking, Linear Interaction Energy (LIE), Metadynamics and Quantitative Structure Activity Relationship (QSAR) methods. The computed binding affinities were compared with the experimental data with the goal to explore strengths and weaknesses of various approaches applied to the investigated carbonic anhydrase/inhibitor system. From the tested methods initially only QSAR showed promising results (R2=0.83-0.89 between experimentally determined versus predicted pKd values.). Possible reasons for this performance were discussed. A modification of the LIE method was suggested which used an alternative LIE-like equation yielding significantly improved results (R2 between the experimentally determined versus the predicted ΔG(bind) improved from 0.24 to 0.50).

  16. Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.

    Science.gov (United States)

    Setny, Piotr

    2015-12-01

    Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method. PMID:26642995

  17. Advances and applications of binding affinity prediction methods in drug discovery.

    Science.gov (United States)

    Parenti, Marco Daniele; Rastelli, Giulio

    2012-01-01

    Nowadays, the improvement of R&D productivity is the primary commitment in pharmaceutical research, both in big pharma and smaller biotech companies. To reduce costs, to speed up the discovery process and to increase the chance of success, advanced methods of rational drug design are very helpful, as demonstrated by several successful applications. Among these, computational methods able to predict the binding affinity of small molecules to specific biological targets are of special interest because they can accelerate the discovery of new hit compounds. Here we provide an overview of the most widely used methods in the field of binding affinity prediction, as well as of our own work in developing BEAR, an innovative methodology specifically devised to overtake some limitations in existing approaches. The BEAR method was successfully validated against different biological targets, and proved its efficacy in retrieving active compounds from virtual screening campaigns. The results obtained so far indicate that BEAR may become a leading tool in the drug discovery pipeline. We primarily discuss advantages and drawbacks of each technique and show relevant examples and applications in drug discovery.

  18. Prediction and dissection of widely-varying association rate constants of actin-binding proteins.

    Directory of Open Access Journals (Sweden)

    Xiaodong Pang

    Full Text Available Actin is an abundant protein that constitutes a main component of the eukaryotic cytoskeleton. Its polymerization and depolymerization are regulated by a variety of actin-binding proteins. Their functions range from nucleation of actin polymerization to sequestering G-actin in 1∶1 complexes. The kinetics of forming these complexes, with rate constants varying at least three orders of magnitude, is critical to the distinct regulatory functions. Previously we have developed a transient-complex theory for computing protein association mechanisms and association rate constants. The transient complex refers to an intermediate in which the two associating proteins have near-native separation and relative orientation but have yet to form short-range specific interactions of the native complex. The association rate constant is predicted as k(a = k(a0 e(-ΔG(el*/k(BT, where k(a0 is the basal rate constant for reaching the transient complex by free diffusion, and the Boltzmann factor captures the bias of long-range electrostatic interactions. Here we applied the transient-complex theory to study the association kinetics of seven actin-binding proteins with G-actin. These proteins exhibit three classes of association mechanisms, due to their different molecular shapes and flexibility. The 1000-fold k(a variations among them can mostly be attributed to disparate electrostatic contributions. The basal rate constants also showed variations, resulting from the different shapes and sizes of the interfaces formed by the seven actin-binding proteins with G-actin. This study demonstrates the various ways that actin-binding proteins use physical properties to tune their association mechanisms and rate constants to suit distinct regulatory functions.

  19. Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment

    DEFF Research Database (Denmark)

    Carrasco Pro, S.; Zimic, M.; Nielsen, Morten

    2014-01-01

    Major histocompatibility complex (MHC) molecules play a key role in cell-mediated immune responses presenting bounded peptides for recognition by the immune system cells. Several in silico methods have been developed to predict the binding affinity of a given peptide to a specific MHC molecule. One...... of the current state-of-the-art methods for MHC class I is NetMHCpan, which has a core ingredient for the representation of the MHC class I molecule using a pseudo-sequence representation of the binding cleft amino acid environment. New and large MHC-peptide-binding data sets are constantly being made available......, and also new structures of MHC class I molecules with a bound peptide have been published. In order to test if the NetMHCpan method can be improved by integrating this novel information, we created new pseudo-sequence definitions for the MHC-binding cleft environment from sequence and structural analyses...

  20. Proteochemometric model for predicting the inhibition of penicillin-binding proteins.

    Science.gov (United States)

    Nabu, Sunanta; Nantasenamat, Chanin; Owasirikul, Wiwat; Lawung, Ratana; Isarankura-Na-Ayudhya, Chartchalerm; Lapins, Maris; Wikberg, Jarl E S; Prachayasittikul, Virapong

    2015-02-01

    Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing β-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic β-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability (R2=0.91, Q2=0.77, QExt2=0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future. PMID:25344841

  1. DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.

    Science.gov (United States)

    Motion, Graham B; Howden, Andrew J M; Huitema, Edgar; Jones, Susan

    2015-12-15

    There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this we develop a plant specific model for predicting DNA-binding proteins. We apply this model to the tomato proteome and demonstrate its ability to perform accurate high-throughput prediction of DNA-binding proteins. In doing so, we have annotated 36 currently uncharacterised proteins by assigning a putative DNA-binding function. Our model is publically available and we propose it be used in combination with existing tools to help increase annotation levels of DNA-binding proteins encoded in plant genomes. PMID:26304539

  2. Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach

    DEFF Research Database (Denmark)

    Buus, S; Lauemøller, S L; Worning, P;

    2003-01-01

    We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict...

  3. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    Directory of Open Access Journals (Sweden)

    Lund Ole

    2007-07-01

    Full Text Available Abstract Background Antigen presenting cells (APCs sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC and three mouse H2-IA alleles. Results The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR, we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. Conclusion

  4. sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides

    Science.gov (United States)

    Luo, Heng; Ye, Hao; Ng, Hui Wen; Sakkiah, Sugunadevi; Mendrick, Donna L.; Hong, Huixiao

    2016-01-01

    Understanding the binding between human leukocyte antigens (HLAs) and peptides is important to understand the functioning of the immune system. Since it is time-consuming and costly to measure the binding between large numbers of HLAs and peptides, computational methods including machine learning models and network approaches have been developed to predict HLA-peptide binding. However, there are several limitations for the existing methods. We developed a network-based algorithm called sNebula to address these limitations. We curated qualitative Class I HLA-peptide binding data and demonstrated the prediction performance of sNebula on this dataset using leave-one-out cross-validation and five-fold cross-validations. This algorithm can predict not only peptides of different lengths and different types of HLAs, but also the peptides or HLAs that have no existing binding data. We believe sNebula is an effective method to predict HLA-peptide binding and thus improve our understanding of the immune system. PMID:27558848

  5. Electrostatic component of binding energy: Interpreting predictions from poisson-boltzmann equation and modeling protocols.

    Science.gov (United States)

    Chakavorty, Arghya; Li, Lin; Alexov, Emil

    2016-10-30

    Macromolecular interactions are essential for understanding numerous biological processes and are typically characterized by the binding free energy. Important component of the binding free energy is the electrostatics, which is frequently modeled via the solutions of the Poisson-Boltzmann Equations (PBE). However, numerous works have shown that the electrostatic component (ΔΔGelec ) of binding free energy is very sensitive to the parameters used and modeling protocol. This prompted some researchers to question the robustness of PBE in predicting ΔΔGelec . We argue that the sensitivity of the absolute ΔΔGelec calculated with PBE using different input parameters and definitions does not indicate PBE deficiency, rather this is what should be expected. We show how the apparent sensitivity should be interpreted in terms of the underlying changes in several numerous and physical parameters. We demonstrate that PBE approach is robust within each considered force field (CHARMM-27, AMBER-94, and OPLS-AA) once the corresponding structures are energy minimized. This observation holds despite of using two different molecular surface definitions, pointing again that PBE delivers consistent results within particular force field. The fact that PBE delivered ΔΔGelec values may differ if calculated with different modeling protocols is not a deficiency of PBE, but natural results of the differences of the force field parameters and potential functions for energy minimization. In addition, while the absolute ΔΔGelec values calculated with different force field differ, their ordering remains practically the same allowing for consistent ranking despite of the force field used. © 2016 Wiley Periodicals, Inc.

  6. Prediction of SAMPL3 Host-Guest Binding Affinities: Evaluating the Accuracy of Generalized Force-Fields

    OpenAIRE

    Muddana, Hari S.; Gilson, Michael K.

    2012-01-01

    We used the second-generation mining minima method (M2) to compute the binding affinities of the novel host-guest complexes in the SAMPL3 blind prediction challenge. The predictions were in poor agreement with experiment, and we conjectured that much of the error might derive from the force field, CHARMm with Vcharge charges. Repeating the calculations with other generalized force-fields led to no significant improvement, and we observed that the predicted affinities were highly sensitive to ...

  7. Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

    Science.gov (United States)

    Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

    2012-07-01

    Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

  8. Prediction on the binding domain between human interleukin-6 and its receptor

    Institute of Scientific and Technical Information of China (English)

    冯健男; 任蕴芳; 沈倍奋

    2000-01-01

    Based on the spatial conformations of human interleukin-6 (hlL-6) derived from nuclear magnetic resonance analysis and human interleukin-6 receptor (hlL-6R) modeled with homology modeling method using human growth hormone receptor as template, the interaction between hlL-6 and its receptor (hIL-6R) is studied with docking program according to the surface electrostatic potential analysis and spatial conformation complement. The stable region structure composed of hlL-6 and hlL-6R is obtained on the basis of molecular mechanism optimization and molecular dynamics simulation. The binding domain between hIL-6 and hIL-6R is predicted theoretically. Furthermore, the especial binding sites that influence the interaction between hlL-6 and hlL-6R are confirmed. The results lay a theoretical foundation for confirming the active regions of hlL-6 and designing novel antagonist with computer-guided techniques.

  9. Prediction on the binding domain between human interleukin-6 and its receptor

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Based on the spatial conformations of human interleukin-6 (hIL-6) derived from nuclear magnetic resonance analysis and human interleukin-6 receptor (hIL-6R) modeled with homology modeling method using human growth hormone receptor as template, the interaction between hIL-6 and its receptor (hIL-6R) is studied with docking program according to the surface electrostatic potential analysis and spatial conformation complement. The stable region structure composed of hIL-6 and hIL-6R is obtained on the basis of molecular mechanism optimization and molecular dynamics simulation. The binding domain between hIL-6 and hIL-6R is predicted theoretically. Furthermore, the especial binding sites that influence the interaction between hIL-6 and hIL-6R are confirmed. The results lay a theoretical foundation for confirming the active regions of hIL-6 and designing novel antagonist with computer-guided techniques.

  10. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael;

    2015-01-01

    A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized ...

  11. Love to win or hate to lose? Asymmetry of dopamine D2 receptor binding predicts sensitivity to reward vs. punishment

    Science.gov (United States)

    Tomer, Rachel; Slagter, Heleen A; Christian, Bradley T; Fox, Andrew S; King, Carlye R; Murali, Dhanabalan; Gluck, Mark A; Davidson, Richard J

    2014-01-01

    Humans show consistent differences in the extent to which their behavior reflects a bias towards appetitive approach-related behavior or avoidance of aversive stimuli (Elliot, 2008). We examined the hypothesis that in healthy subjects this motivational bias (assessed by self-report and by a probabilistic learning task that allows direct comparison of the relative sensitivity to reward and punishment) reflects lateralization of dopamine signaling. Using [F-18]fallypride to measure D2/D3 binding , we found that self-reported motivational bias was predicted by the asymmetry of frontal D2 binding. Similarly, striatal and frontal asymmetries in D2 dopamine receptor binding, rather than absolute binding levels, predicted individual differences in learning from reward vs. punishment. These results suggest that normal variation in asymmetry of dopamine signaling may, in part, underlie human personality and cognition. PMID:24345165

  12. Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Blicher, Thomas;

    2008-01-01

    is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent......-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while...... class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method...

  13. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

    Science.gov (United States)

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  14. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events.

    Science.gov (United States)

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The [Formula: see text] class contains tandem [Formula: see text]-type motif sequences, and the [Formula: see text] class contains alternating [Formula: see text], [Formula: see text] and [Formula: see text] type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a [Formula: see text]-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the [Formula: see text] class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for [Formula: see text]-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  15. Model-based Comparative Prediction of Transcription-Factor Binding Motifs in Anabolic Responses in Bone

    Institute of Scientific and Technical Information of China (English)

    Andy; B.; Chen; Kazunori; Hamamura; Guohua; Wang; Weirong; Xing; Subburaman; Mohan; Hiroki; Yokota; Yunlong; Liu

    2007-01-01

    Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both "anabolic responses of mechanical loading" and "BMP-mediated osteogenic signaling"? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated recep- tor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells sup- ported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.

  16. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals

    Science.gov (United States)

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-01-01

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold2 software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed. PMID:27023588

  17. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals

    Directory of Open Access Journals (Sweden)

    Huixiao Hong

    2016-03-01

    Full Text Available Endocrine disruptors such as polychlorinated biphenyls (PCBs, diethylstilbestrol (DES and dichlorodiphenyltrichloroethane (DDT are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest and the molecular descriptors calculated from two-dimensional structures by Mold2 software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69% and external validations using 22 chemicals (balanced accuracy of 71%. Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  18. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

    Science.gov (United States)

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-04-01

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed. PMID:27023588

  19. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

    Directory of Open Access Journals (Sweden)

    Panwar Bharat

    2013-02-01

    Full Text Available Abstract Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL. It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i vitamin interacting residues (VIRs, (ii vitamin-A interacting residues (VAIRs, (iii vitamin-B interacting residues (VBIRs and (iv pyridoxal-5-phosphate (vitamin B6 interacting residues (PLPIRs have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM features of protein sequences. Finally, we selected best performing SVM modules and

  20. Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

    Institute of Scientific and Technical Information of China (English)

    Sun Zhong-Hua; Jiang Fan

    2010-01-01

    In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method.

  1. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  2. Protein function annotation by local binding site surface similarity.

    Science.gov (United States)

    Spitzer, Russell; Cleves, Ann E; Varela, Rocco; Jain, Ajay N

    2014-04-01

    Hundreds of protein crystal structures exist for proteins whose function cannot be confidently determined from sequence similarity. Surflex-PSIM, a previously reported surface-based protein similarity algorithm, provides an alternative method for hypothesizing function for such proteins. The method now supports fully automatic binding site detection and is fast enough to screen comprehensive databases of protein binding sites. The binding site detection methodology was validated on apo/holo cognate protein pairs, correctly identifying 91% of ligand binding sites in holo structures and 88% in apo structures where corresponding sites existed. For correctly detected apo binding sites, the cognate holo site was the most similar binding site 87% of the time. PSIM was used to screen a set of proteins that had poorly characterized functions at the time of crystallization, but were later biochemically annotated. Using a fully automated protocol, this set of 8 proteins was screened against ∼60,000 ligand binding sites from the PDB. PSIM correctly identified functional matches that predated query protein biochemical annotation for five out of the eight query proteins. A panel of 12 currently unannotated proteins was also screened, resulting in a large number of statistically significant binding site matches, some of which suggest likely functions for the poorly characterized proteins.

  3. Computational analysis and prediction of the binding motif and protein interacting partners of the Abl SH3 domain.

    Directory of Open Access Journals (Sweden)

    Tingjun Hou

    2006-01-01

    Full Text Available Protein-protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains, such as Src Homology 2 and 3 (SH2 and SH3 domains, which bind to specific sequence and structural motifs. It is important but challenging to determine the binding specificity of these domains accurately and to predict their physiological interacting partners. In this study, the interactions between 35 peptide ligands (15 binders and 20 non-binders and the Abl SH3 domain were analyzed using molecular dynamics simulation and the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. The calculated binding free energies correlated well with the rank order of the binding peptides and clearly distinguished binders from non-binders. Free energy component analysis revealed that the van der Waals interactions dictate the binding strength of peptides, whereas the binding specificity is determined by the electrostatic interaction and the polar contribution of desolvation. The binding motif of the Abl SH3 domain was then determined by a virtual mutagenesis method, which mutates the residue at each position of the template peptide relative to all other 19 amino acids and calculates the binding free energy difference between the template and the mutated peptides using the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. A single position mutation free energy profile was thus established and used as a scoring matrix to search peptides recognized by the Abl SH3 domain in the human genome. Our approach successfully picked ten out of 13 experimentally determined binding partners of the Abl SH3 domain among the top 600 candidates from the 218,540 decapeptides with the PXXP motif in the SWISS-PROT database. We expect that this physical-principle based method can be applied to other protein domains as well.

  4. Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

    Directory of Open Access Journals (Sweden)

    Marharyta Petukh

    2015-07-01

    Full Text Available A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624 while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation.

  5. PiRaNhA: a server for the computational prediction of RNA-binding residues in protein sequences

    Science.gov (United States)

    Murakami, Yoichi; Spriggs, Ruth V.; Nakamura, Haruki; Jones, Susan

    2010-01-01

    The PiRaNhA web server is a publicly available online resource that automatically predicts the location of RNA-binding residues (RBRs) in protein sequences. The goal of functional annotation of sequences in the field of RNA binding is to provide predictions of high accuracy that require only small numbers of targeted mutations for verification. The PiRaNhA server uses a support vector machine (SVM), with position-specific scoring matrices, residue interface propensity, predicted residue accessibility and residue hydrophobicity as features. The server allows the submission of up to 10 protein sequences, and the predictions for each sequence are provided on a web page and via email. The prediction results are provided in sequence format with predicted RBRs highlighted, in text format with the SVM threshold score indicated and as a graph which enables users to quickly identify those residues above any specific SVM threshold. The graph effectively enables the increase or decrease of the false positive rate. When tested on a non-redundant data set of 42 protein sequences not used in training, the PiRaNhA server achieved an accuracy of 85%, specificity of 90% and a Matthews correlation coefficient of 0.41 and outperformed other publicly available servers. The PiRaNhA prediction server is freely available at http://www.bioinformatics.sussex.ac.uk/PIRANHA. PMID:20507911

  6. In silico engineering and optimization of Transcription Activator-Like Effectors and their derivatives for improved DNA binding predictions.

    KAUST Repository

    Piatek, Marek J.

    2015-12-01

    Transcription Activator-Like Effectors (TALEs) can be used as adaptable DNAbinding modules to create site-specific chimeric nucleases or synthetic transcriptional regulators. The central repeat domain mediates specific DNA binding via hypervariable repeat di-residues (RVDs). This DNA-Binding Domain can be engineered to bind preferentially to any user-selected DNA sequence if engineered appropriately. Therefore, TALEs and their derivatives have become indispensable molecular tools in site-specific manipulation of genes and genomes. This thesis revolves around two problems: in silico design and improved binding site prediction of TALEs. In the first part, a study is shown where TALEs are successfully designed in silico and validated in laboratory to yield the anticipated effects on selected genes. Software is developed to accompany the process of designing and prediction of binding sites. I expanded the functionality of the software to be used as a more generic set of tools for the design, target and offtarget searching. Part two contributes a method and associated toolkit developed to allow users to design in silico optimized synthetic TALEs with user-defined specificities for various experimental purposes. This method is based on a mutual relationship of three consecutive tandem repeats in the DNA-binding domain. This approach revealed positional and compositional bias behind the binding of TALEs to DNA. In conclusion, I developed methods, approaches, and software to enhance the functionality of synthetic TALEs, which should improve understanding of TALEs biology and will further advance genome-engineering applications in various organisms and cell types.

  7. Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations

    DEFF Research Database (Denmark)

    Poongavanam, Vasanthanathan; Olsen, Lars; Jørgensen, Flemming Steen;

    2010-01-01

    , and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both...... substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent...

  8. MHC class I epitope binding prediction trained on small data sets

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Nielsen, Morten; Lamberth, K.;

    2004-01-01

    The identification of potential T-cell epitopes is important for development of new human or vetenary vaccines, both considering single protein/subunit vaccines, and for epitope/peptide vaccines as such. The highly diverse MHC class I alleles bind very different peptides, and accurate binding pre...... in situations where only very limited data are available for training....

  9. An integrative approach to CTL epitope prediction: A combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

    DEFF Research Database (Denmark)

    Larsen, Mette Voldby; Lundegaard, Claus; Lamberth, K;

    2005-01-01

    Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have al.......The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php....

  10. PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

    Directory of Open Access Journals (Sweden)

    Adeel Malik

    2010-01-01

    Full Text Available Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins as well as noncovalently (protein-carbohydrate complexes is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB, (ii Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

  11. Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles.

    Science.gov (United States)

    Brender, Jeffrey R; Zhang, Yang

    2015-10-01

    The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies.

  12. Flanking p10 contribution and sequence bias in matrix based epitope prediction: revisiting the assumption of independent binding pockets

    Directory of Open Access Journals (Sweden)

    Parry Christian S

    2008-10-01

    Full Text Available Abstract Background Eluted natural peptides from major histocompatibility molecules show patterns of conserved residues. Crystallographic structures show that the bound peptide in class II major histocompatibility complex adopts a near uniform polyproline II-like conformation. This way allele-specific favoured residues are able to anchor into pockets in the binding groove leaving other peptide side chains exposed for recognition by T cells. The anchor residues form a motif. This sequence pattern can be used to screen large sequences for potential epitopes. Quantitative matrices extend the motif idea to include the contribution of non-anchor peptide residues. This report examines two new matrices that extend the binding register to incorporate the polymorphic p10 pocket of human leukocyte antigen DR1. Their performance is quantified against experimental binding measurements and against the canonical nine-residue register matrix. Results One new matrix shows significant improvement over the base matrix; the other does not. The new matrices differ in the sequence of the peptide library. Conclusion One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix. Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions. Such interactions may influence epitope prediction in this test of quantitative matrices. This calls into question the assumption of the independent contribution of individual binding pockets.

  13. Prediction of Peptide Binding to Major Histocompatibility II Receptors with Molecular Mechanics and Semi-Empirical Quantum Mechanics Methods

    Directory of Open Access Journals (Sweden)

    James A Platts

    2012-02-01

    Full Text Available Methods for prediction of the binding of peptides to major histocompatibility complex (MHC II receptors are examined, using literature values of IC50 as a benchmark. Two sets of IC50 data for closely structurally related peptides based on hen egg lysozyme (HEL and myelin basic protein (MBP are reported first. This shows that methods based on both molecular mechanics and semi-empirical quantum mechanics can predict binding with good-to-reasonable accuracy, as long as a suitable method for estimation of solvation effects is included. A more diverse set of 22 peptides bound to HLA-DR1 provides a tougher test of such methods, especially since no crystal structure is available for these peptide-MHC complexes. We therefore use sequence based methods such as SYFPEITHI and SVMHC to generate possible binding poses, using a consensus approach to determine the most likely anchor residues, which are then mapped onto the crystal structure of an unrelated peptide bound to the same receptor. This analysis shows that the MM/GBVI method performs particularly well, as does the AMBER94 forcefield with Born solvation model. Indeed, MM/GBVI can be used as an alternative to sequence based methods in generating binding poses, leading to still better accuracy.

  14. Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method

    OpenAIRE

    Marharyta Petukh; Minghui Li; Emil Alexov

    2015-01-01

    Author Summary Developing methods for accurate prediction of effects of amino acid substitutions on protein-protein affinity is important for both understanding disease-causing mechanism of missense mutations and guiding protein engineering. For both purposes, there is a need for accurate methods primarily based on first principle calculations, while being fast enough to handle large number of cases. Here we report a new method, the Single Amino Acid Mutation based change in Binding free Ener...

  15. THUMP--a predicted RNA-binding domain shared by 4-thiouridine, pseudouridine synthases and RNA methylases.

    Science.gov (United States)

    Aravind, L; Koonin, E V

    2001-04-01

    Sequence profile searches were used to identify an ancient domain in ThiI-like thiouridine synthases, conserved RNA methylases, archaeal pseudouridine synthases and several uncharacterized proteins. We predict that this domain is an RNA-binding domain that adopts an alpha/beta fold similar to that found in the C-terminal domain of translation initiation factor 3 and ribosomal protein S8.

  16. Predicting the Impact of Missense Mutations on Protein–Protein Binding Affinity

    OpenAIRE

    Li, Minghui; Petukh, Marharyta; Alexov, Emil; Panchenko, Anna R

    2014-01-01

    The crucial prerequisite for proper biological function is the protein’s ability to establish highly selective interactions with macromolecular partners. A missense mutation that alters the protein binding affinity may cause significant perturbations or complete abolishment of the function, potentially leading to diseases. The availability of computational methods to evaluate the impact of mutations on protein–protein binding is critical for a wide range of biomedical applications. Here, we r...

  17. The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement.

    Science.gov (United States)

    Brylinski, Michal; Lee, Seung Yup; Zhou, Hongyi; Skolnick, Jeffrey

    2011-03-01

    Exhaustive exploration of molecular interactions at the level of complete proteomes requires efficient and reliable computational approaches to protein function inference. Ligand docking and ranking techniques show considerable promise in their ability to quantify the interactions between proteins and small molecules. Despite the advances in the development of docking approaches and scoring functions, the genome-wide application of many ligand docking/screening algorithms is limited by the quality of the binding sites in theoretical receptor models constructed by protein structure prediction. In this study, we describe a new template-based method for the local refinement of ligand-binding regions in protein models using remotely related templates identified by threading. We designed a Support Vector Regression (SVR) model that selects correct binding site geometries in a large ensemble of multiple receptor conformations. The SVR model employs several scoring functions that impose geometrical restraints on the Cα positions, account for the specific chemical environment within a binding site and optimize the interactions with putative ligands. The SVR score is well correlated with the RMSD from the native structure; in 47% (70%) of the cases, the Pearson's correlation coefficient is >0.5 (>0.3). When applied to weakly homologous models, the average heavy atom, local RMSD from the native structure of the top-ranked (best of top five) binding site geometries is 3.1Å (2.9Å) for roughly half of the targets; this represents a 0.1 (0.3)Å average improvement over the original predicted structure. Focusing on the subset of strongly conserved residues, the average heavy atom RMSD is 2.6Å (2.3Å). Furthermore, we estimate the upper bound of template-based binding site refinement using only weakly related proteins to be ∼2.6Å RMSD. This value also corresponds to the plasticity of the ligand-binding regions in distant homologues. The Binding Site Refinement (BSR

  18. BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

    Science.gov (United States)

    Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

    2016-10-01

    Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc.

  19. Computational Characterization and Prediction of Estrogen Receptor Coactivator Binding Site Inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Bennion, B J; Kulp, K S; Cosman, M; Lightstone, F C

    2005-08-26

    Many carcinogens have been shown to cause tissue specific tumors in animal models. The mechanism for this specificity has not been fully elucidated and is usually attributed to differences in organ metabolism. For heterocyclic amines, potent carcinogens that are formed in well-done meat, the ability to either bind to the estrogen receptor and activate or inhibit an estrogenic response will have a major impact on carcinogenicity. Here we describe our work with the human estrogen receptor alpha (hERa) and the mutagenic/carcinogenic heterocyclic amines PhIP, MeIQx, IFP, and the hydroxylated metabolite of PhIP, N2-hydroxy-PhIP. We found that PhIP, in contrast to the other heterocyclic amines, increased cell-proliferation in MCF-7 human breast cancer cells and activated the hERa receptor. We show mechanistic data supporting this activation both computationally by homology modeling and docking, and by NMR confirmation that PhIP binds with the ligand binding domain (LBD). This binding competes with estradiol (E2) in the native E2 binding cavity of the receptor. We also find that other heterocyclic amines and N2-hydroxy-PhIP inhibit ER activation presumably by binding into another cavity on the LBD. Moreover, molecular dynamics simulations of inhibitory heterocyclic amines reveal a disruption of the surface of the receptor protein involved with protein-protein signaling. We therefore propose that the mechanism for the tissue specific carcinogenicity seen in the rat breast tumors and the presumptive human breast cancer associated with the consumption of well-done meat maybe mediated by this receptor activation.

  20. Combined molecular dynamics and continuum solvent approaches (MM-PBSA/GBSA) to predict noscapinoid binding to γ-tubulin dimer.

    Science.gov (United States)

    Suri, C; Naik, P K

    2015-06-01

    γ-tubulin plays crucial role in the nucleation and organization of microtubules during cell division. Recent studies have also indicated its role in the regulation of microtubule dynamics at the plus end of the microtubules. Moreover, γ-tubulin has been found to be over-expressed in many cancer types, such as carcinomas of the breast and glioblastoma multiforme. These studies have led to immense interest in the identification of chemical leads that might interact with γ-tubulin and disrupt its function in order to explore γ-tubulin as potential chemotherapeutic target. Recently a colchicine-interacting cavity was identified at the interface of γ-tubulin dimer that might also interact with other similar compounds. In the same direction we theoretically investigated binding of a class of compounds, noscapinoids (noscapine and its derivatives) at the interface of the γ-tubulin dimer. Molecular interaction of noscapine and two of its derivatives, amino-noscapine and bromo-noscapine, was investigated by molecular docking, molecular dynamics simulation and binding free energy calculation. All noscapinoids displayed stable interaction throughout simulation of 25 ns. The predictive binding free energy (ΔGbind) indicates that noscapinoids bind strongly with the γ-tubulin dimer. However, bromo-noscapine showed the best binding affinity (ΔGbind = -37.6 kcal/mol) followed by noscapine (ΔGbind = -29.85 kcal/mol) and amino-noscapine (ΔGbind = -23.99 kcal/mol) using the MM-PBSA method. Similarly using the MM-GBSA method, bromo-noscapine showed highest binding affinity (ΔGbind = -43.64 kcal/mol) followed by amino-noscapine (ΔGbind = -37.56 kcal/mol) and noscapine (ΔGbind = -34.57 kcal/mol). The results thus generate compelling evidence that these noscapinoids may hold great potential for preclinical and clinical evaluation. PMID:26274780

  1. Positron emission tomography displacement sensitivity: predicting binding potential change for positron emission tomography tracers based on their kinetic characteristics.

    Science.gov (United States)

    Morris, Evan D; Yoder, Karmen K

    2007-03-01

    There is great interest in positron emission tomography (PET) as a noninvasive assay of fluctuations in synaptic neurotransmitter levels, but questions remain regarding the optimal choice of tracer for such a task. A mathematical method is proposed for predicting the utility of any PET tracer as a detector of changes in the concentration of an endogenous competitor via displacement of the tracer (a.k.a., its 'vulnerability' to competition). The method is based on earlier theoretical work by Endres and Carson and by the authors. A tracer-specific predictor, the PET Displacement Sensitivity (PDS), is calculated from compartmental model simulations of the uptake and retention of dopaminergic radiotracers in the presence of transient elevations of dopamine (DA). The PDS predicts the change in binding potential (DeltaBP) for a given change in receptor occupancy because of binding by the endogenous competitor. Simulations were performed using estimates of tracer kinetic parameters derived from the literature. For D(2)/D(3) tracers, the calculated PDS indices suggest a rank order for sensitivity to displacement by DA as follows: raclopride (highest sensitivity), followed by fallypride, FESP, FLB, NMSP, and epidepride (lowest). Although the PDS takes into account the affinity constant for the tracer at the binding site, its predictive value cannot be matched by either a single equilibrium constant, or by any one rate constant of the model. Values for DeltaBP have been derived from published studies that employed comparable displacement paradigms with amphetamine and a D(2)/D(3) tracer. The values are in good agreement with the PDS-predicted rank order of sensitivity to displacement. PMID:16788713

  2. Sex hormone-binding globulin levels predict insulin sensitivity, disposition index, and cardiovascular risk during puberty

    DEFF Research Database (Denmark)

    Sørensen, Kaspar; Aksglaede, Lise; Munch-Andersen, Thor;

    2009-01-01

    Early puberty is associated with increased risk of subsequent cardiovascular disease. Low sex hormone-binding globulin (SHBG) levels are a feature of early puberty and of conditions associated with increased cardiovascular risk. The aim of the present study was to evaluate SHBG as a predictor of ...

  3. Interplay between magnetism and energetics in Fe-Cr alloys from a predictive noncollinear magnetic tight-binding model

    Science.gov (United States)

    Soulairol, R.; Barreteau, C.; Fu, Chu-Chun

    2016-07-01

    Magnetism is a key driving force controlling several thermodynamic and kinetic properties of Fe-Cr systems. We present a tight-binding model for Fe-Cr, where magnetism is treated beyond the usual collinear approximation. A major advantage of this model consists in a rather simple fitting procedure. In particular, no specific property of the binary system is explicitly required in the fitting database. The present model is proved to be accurate and highly transferable for electronic, magnetic, and energetic properties of a large variety of structural and chemical environments: surfaces, interfaces, embedded clusters, and the whole compositional range of the binary alloy. The occurrence of noncollinear magnetic configurations caused by magnetic frustrations is successfully predicted. The present tight-binding approach can apply to other binary magnetic transition-metal alloys. It is expected to be particularly promising if the size difference between the alloying elements is rather small and the electronic properties prevail.

  4. Interplay between magnetism and energetics in Fe-Cr alloys from a predictive noncollinear magnetic tight-binding model

    DEFF Research Database (Denmark)

    Soulairol, R.; Barreteau, Cyrille; Fu, Chu-Chun

    2016-01-01

    Magnetism is a key driving force controlling several thermodynamic and kinetic properties of Fe-Cr systems. We present a tight-binding model for Fe-Cr, where magnetism is treated beyond the usual collinear approximation. A major advantage of this model consists in a rather simple fitting procedure....... In particular, no specific property of the binary system is explicitly required in the fitting database. The present model is proved to be accurate and highly transferable for electronic, magnetic, and energetic properties of a large variety of structural and chemical environments: surfaces, interfaces......, embedded clusters, and the whole compositional range of the binary alloy. The occurrence of noncollinear magnetic configurations caused by magnetic frustrations is successfully predicted. The present tight-binding approach can apply to other binary magnetic transition-metal alloys. It is expected...

  5. Urinary liver-type fatty acid-binding protein predicts adverse outcomes in acute kidney injury

    OpenAIRE

    Ferguson, Michael A.; Vaidya, Vishal S.; Waikar, Sushrut S.; Collings, Fitz B.; Sunderland, Kelsey E.; Gioules, Costas J.; Bonventre, Joseph V.

    2009-01-01

    Acute kidney injury (AKI) is a common condition with significant associated morbidity and mortality. The insensitivity and non-specificity of traditional markers of renal dysfunction prevent timely diagnosis, estimation of the severity of renal injury, and the administration of possible therapeutic agents. Here, we determine the prognostic ability of urinary liver-type fatty acid-binding protein (L-FABP), and further characterize its sensitivity and specificity as a biomarker of AKI. Initial ...

  6. Seasonal difference in brain serotonin transporter binding predicts symptom severity in patients with seasonal affective disorder.

    Science.gov (United States)

    Mc Mahon, Brenda; Andersen, Sofie B; Madsen, Martin K; Hjordt, Liv V; Hageman, Ida; Dam, Henrik; Svarer, Claus; da Cunha-Bang, Sofi; Baaré, William; Madsen, Jacob; Hasholt, Lis; Holst, Klaus; Frokjaer, Vibe G; Knudsen, Gitte M

    2016-05-01

    Cross-sectional neuroimaging studies in non-depressed individuals have demonstrated an inverse relationship between daylight minutes and cerebral serotonin transporter; this relationship is modified by serotonin-transporter-linked polymorphic region short allele carrier status. We here present data from the first longitudinal investigation of seasonal serotonin transporter fluctuations in both patients with seasonal affective disorder and in healthy individuals. Eighty (11)C-DASB positron emission tomography scans were conducted to quantify cerebral serotonin transporter binding; 23 healthy controls with low seasonality scores and 17 patients diagnosed with seasonal affective disorder were scanned in both summer and winter to investigate differences in cerebral serotonin transporter binding across groups and across seasons. The two groups had similar cerebral serotonin transporter binding in the summer but in their symptomatic phase during winter, patients with seasonal affective disorder had higher serotonin transporter than the healthy control subjects (P = 0.01). Compared to the healthy controls, patients with seasonal affective disorder changed their serotonin transporter significantly less between summer and winter (P sex- (P = 0.02) and genotype- (P = 0.04) dependent. In the patients with seasonal affective disorder, the seasonal change in serotonin transporter binding was positively associated with change in depressive symptom severity, as indexed by Hamilton Rating Scale for Depression - Seasonal Affective Disorder version scores (P = 0.01). Our findings suggest that the development of depressive symptoms in winter is associated with a failure to downregulate serotonin transporter levels appropriately during exposure to the environmental stress of winter, especially in individuals with high predisposition to affective disorders.media-1vid110.1093/brain/aww043_video_abstractaww043_video_abstract. PMID:26994750

  7. Seasonal difference in brain serotonin transporter binding predicts symptom severity in patients with seasonal affective disorder

    DEFF Research Database (Denmark)

    Mc Mahon, Brenda; Andersen, Sofie B; Madsen, Martin K.;

    2016-01-01

    between summer and winter (P sex- (P = 0.02) and genotype- (P = 0.04) dependent. In the patients with seasonal affective disorder, the seasonal change in serotonin transporter binding was positively associated with change in depressive symptom...... to the environmental stress of winter, especially in individuals with high predisposition to affective disorders.media-1vid110.1093/brain/aww043_video_abstractaww043_video_abstract....

  8. Development of classification model and QSAR model for predicting binding affinity of endocrine disrupting chemicals to human sex hormone-binding globulin.

    Science.gov (United States)

    Liu, Huihui; Yang, Xianhai; Lu, Rui

    2016-08-01

    Disturbing the transport process is a crucial pathway for endocrine disrupting chemicals (EDCs) to disrupt endocrine function. However, this mechanism has not gotten enough attention, compared with that of hormone receptors and synthetase up to now, especially for the sex hormone transport process. In this study, we selected sex hormone-binding globulin (SHBG) and EDCs as a model system and the relative competing potency of a chemical with testosterone binding to SHBG (log RBA) as the endpoints, to develop classification models and quantitative structure-activity relationship (QSAR) models. With the classification model, a satisfactory model with nR09, nR10 and RDF155v as the most relevant variables was screened. Statistic results indicated that the model had the sensitivity, specificity, accuracy of 86.4%, 80.0%, 84.4% and 85.7%, 87.5%, 86.2% for the training set and validation set, respectively, highlighting a high classification performance of the model. With the QSAR model, a satisfactory model with statistical parameters, specifically, an adjusted determination coefficient (Radj(2)) of 0.810, a root mean square error (RMSE) of 0.616, a leave-one-out cross-validation squared correlation coefficient (QLOO(2)) of 0.777, a bootstrap method (QBOOT(2)) of 0.756, an external validation coefficient (Qext(2)) of 0.544 and a RMSEext of 0.859, were obtained, which implied satisfactory goodness of fit, robustness and predictive ability. The applicability domain of the current model covers a large number of structurally diverse chemicals, especially a few classes of nonsteroidal compounds. PMID:27156209

  9. Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface.

    Science.gov (United States)

    Metz, Alexander; Pfleger, Christopher; Kopitz, Hannes; Pfeiffer-Marek, Stefania; Baringhaus, Karl-Heinz; Gohlke, Holger

    2012-01-23

    Protein-protein interfaces are considered difficult targets for small-molecule protein-protein interaction modulators (PPIMs ). Here, we present for the first time a computational strategy that simultaneously considers aspects of energetics and plasticity in the context of PPIM binding to a protein interface. The strategy aims at identifying the determinants of small-molecule binding, hot spots, and transient pockets, in a protein-protein interface in order to make use of this knowledge for predicting binding modes of and ranking PPIMs with respect to their affinity. When applied to interleukin-2 (IL-2), the computationally inexpensive constrained geometric simulation method FRODA outperforms molecular dynamics simulations in sampling hydrophobic transient pockets. We introduce the PPIAnalyzer approach for identifying transient pockets on the basis of geometrical criteria only. A sequence of docking to identified transient pockets, starting structure selection based on hot spot information, RMSD clustering and intermolecular docking energies, and MM-PBSA calculations allows one to enrich IL-2 PPIMs from a set of decoys and to discriminate between subgroups of IL-2 PPIMs with low and high affinity. Our strategy will be applicable in a prospective manner where nothing else than a protein-protein complex structure is known; hence, it can well be the first step in a structure-based endeavor to identify PPIMs. PMID:22087639

  10. Prediction of striatal D2 receptor binding by DRD2/ANKK1 TaqIA allele status.

    Science.gov (United States)

    Eisenstein, Sarah A; Bogdan, Ryan; Love-Gregory, Latisha; Corral-Frías, Nadia S; Koller, Jonathan M; Black, Kevin J; Moerlein, Stephen M; Perlmutter, Joel S; Barch, Deanna M; Hershey, Tamara

    2016-10-01

    In humans, the A1 (T) allele of the dopamine (DA) D2 receptor/ankyrin repeat and kinase domain containing 1 (DRD2/ANKK1) TaqIA (rs1800497) single nucleotide polymorphism has been associated with reduced striatal DA D2/D3 receptor (D2/D3R) availability. However, radioligands used to estimate D2/D3R are displaceable by endogenous DA and are nonselective for D2R, leaving the relationship between TaqIA genotype and D2R specific binding uncertain. Using the positron emission tomography (PET) radioligand, (N-[(11) C]methyl)benperidol ([(11) C]NMB), which is highly selective for D2R over D3R and is not displaceable by endogenous DA, the current study examined whether DRD2/ANKK1 TaqIA genotype predicts D2R specific binding in two independent samples. Sample 1 (n = 39) was composed of obese and nonobese adults; sample 2 (n = 18) was composed of healthy controls, unmedicated individuals with schizophrenia, and siblings of individuals with schizophrenia. Across both samples, A1 allele carriers (A1+) had 5 to 12% less striatal D2R specific binding relative to individuals homozygous for the A2 allele (A1-), regardless of body mass index or diagnostic group. This reduction is comparable to previous PET studies of D2/D3R availability (10-14%). The pooled effect size for the difference in total striatal D2R binding between A1+ and A1- was large (0.84). In summary, in line with studies using displaceable D2/D3R radioligands, our results indicate that DRD2/ANKK1 TaqIA allele status predicts striatal D2R specific binding as measured by D2R-selective [(11) C]NMB. These findings support the hypothesis that DRD2/ANKK1 TaqIA allele status may modify D2R, perhaps conferring risk for certain disease states. PMID:27241797

  11. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

    International Nuclear Information System (INIS)

    The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2 = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R2 = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables prediction of both

  12. Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

    Directory of Open Access Journals (Sweden)

    Hasnain Seyed

    2004-09-01

    Full Text Available Abstract Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG, an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase

  13. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

    Energy Technology Data Exchange (ETDEWEB)

    Politi, Regina [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, University of North Carolina, Chapel Hill, NC 27599 (United States); Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599 (United States); Rusyn, Ivan, E-mail: iir@unc.edu [Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599 (United States); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, University of North Carolina, Chapel Hill, NC 27599 (United States)

    2014-10-01

    The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables

  14. Ligand-induced conformational changes: Improved predictions of ligand binding conformations and affinities

    DEFF Research Database (Denmark)

    Frimurer, T.M.; Peters, Günther H.J.; Iversen, L.F.;

    2003-01-01

    A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein...... tyrosine phosphatase 1 B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal...... with low estimated binding energies corresponded to relatively large RMS differences when aligned with the corresponding crystal structure. Secondly, the inhibitors were docked to their parent protein structures in which they were cocrystallized. In this case, there was a good correlation between low...

  15. Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules.

    Science.gov (United States)

    Glavatskikh, Marta; Madzhidov, Timur; Solov'ev, Vitaly; Marcou, Gilles; Horvath, Dragos; Graton, Jérôme; Le Questel, Jean-Yves; Varnek, Alexandre

    2016-02-01

    Halogen bonding (XB) strength assesses the ability of an electron-enriched group to be involved in complexes with polarizable electrophilic halogenated or diatomic halogen molecules. Here, we report QSPR models of XB of particular relevance for an efficient screening of large sets of compounds. The basicity is described by pKBI2 , the decimal logarithm of the experimental 1 : 1 (B : I2 ) complexation constant K of organic compounds (B) with diiodine (I2 ) as a reference halogen-bond donor in alkanes at 298 K. Modeling involved ISIDA fragment descriptors, using SVM and MLR methods on a set of 598 organic compounds. Developed models were then challenged to make predictions for an external test set of 11 polyfunctional compounds for which unambiguous assignment of the measured effective complexation constant to specific groups out of the putative acceptor sites is not granted. At this stage, developed models were used to predict pKBI2 of all putative acceptor sites, followed by an estimation of the predicted effective complexation constant using the ChemEqui program. The best consensus models perform well both in cross-validation (root mean squared error RMSE=0.39-0.47 logKBI2 units) and external predictions (RMSE=0.49). The SVM models are implemented on our website (http://infochim.u-strasbg.fr/webserv/VSEngine.html) together with the estimation of their applicability domain and an automatic detection of potential halogen-bond acceptor atoms. PMID:27491792

  16. Predicting protein-binding RNA nucleotides using the feature-based removal of data redundancy and the interaction propensity of nucleotide triplets.

    Science.gov (United States)

    Choi, Sungwook; Han, Kyungsook

    2013-11-01

    Several learning approaches have been used to predict RNA-binding amino acids in a protein sequence, but there has been little attempt to predict protein-binding nucleotides in an RNA sequence. One of the reasons is that the differences between nucleotides in their interaction propensity are much smaller than those between amino acids. Another reason is that RNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding RNA nucleotides is much harder than predicting RNA-binding amino acids. We developed a new method that removes data redundancy in a training set of sequences based on their features. The new method constructs a larger and more informative training set than the standard redundancy removal method based on sequence similarity, and the constructed dataset is guaranteed to be redundancy-free. We computed the interaction propensity (IP) of nucleotide triplets by applying a new definition of IP to an extensive dataset of protein-RNA complexes, and developed a support vector machine (SVM) model to predict protein binding sites in RNA sequences. In a 5-fold cross-validation with 812 RNA sequences, the SVM model predicted protein-binding nucleotides with an accuracy of 86.4%, an F-measure of 84.8%, and a Matthews correlation coefficient of 0.66. With an independent dataset of 56 RNA sequences that were not used in training, the resulting accuracy was 68.1% with an F-measure of 71.7% and a Matthews correlation coefficient of 0.35. To the best of our knowledge, this is the first attempt to predict protein-binding RNA nucleotides in a given RNA sequence from the sequence data alone. The SVM model and datasets are freely available for academics at http://bclab.inha.ac.kr/primer.

  17. Quantitative structure-property relationships modeling to predict in vitro and in vivo binding of drugs to the bile sequestrant, colesevelam (Welchol).

    Science.gov (United States)

    Walker, Joseph R; Brown, Karen; Rohatagi, Shashank; Bathala, Mohinder S; Xu, Chao; Wickremasingha, Prachi K; Salazar, Daniel E; Mager, Donald E

    2009-10-01

    Quantitative structure-property relationship (QSPR) models were developed to correlate physicochemical properties of structurally unrelated drugs with extent of in vitro binding to colesevelam, and predicted values were compared with drug exposure changes in vivo following coadministration. The binding of 17 drugs to colesevelam was determined by an in vitro dissolution drug-binding assay. Data from several clinical studies in healthy volunteers to support administration of colesevelam in diabetic patients were also collected along with existing in vivo literature data and compared with in vitro results. Steric, electronic, and hydrophobic descriptors were calculated for test compounds, and univariate and partial least squares regression approaches were used to derive QSPR models to evaluate which of the molecular descriptors correlated best with in vitro binding. A quadrant analysis evaluated the correlation between predicted/actual in vitro binding results and the in vivo data. The in vitro binding assay exhibited high sensitivity, identifying those compounds with a low probability of producing relevant in vivo drug interactions. Drug lipophilicity was identified as the primary determinant of in vitro binding to colesevelam by the final univariate and partial least squares models (R(2) = 0.69 and 0.98; Q(2) = 0.48 and 0.59). The in vitro assay and in silico models represent predictive tools that may allow investigators to conduct only informative clinical drug interaction studies with colesevelam.

  18. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data

    Directory of Open Access Journals (Sweden)

    Martin eReczko

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small regulatory genes regulating gene expression by targetingmessenger RNA. Though computational methods for miRNA target prediction are the prevailingmeans to analyze their function, they still miss a large fraction of the targeted genes and additionallypredict a large number of false positives. Here we introduce a novel algorithm called DIANAmicroT-ANN which combines multiple novel target site features through an artificial neural network(ANN and is trained using recently published high-throughput data measuring the change of proteinlevels after miRNA overexpression, providing positive and negative targeting examples. The featurescharacterizing each miRNA recognition element include binding structure, conservation level and aspecific profile of structural accessibility. The ANN is trained to integrate the features of eachrecognition element along the 3’ untranslated region into a targeting score, reproducing the relativerepression fold change of the protein. Tested on two different sets the algorithm outperforms otherwidely used algorithms and also predicts a significant number of unique and reliable targets notpredicted by the other methods. For 542 human miRNAs DIANA-microT-ANN predicts 120,000targets not provided by TargetScan 5.0. The algorithm is freely available athttp://microrna.gr/microT-ANN.

  19. Physics-based enzyme design: predicting binding affinity and catalytic activity.

    Science.gov (United States)

    Sirin, Sarah; Pearlman, David A; Sherman, Woody

    2014-12-01

    Computational enzyme design is an emerging field that has yielded promising success stories, but where numerous challenges remain. Accurate methods to rapidly evaluate possible enzyme design variants could provide significant value when combined with experimental efforts by reducing the number of variants needed to be synthesized and speeding the time to reach the desired endpoint of the design. To that end, extending our computational methods to model the fundamental physical-chemical principles that regulate activity in a protocol that is automated and accessible to a broad population of enzyme design researchers is essential. Here, we apply a physics-based implicit solvent MM-GBSA scoring approach to enzyme design and benchmark the computational predictions against experimentally determined activities. Specifically, we evaluate the ability of MM-GBSA to predict changes in affinity for a steroid binder protein, catalytic turnover for a Kemp eliminase, and catalytic activity for α-Gliadin peptidase variants. Using the enzyme design framework developed here, we accurately rank the most experimentally active enzyme variants, suggesting that this approach could provide enrichment of active variants in real-world enzyme design applications.

  20. Mannose binding lectin (MBL levels predict lung function decline in severe asthma

    Directory of Open Access Journals (Sweden)

    Ilonka. H. van Veen

    2006-12-01

    Full Text Available There is increasing evidence that activation of the complement system in asthma contributes to ongoing inflammation, tissue damage and airway remodeling. Mannose binding lectin (MBL is a pattern recognition molecule that serves as the key mediator of the lectin pathway of complement activation. MBL levels are genetically determined and vary widely amongst individuals. In the present study we hypothesized that high MBL levels in asthma are associated with increased loss of lung function over time, as a consequence of inflammatory tissue damage. We measured serum MBL levels by ELISA in 68 patients with severe asthma and prospectively determined the change in post-bronchodilator (pb FEV1 over a mean period of 5.7 years. The relationship between MBL and change in pbFEV1 (FEV1 was analysed using (multiple regression analysis and corrected for possible confounders (age, sex, age of onset, asthma duration, and pbFEV1. The median (range MBL level was 332 (10.8-3587 ng·ml–1. MBL was significantly associated with FEV1 (p<0.04. Patients with a high MBL level (332 ng·ml–1 had an increased risk of lung function decline compared to those with low MBL levels (OR (CI: 3.16 (1.14-8.79, p = 0.027; the excess decline being 42 ml·yr–1 (p = 0.01. We conclude that a high MBL level is associated with an increased decline in lung function in patients with severe asthma. MBL might provide a clue towards better understanding of the pathophysiology of ongoing inflammation and subsequent decline in lung function of patients with severe asthma.

  1. The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding

    DEFF Research Database (Denmark)

    Zhang, H.; Lund, Ole; Nielsen, M.

    2009-01-01

    the polymorphic pocket residues in MHC molecules that are in close proximity to the peptide residue. For MHC molecules with known specificities, we established a library of pocket-residues and corresponding binding specificities. The binding specificity for a novel MHC molecule is calculated as the average...

  2. Prediction of Surface and pH-Specific Binding of Peptides to Metal and Oxide Nanoparticles

    Science.gov (United States)

    Heinz, Hendrik; Lin, Tzu-Jen; Emami, Fateme Sadat; Ramezani-Dakhel, Hadi; Naik, Rajesh; Knecht, Marc; Perry, Carole C.; Huang, Yu

    2015-03-01

    The mechanism of specific peptide adsorption onto metallic and oxidic nanostructures has been elucidated in atomic resolution using novel force fields and surface models in comparison to measurements. As an example, variations in peptide adsorption on Pd and Pt nanoparticles depending on shape, size, and location of peptides on specific bounding facets are explained. Accurate computational predictions of reaction rates in C-C coupling reactions using particle models derived from HE-XRD and PDF data illustrate the utility of computational methods for the rational design of new catalysts. On oxidic nanoparticles such as silica and apatites, it is revealed how changes in pH lead to similarity scores of attracted peptides lower than 20%, supported by appropriate model surfaces and data from adsorption isotherms. The results demonstrate how new computational methods can support the design of nanoparticle carriers for drug release and the understanding of calcification mechanisms in the human body.

  3. Protein-DNA binding dynamics predict transcriptional response to nutrients in archaea.

    Science.gov (United States)

    Todor, Horia; Sharma, Kriti; Pittman, Adrianne M C; Schmid, Amy K

    2013-10-01

    Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators.

  4. Protein–DNA binding dynamics predict transcriptional response to nutrients in archaea

    Science.gov (United States)

    Todor, Horia; Sharma, Kriti; Pittman, Adrianne M. C.; Schmid, Amy K.

    2013-01-01

    Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators. PMID:23892291

  5. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lund, Ole

    2009-01-01

    this binding event. RESULTS: Here, we present a novel artificial neural network-based method, NN-align that allows for simultaneous identification of the MHC class II binding core and binding affinity. NN-align is trained using a novel training algorithm that allows for correction of bias in the training data...

  6. Mutational analysis of a predicted zinc-binding motif in the 26-kilodalton protein encoded by the vaccinia virus A2L gene: correlation of zinc binding with late transcriptional transactivation activity.

    OpenAIRE

    Keck, J G; Feigenbaum, F; B. Moss

    1993-01-01

    Transient transfection assays indicated that A2L is one of three vaccinia virus intermediate genes that are required for the transcriptional transactivation of viral late genes. We have expressed the A2L open reading frame in Escherichia coli and shown by blotting experiments that the 26-kDa protein binds zinc, a property predicted by the presence of a CX2CX13CX2C zinc finger motif. The specificity for zinc binding was demonstrated by competition with other metals. The role of the sequence mo...

  7. Holo- And Apo- Structures of Bacterial Periplasmic Heme Binding Proteins

    Energy Technology Data Exchange (ETDEWEB)

    Ho, W.W.; Li, H.; Eakanunkul, S.; Tong, Y.; Wilks, A.; Guo, M.; Poulos, T.L.

    2009-06-01

    An essential component of heme transport in Gram-negative bacterial pathogens is the periplasmic protein that shuttles heme between outer and inner membranes. We have solved the first crystal structures of two such proteins, ShuT from Shigella dysenteriae and PhuT from Pseudomonas aeruginosa. Both share a common architecture typical of Class III periplasmic binding proteins. The heme binds in a narrow cleft between the N- and C-terminal binding domains and is coordinated by a Tyr residue. A comparison of the heme-free (apo) and -bound (holo) structures indicates little change in structure other than minor alterations in the heme pocket and movement of the Tyr heme ligand from an 'in' position where it can coordinate the heme iron to an 'out' orientation where it points away from the heme pocket. The detailed architecture of the heme pocket is quite different in ShuT and PhuT. Although Arg{sup 228} in PhuT H-bonds with a heme propionate, in ShuT a peptide loop partially takes up the space occupied by Arg{sup 228}, and there is no Lys or Arg H-bonding with the heme propionates. A comparison of PhuT/ShuT with the vitamin B{sub 12}-binding protein BtuF and the hydroxamic-type siderophore-binding protein FhuD, the only two other structurally characterized Class III periplasmic binding proteins, demonstrates that PhuT/ShuT more closely resembles BtuF, which reflects the closer similarity in ligands, heme and B{sub 12}, compared with ligands for FhuD, a peptide siderophore.

  8. Predicting the binding free energy of the inclusion process of 2-hydroxypropyl-β-cyclodextrin and small molecules by means of the MM/3D-RISM method.

    Science.gov (United States)

    Sugita, Masatake; Hirata, Fumio

    2016-09-28

    A protocol to calculate the binding free energy of a host-guest system is proposed based on the MM/3D-RISM method, taking cyclodextrin derivatives and their ligands as model systems. The protocol involves the procedure to identify the most probable binding mode (MPBM) of receptors and ligands by means of the umbrella sampling method. The binding free energies calculated by the MM/3D-RISM method for the complexes of the seven ligands with the MPBM of the cyclodextrin, and with the fluctuated structures around it, are in agreement with the corresponding experimental data in a semi-quantitative manner. It suggests that the protocol proposed here is promising for predicting the binding affinity of a small ligand to a relatively rigid receptor such as cyclodextrin. PMID:27452185

  9. Predicting the binding free energy of the inclusion process of 2-hydroxypropyl-β-cyclodextrin and small molecules by means of the MM/3D-RISM method

    Science.gov (United States)

    Sugita, Masatake; Hirata, Fumio

    2016-09-01

    A protocol to calculate the binding free energy of a host–guest system is proposed based on the MM/3D-RISM method, taking cyclodextrin derivatives and their ligands as model systems. The protocol involves the procedure to identify the most probable binding mode (MPBM) of receptors and ligands by means of the umbrella sampling method. The binding free energies calculated by the MM/3D-RISM method for the complexes of the seven ligands with the MPBM of the cyclodextrin, and with the fluctuated structures around it, are in agreement with the corresponding experimental data in a semi-quantitative manner. It suggests that the protocol proposed here is promising for predicting the binding affinity of a small ligand to a relatively rigid receptor such as cyclodextrin.

  10. ¹³C NMR-distance matrix descriptors: optimal abstract 3D space granularity for predicting estrogen binding.

    Science.gov (United States)

    Slavov, Svetoslav H; Geesaman, Elizabeth L; Pearce, Bruce A; Schnackenberg, Laura K; Buzatu, Dan A; Wilkes, Jon G; Beger, Richard D

    2012-07-23

    An improved three-dimensional quantitative spectral data-activity relationship (3D-QSDAR) methodology was used to build and validate models relating the activity of 130 estrogen receptor binders to specific structural features. In 3D-QSDAR, each compound is represented by a unique fingerprint constructed from (13)C chemical shift pairs and associated interatomic distances. Grids of different granularity can be used to partition the abstract fingerprint space into congruent "bins" for which the optimal size was previously unexplored. For this purpose, the endocrine disruptor knowledge base data were used to generate 50 3D-QSDAR models with bins ranging in size from 2 ppm × 2 ppm × 0.5 Å to 20 ppm × 20 ppm × 2.5 Å, each of which was validated using 100 training/test set partitions. Best average predictivity in terms of R(2)test was achieved at 10 ppm ×10 ppm × Z Å (Z = 0.5, ..., 2.5 Å). It was hypothesized that this optimum depends on the chemical shifts' estimation error (±4.13 ppm) and the precision of the calculated interatomic distances. The highest ranked bins from partial least-squares weights were found to be associated with structural features known to be essential for binding to the estrogen receptor.

  11. gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.

    Science.gov (United States)

    Zhang, Yan-Ping; Wuyunqiqige; Zheng, Wei; Liu, Shuyi; Zhao, Chunguang

    2016-10-01

    DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which is a DNA-binding predictor that combines the support vector machine classifier and a novel kind of feature called graphical representation. The DNA-binding protein sequence information was described with the 20 probabilities of amino acids and the 23 new numerical graphical representation features of a protein sequence, based on 23 physicochemical properties of 20 amino acids. The Principal Components Analysis (PCA) was employed as feature selection method for removing the irrelevant features and reducing redundant features. The Sigmod function and Min-max normalization methods for PCA were applied to accelerate the training speed and obtain higher accuracy. Experiments demonstrated that the Principal Components Analysis with Sigmod function generated the best performance. The gDNA-Prot method was also compared with the DNAbinder, iDNA-Prot and DNA-Prot. The results suggested that gDNA-Prot outperformed the DNAbinder and iDNA-Prot. Although the DNA-Prot outperformed gDNA-Prot, gDNA-Prot was faster and convenient to predict the DNA-binding proteins. Additionally, the proposed gNDA-Prot method is available at http://sourceforge.net/projects/gdnaprot.

  12. gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.

    Science.gov (United States)

    Zhang, Yan-Ping; Wuyunqiqige; Zheng, Wei; Liu, Shuyi; Zhao, Chunguang

    2016-10-01

    DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which is a DNA-binding predictor that combines the support vector machine classifier and a novel kind of feature called graphical representation. The DNA-binding protein sequence information was described with the 20 probabilities of amino acids and the 23 new numerical graphical representation features of a protein sequence, based on 23 physicochemical properties of 20 amino acids. The Principal Components Analysis (PCA) was employed as feature selection method for removing the irrelevant features and reducing redundant features. The Sigmod function and Min-max normalization methods for PCA were applied to accelerate the training speed and obtain higher accuracy. Experiments demonstrated that the Principal Components Analysis with Sigmod function generated the best performance. The gDNA-Prot method was also compared with the DNAbinder, iDNA-Prot and DNA-Prot. The results suggested that gDNA-Prot outperformed the DNAbinder and iDNA-Prot. Although the DNA-Prot outperformed gDNA-Prot, gDNA-Prot was faster and convenient to predict the DNA-binding proteins. Additionally, the proposed gNDA-Prot method is available at http://sourceforge.net/projects/gdnaprot. PMID:27378005

  13. An improved method for TAL effectors DNA-binding sites prediction reveals functional convergence in TAL repertoires of Xanthomonas oryzae strains.

    Directory of Open Access Journals (Sweden)

    Alvaro L Pérez-Quintero

    Full Text Available Transcription Activators-Like Effectors (TALEs belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.

  14. In silico peptide-binding predictions of passerine MHC class I reveal similarities across distantly related species, suggesting convergence on the level of protein function

    DEFF Research Database (Denmark)

    Follin, Elna; Karlsson, Maria; Lundegaard, Claus;

    2013-01-01

    compared to most mammals. To elucidate the reason for this large number of genes, we compared 14 MHC class I alleles (α1–α3 domains), from great reed warbler, house sparrow and tree sparrow, via phylogenetic analysis, homology modelling and in silico peptide-binding predictions to investigate...... is of functional significance. The MHC class I allomorphs from house sparrow and tree sparrow, species that diverged 10 million years ago (MYA), had overlapping peptide-binding specificities, and these similarities across species were also confirmed in phylogenetic analyses based on amino acid sequences. Notably......, there were also overlapping peptide-binding specificities in the allomorphs from house sparrow and great reed warbler, although these species diverged 30 MYA. This overlap was not found in a tree based on amino acid sequences. Our interpretation is that convergent evolution on the level of the protein...

  15. Improving the performance of the PLB index for ligand-binding site prediction using dihedral angles and the solvent-accessible surface area.

    Science.gov (United States)

    Cao, Chen; Xu, Shutan

    2016-01-01

    Protein ligand-binding site prediction is highly important for protein function determination and structure-based drug design. Over the past twenty years, dozens of computational methods have been developed to address this problem. Soga et al. identified ligand cavities based on the preferences of amino acids for the ligand-binding site (RA) and proposed the propensity for ligand binding (PLB) index to rank the cavities on the protein surface. However, we found that residues exhibit different RAs in response to changes in solvent exposure. Furthermore, previous studies have suggested that some dihedral angles of amino acids in specific regions of the Ramachandran plot are preferred at the functional sites of proteins. Based on these discoveries, the amino acid solvent-accessible surface area and dihedral angles were combined with the RA and PLB to obtain two new indexes, multi-factor RA (MF-RA) and multi-factor PLB (MF-PLB). MF-PLB, PLB and other methods were tested using two benchmark databases and two particular ligand-binding sites. The results show that MF-PLB can improve the success rate of PLB for both ligand-bound and ligand-unbound structures, particularly for top choice prediction. PMID:27619067

  16. [Predicting the cadmium bioavailability in the soil of sugarcane field based on the diffusive gradients in thin films with binding phase of sodium polyacrylate].

    Science.gov (United States)

    Wang, Fang-Li; Song, Ning-Ning; Zhao, Yu-Jie; Zhang, Chang-Bo; Shen, Yue; Liu, Zhong-Qi

    2012-10-01

    The diffusive gradients in thin films (DGT) technique with solid-state binding phases has been widely used for in situ collection and measurement of available heavy metals in waters, soils or sediments, whereas DGT with liquid binding phase is primarily used in the in situ analysis of heavy metals in waters. In this paper, rhizosphere soils of sugarcane were collected in Guangxi and the concentrations of cadmium (Cd) were determined by DGT with a solid-state binding phase of chelex100 (chelex100-DGT) and modified DGT with a liquid binding phase of sodium polyacrylate (CDM-PAAS-DGT). The result showed that the Cd contents in soils measured by DGT with both binding phases and Cd in the roots, leaves and unpolished stems of sugarcane had significant positive correlation. The extraction ability of the CDM-PAAAS-DGT was much higher than that of the chelex100-DGT. In addition, multivariate analyses were used to assess the impact of pH, cation exchange capacity (CEC), soil organic matter (OM) and texture. Two principal components were extracted and the linear regression models were established. The Cd bioavailability in soils could be accurately predicted by the CDM-PAAAS-DGT technique, which expanded its applicable area. PMID:23233989

  17. DAT versus D2 receptor binding in the rat striatum: l-DOPA-induced motor activity is better predicted by reuptake than release of dopamine.

    Science.gov (United States)

    Nikolaus, Susanne; Beu, Markus; Angelica De Souza Silva, Maria; Huston, Joseph P; Hautzel, Hubertus; Antke, Christina; Müller, Hans-Wilhelm

    2016-09-01

    The reuptake and release of dopamine (DA) can be estimated using in vivo imaging methods by assessing the competition between endogenous DA and an administered exogenous DA transporter (DAT) and D2 receptor (D2 R) radioligand, respectively. The aim of this study was to investigate the comparative roles of DA release vs DA reuptake in the rat striatum with small animal SPECT in relation to l-DOPA-induced behaviors. DAT and D2 R binding, together with behavioral measures, were obtained in 99 rats in response to treatment with either 5 or 10 mg/kg l-DOPA or vehicle. The behavioral parameters included the distance travelled, and durations and frequencies of ambulation, sitting, rearing, head-shoulder motility, and grooming. Data were subjected to a cluster analysis and to a multivariate principal component analysis. The highest DAT binding (i.e., the lowest DA reuptake) was associated with the highest, and the lowest DAT binding (i.e., the highest DA reuptake) was associated with the lowest motor/exploratory activity. The highest and the lowest D2 R binding (i.e., the lowest and the highest DA release, respectively) were merely associated with the second highest and second lowest levels of motor/exploratory activity. These findings indicate that changes in DA reuptake in response to fluctuating DA levels offer a better prediction of motor activity than the release of DA into the synaptic cleft. This dissociation, as reflected by in vivo DAT and D2 R binding data, may be accounted for by the regulatory sensitization meachnisms that occur at D2 R binding sites in response to altered levels of DA. Synapse 70:369-377, 2016. © 2016 Wiley Periodicals, Inc. PMID:27164322

  18. Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.

    Science.gov (United States)

    Paricharak, Shardul; Cortés-Ciriano, Isidro; IJzerman, Adriaan P; Malliavin, Thérèse E; Bender, Andreas

    2015-01-01

    The rampant increase of public bioactivity databases has fostered the development of computational chemogenomics methodologies to evaluate potential ligand-target interactions (polypharmacology) both in a qualitative and quantitative way. Bayesian target prediction algorithms predict the probability of an interaction between a compound and a panel of targets, thus assessing compound polypharmacology qualitatively, whereas structure-activity relationship techniques are able to provide quantitative bioactivity predictions. We propose an integrated drug discovery pipeline combining in silico target prediction and proteochemometric modelling (PCM) for the respective prediction of compound polypharmacology and potency/affinity. The proposed pipeline was evaluated on the retrospective discovery of Plasmodium falciparum DHFR inhibitors. The qualitative in silico target prediction model comprised 553,084 ligand-target associations (a total of 262,174 compounds), covering 3,481 protein targets and used protein domain annotations to extrapolate predictions across species. The prediction of bioactivities for plasmodial DHFR led to a recall value of 79% and a precision of 100%, where the latter high value arises from the structural similarity of plasmodial DHFR inhibitors and T. gondii DHFR inhibitors in the training set. Quantitative PCM models were then trained on a dataset comprising 20 eukaryotic, protozoan and bacterial DHFR sequences, and 1,505 distinct compounds (in total 3,099 data points). The most predictive PCM model exhibited R (2) 0 test and RMSEtest values of 0.79 and 0.59 pIC50 units respectively, which was shown to outperform models based exclusively on compound (R (2) 0 test/RMSEtest = 0.63/0.78) and target information (R (2) 0 test/RMSEtest = 0.09/1.22), as well as inductive transfer knowledge between targets, with respective R (2) 0 test and RMSEtest values of 0.76 and 0.63 pIC50 units. Finally, both methods were integrated to predict the protein

  19. NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Blicher, Thomas;

    2007-01-01

    surpassed 1500. Characterizing the specificity of each separately would be a major undertaking. PRINCIPAL FINDINGS: Here, we have drawn on a large database of known peptide-HLA-I interactions to develop a bioinformatics method, which takes both peptide and HLA sequence information into account, and...... generates quantitative predictions of the affinity of any peptide-HLA-I interaction. Prospective experimental validation of peptides predicted to bind to previously untested HLA-I molecules, cross-validation, and retrospective prediction of known HIV immune epitopes and endogenous presented peptides, all...... provide new basic insights into HLA structure-function relationships. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan....

  20. Coarse-grained/molecular mechanics of the TAS2R38 bitter taste receptor: experimentally-validated detailed structural prediction of agonist binding.

    Directory of Open Access Journals (Sweden)

    Alessandro Marchiori

    Full Text Available Bitter molecules in humans are detected by ∼25 G protein-coupled receptors (GPCRs. The lack of atomic resolution structure for any of them is complicating an in depth understanding of the molecular mechanisms underlying bitter taste perception. Here, we investigate the molecular determinants of the interaction of the TAS2R38 bitter taste receptor with its agonists phenylthiocarbamide (PTC and propylthiouracil (PROP. We use the recently developed hybrid Molecular Mechanics/Coarse Grained (MM/CG method tailored specifically for GPCRs. The method, through an extensive exploration of the conformational space in the binding pocket, allows the identification of several residues important for agonist binding that would have been very difficult to capture from the standard bioinformatics/docking approach. Our calculations suggest that both agonists bind to Asn103, Phe197, Phe264 and Trp201, whilst they do not interact with the so-called extra cellular loop 2, involved in cis-retinal binding in the GPCR rhodopsin. These predictions are consistent with data sets based on more than 20 site-directed mutagenesis and functional calcium imaging experiments of TAS2R38. The method could be readily used for other GPCRs for which experimental information is currently lacking.

  1. Predicting treatment response in Schizophrenia: the role of stratal and frontal dopamine D2/D3 receptor binding potential

    DEFF Research Database (Denmark)

    Wulff, Sanne; Nørbak-Emig, Henrik; Nielsen, Mette Ødegaard;

    2014-01-01

    the ligand [123]IBZM (123labeled iodbenzamid) to examine the binding potential (BP) of dopamine D2/D3 receptors in striatum. Patients were treated with amisulpride for six weeks. In the EPIcohort we included 25 patients. The ligand [123I]epidepride was used for quantification of extrastriatal dopamine D2/D3...

  2. Predicting treatment response in schizophrenia: The role of striatal and frontal dopamine D2/D3 receptor binding potential

    DEFF Research Database (Denmark)

    Nørbak, Henrik; Wulff, Sanne; Nielsen, Mette Ødegaard;

    structural Magnetic Resonance Imaging, SPECT and PANSS. In the IBZMcohort we included 26 patients. We used the ligand [123]IBZM (123labeled iodbenzamid) to examine the binding potential (BP) of dopamine D2/D3 receptors in striatum. Patients were treated with amisulpride for six weeks. In the EPIcohort we...

  3. Predicting Allosteric Effects from Orthosteric Binding in Hsp90-Ligand Interactions: Implications for Fragment-Based Drug Design

    Science.gov (United States)

    Larsson, Andreas; Nordlund, Paer; Jansson, Anna; Anand, Ganesh S.

    2016-01-01

    A key question in mapping dynamics of protein-ligand interactions is to distinguish changes at binding sites from those associated with long range conformational changes upon binding at distal sites. This assumes a greater challenge when considering the interactions of low affinity ligands (dissociation constants, KD, in the μM range or lower). Amide hydrogen deuterium Exchange mass spectrometry (HDXMS) is a robust method that can provide both structural insights and dynamics information on both high affinity and transient protein-ligand interactions. In this study, an application of HDXMS for probing the dynamics of low affinity ligands to proteins is described using the N-terminal ATPase domain of Hsp90. Comparison of Hsp90 dynamics between high affinity natural inhibitors (KD ~ nM) and fragment compounds reveal that HDXMS is highly sensitive in mapping the interactions of both high and low affinity ligands. HDXMS reports on changes that reflect both orthosteric effects and allosteric changes accompanying binding. Orthosteric sites can be identified by overlaying HDXMS onto structural information of protein-ligand complexes. Regions distal to orthosteric sites indicate long range conformational changes with implications for allostery. HDXMS, thus finds powerful utility as a high throughput method for compound library screening to identify binding sites and describe allostery with important implications for fragment-based ligand discovery (FBLD). PMID:27253209

  4. Predicting Allosteric Effects from Orthosteric Binding in Hsp90-Ligand Interactions: Implications for Fragment-Based Drug Design.

    Directory of Open Access Journals (Sweden)

    Arun Chandramohan

    2016-06-01

    Full Text Available A key question in mapping dynamics of protein-ligand interactions is to distinguish changes at binding sites from those associated with long range conformational changes upon binding at distal sites. This assumes a greater challenge when considering the interactions of low affinity ligands (dissociation constants, KD, in the μM range or lower. Amide hydrogen deuterium Exchange mass spectrometry (HDXMS is a robust method that can provide both structural insights and dynamics information on both high affinity and transient protein-ligand interactions. In this study, an application of HDXMS for probing the dynamics of low affinity ligands to proteins is described using the N-terminal ATPase domain of Hsp90. Comparison of Hsp90 dynamics between high affinity natural inhibitors (KD ~ nM and fragment compounds reveal that HDXMS is highly sensitive in mapping the interactions of both high and low affinity ligands. HDXMS reports on changes that reflect both orthosteric effects and allosteric changes accompanying binding. Orthosteric sites can be identified by overlaying HDXMS onto structural information of protein-ligand complexes. Regions distal to orthosteric sites indicate long range conformational changes with implications for allostery. HDXMS, thus finds powerful utility as a high throughput method for compound library screening to identify binding sites and describe allostery with important implications for fragment-based ligand discovery (FBLD.

  5. Urinary liver-type fatty acid-binding protein predicts progression to nephropathy in type 1 diabetic patients

    DEFF Research Database (Denmark)

    Nielsen, Stine Elkjaer; Sugaya, Takeshi; Hovind, Peter;

    2010-01-01

    Urinary liver-type fatty acid-binding protein (u-LFABP) is a marker of tubulointerstitial inflammation and has been shown to be increased in patients with type 1 diabetes and is further increased in patients who progress to micro- and macroalbuminuria. Our aim was to evaluate u-LFABP as a predictor...

  6. Predicting novel binding modes of agonists to β adrenergic receptors using all-atom molecular dynamics simulations.

    Directory of Open Access Journals (Sweden)

    Stefano Vanni

    Full Text Available Understanding the binding mode of agonists to adrenergic receptors is crucial to enabling improved rational design of new therapeutic agents. However, so far the high conformational flexibility of G protein-coupled receptors has been an obstacle to obtaining structural information on agonist binding at atomic resolution. In this study, we report microsecond classical molecular dynamics simulations of β(1 and β(2 adrenergic receptors bound to the full agonist isoprenaline and in their unliganded form. These simulations show a novel agonist binding mode that differs from the one found for antagonists in the crystal structures and from the docking poses reported by in silico docking studies performed on rigid receptors. Internal water molecules contribute to the stabilization of novel interactions between ligand and receptor, both at the interface of helices V and VI with the catechol group of isoprenaline as well as at the interface of helices III and VII with the ethanolamine moiety of the ligand. Despite the fact that the characteristic N-C-C-OH motif is identical in the co-crystallized ligands and in the full agonist isoprenaline, the interaction network between this group and the anchor site formed by Asp(3.32 and Asn(7.39 is substantially different between agonists and inverse agonists/antagonists due to two water molecules that enter the cavity and contribute to the stabilization of a novel network of interactions. These new binding poses, together with observed conformational changes in the extracellular loops, suggest possible determinants of receptor specificity.

  7. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals

    OpenAIRE

    Huixiao Hong; Jie Shen; Hui Wen Ng; Sugunadevi Sakkiah; Hao Ye; Weigong Ge; Ping Gong; Wenming Xiao; Weida Tong

    2016-01-01

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endo...

  8. Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

    Science.gov (United States)

    The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

  9. Murine hyperglycemic vasculopathy and cardiomyopathy: whole-genome gene expression analysis predicts cellular targets and regulatory networks influenced by mannose binding lectin

    Directory of Open Access Journals (Sweden)

    Chenhui eZou

    2012-02-01

    Full Text Available Hyperglycemia, in the absence of type 1 or 2 diabetes, is an independent risk factor for cardiovascular disease. We have previously demonstrated a central role for mannose binding lectin (MBL-mediated cardiac dysfunction in acute hyperglycemic mice. In this study, we applied whole genome microarray data analysis to investigate MBL’s role in systematic gene expression changes. The data predict possible intracellular events taking place in multiple cellular compartments such as enhanced insulin signaling pathway sensitivity, promoted mitochondrial respiratory function, improved cellular energy expenditure and protein quality control, improved cytoskeleton structure and facilitated intracellular trafficking, all of which may contribute to the organismal health of MBL null mice against acute hyperglycemia. Our data show a tight association between gene expression profile and tissue function which might be a very useful tool in predicting cellular targets and regulatory networks connected with in vivo observations, providing clues for further mechanistic studies.

  10. Urinary Liver-Type Fatty Acid-Binding Protein Predicts Progression to Nephropathy in Type 1 Diabetic Patients

    OpenAIRE

    Nielsen, Stine Elkjaer; Sugaya, Takeshi; Hovind, Peter; Baba, Tsuneharu; Parving, Hans-Henrik; Rossing, Peter

    2010-01-01

    OBJECTIVE Urinary liver-type fatty acid-binding protein (u-LFABP) is a marker of tubulointerstitial inflammation and has been shown to be increased in patients with type 1 diabetes and is further increased in patients who progress to micro- and macroalbuminuria. Our aim was to evaluate u-LFABP as a predictor of progression to micro- and macroalbuminuria in type 1 diabetes. RESEARCH DESIGN AND METHODS From an inception cohort of 277 patients, u-LFABP, adjusted for urinary creatinine (enzyme-li...

  11. Monitoring of Urinary L-Type Fatty Acid-Binding Protein Predicts Histological Severity of Acute Kidney Injury

    OpenAIRE

    Negishi, Kousuke; Noiri, Eisei; DOI, Kent; Maeda-Mamiya, Rui; Sugaya, Takeshi; Portilla, Didier; Fujita, Toshiro

    2009-01-01

    The present study aimed to evaluate whether levels of urinary L-type fatty acid-binding protein (L-FABP) could be used to monitor histological injury in acute kidney injury (AKI) induced by cis-platinum (CP) injection and ischemia reperfusion (IR). Different degrees of AKI severity were induced by several renal insults (CP dose and ischemia time) in human L-FABP transgenic mice. Renal histological injury scores increased with both CP dose and ischemic time. In CP-induced AKI, urinary L-FABP l...

  12. High-Throughput Melanin-Binding Affinity and In Silico Methods to Aid in the Prediction of Drug Exposure in Ocular Tissue.

    Science.gov (United States)

    Reilly, John; Williams, Sarah L; Forster, Cornelia J; Kansara, Viral; End, Peter; Serrano-Wu, Michael H

    2015-12-01

    Drugs possessing the ability to bind to melanin-rich tissue, such as the eye, are linked with higher ocular exposure, and therefore have the potential to affect the efficacy and safety profiles of therapeutics. A high-throughput melanin chromatographic affinity assay has been developed and validated, which has allowed the rapid melanin affinity assessment for a large number of compounds. Melanin affinity of compounds can be quickly assigned as low, medium, or high melanin binders. A high-throughput chromatographic method has been developed and fully validated to assess melanin affinity of pharmaceuticals and has been useful in predicting ocular tissue distribution in vivo studies. The high-throughput experimental approach has also allowed for a specific training set of 263 molecules for a quantitative structure-affinity relationships (QSAR) method to be developed, which has also been shown to be a predictor of ocular tissue exposure. Previous studies have reported the development of in silico QSAR models based on training sets of relatively small and mostly similar compounds; this model covers a broader range of melanin-binding affinities than what has been previously published and identified several physiochemical descriptors to be considered in the design of compounds where melanin-binding modulation is desired.

  13. Prediction and validation of protein–protein interactors from genome-wide DNA-binding data using a knowledge-based machine-learning approach

    Science.gov (United States)

    Homan, Bernou; Mohamed, Stephanie; Harvey, Richard P.; Bouveret, Romaric

    2016-01-01

    The ability to accurately predict the DNA targets and interacting cofactors of transcriptional regulators from genome-wide data can significantly advance our understanding of gene regulatory networks. NKX2-5 is a homeodomain transcription factor that sits high in the cardiac gene regulatory network and is essential for normal heart development. We previously identified genomic targets for NKX2-5 in mouse HL-1 atrial cardiomyocytes using DNA-adenine methyltransferase identification (DamID). Here, we apply machine learning algorithms and propose a knowledge-based feature selection method for predicting NKX2-5 protein : protein interactions based on motif grammar in genome-wide DNA-binding data. We assessed model performance using leave-one-out cross-validation and a completely independent DamID experiment performed with replicates. In addition to identifying previously described NKX2-5-interacting proteins, including GATA, HAND and TBX family members, a number of novel interactors were identified, with direct protein : protein interactions between NKX2-5 and retinoid X receptor (RXR), paired-related homeobox (PRRX) and Ikaros zinc fingers (IKZF) validated using the yeast two-hybrid assay. We also found that the interaction of RXRα with NKX2-5 mutations found in congenital heart disease (Q187H, R189G and R190H) was altered. These findings highlight an intuitive approach to accessing protein–protein interaction information of transcription factors in DNA-binding experiments. PMID:27683156

  14. HADDOCK2P2I : A biophysical model for predicting the binding affinity of protein-protein interaction inhibitors

    NARCIS (Netherlands)

    Kastritis, Panagiotis L.; Garcia Lopes Maia Rodrigues, João; Bonvin, Alexandre M J J

    2014-01-01

    The HADDOCK score, a scoring function for both protein-protein and protein-nucleic acid modeling, has been successful in selecting near-native docking poses in a variety of cases, including those of the CAPRI blind prediction experiment. However, it has yet to be optimized for small molecules, and i

  15. Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

    Directory of Open Access Journals (Sweden)

    Katherine Gurdziel

    Full Text Available The Hedgehog (Hh signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthodenticle contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A (Cpr100A; invected (inv, which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx, the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb; and two previously untested regions of the Hh receptor-encoding patched (ptc gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci.

  16. Predicting promiscuous antigenic T cell epitopes of Mycobacterium tuberculosis mymA operon proteins binding to MHC Class I and Class II molecules.

    Science.gov (United States)

    Saraav, Iti; Pandey, Kirti; Sharma, Monika; Singh, Swati; Dutta, Prasun; Bhardwaj, Anshu; Sharma, Sadhna

    2016-10-01

    Limited efficacy of Bacillus Calmette-Guérin vaccine has raised the need to explore other immunogenic candidates to develop an effective vaccine against Mycobacterium tuberculosis (Mtb). Both CD4+ and CD8+ T cells play a critical role in host immunity to Mtb. Infection of macrophages with Mtb results in upregulation of mymA operon genes thereby suggesting their importance as immune targets. In the present study, after exclusion of self-peptides mymA operon proteins of Mtb were analyzed in silico for the presence of Human Leukocyte Antigen (HLA) Class I and Class II binding peptides using Bioinformatics and molecular analysis section, NetMHC 3.4, ProPred and Immune epitope database software. Out of 56 promiscuous epitopes obtained, 41 epitopes were predicted to be antigenic for MHC Class I. In MHC Class II, out of 336 promiscuous epitopes obtained, 142 epitopes were predicted to be antigenic. The comparative bioinformatics analysis of mymA operon proteins found Rv3083 to be the best vaccine candidate. Molecular docking was performed with the most antigenic peptides of Rv3083 (LASGAASVV with alleles HLA-B51:01, HAATSGTLI with HLA-A02, IVTATGLNI and EKIHYGLKVNTA with HLA-DRB1_01:01) to study the structural basis for recognition of peptides by various HLA molecules. The software binding prediction was validated by the obtained molecular docking score of peptide-HLA complex. These peptides can be further investigated for their immunological relevance in patients of tuberculosis using major histocompatibility complex tetramer approach. PMID:27389362

  17. Integrative genomic analyses of the RNA-binding protein, RNPC1, and its potential role in cancer prediction.

    Science.gov (United States)

    Ding, Zhiming; Yang, Hai-Wei; Xia, Tian-Song; Wang, Bo; Ding, Qiang

    2015-08-01

    The RNA binding motif protein 38 (RBM38, also known as RNPC1) plays a pivotal role in regulating a wide range of biological processes, from cell proliferation and cell cycle arrest to cell myogenic differentiation. It was originally recognized as an oncogene, and was frequently found to be amplified in prostate, ovarian and colorectal cancer, chronic lymphocytic leukemia, colon carcinoma, esophageal cancer, dog lymphomas and breast cancer. In the present study, the complete RNPC1 gene was identified in a number of vertebrate genomes, suggesting that RNPC1 exists in all types of vertebrates, including fish, amphibians, birds and mammals. In the different genomes, the gene had a similar 4 exon/3 intron organization, and all the genetic loci were syntenically conserved. The phylogenetic tree demonstrated that the RNPC1 gene from the mammalian, bird, reptile and teleost lineage formed a species-specific cluster. A total of 34 functionally relevant single nucleotide polymorphisms (SNPs), including 14 SNPs causing missense mutations, 8 exonic splicing enhancer SNPs and 12 SNPs causing nonsense mutations, were identified in the human RNPC1 gene. RNPC1 was found to be expressed in bladder, blood, brain, breast, colorectal, eye, head and neck, lung, ovarian, skin and soft tissue cancer. In 14 of the 94 tests, an association between RNPC1 gene expression and cancer prognosis was observed. We found that the association between the expression of RNPC1 and prognosis varied in different types of cancer, and even in the same type of cancer from the different databases used. This suggests that the function of RNPC1 in these tumors may be multidimensional. The sex determining region Y (SRY)-box 5 (Sox5), runt-related transcription factor 3 (RUNX3), CCAAT displacement protein 1 (CUTL1), v-rel avian reticuloendotheliosis viral oncogene homolog (Rel)A, peroxisome proliferator-activated receptor γ isoform 2 (PPARγ2) and activating transcription factor 6 (ATF6) regulatory

  18. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  19. Crystal structure of tyrosine decarboxylase and identification of key residues involved in conformational swing and substrate binding

    Science.gov (United States)

    Zhu, Haixia; Xu, Guochao; Zhang, Kai; Kong, Xudong; Han, Ruizhi; Zhou, Jiahai; Ni, Ye

    2016-01-01

    Tyrosine decarboxylase (TDC) is a pyridoxal 5-phosphate (PLP)-dependent enzyme and is mainly responsible for the synthesis of tyramine, an important biogenic amine. In this study, the crystal structures of the apo and holo forms of Lactobacillus brevis TDC (LbTDC) were determined. The LbTDC displays only 25% sequence identity with the only reported TDC structure. Site-directed mutagenesis of the conformationally flexible sites and catalytic center was performed to investigate the potential catalytic mechanism. It was found that H241 in the active site plays an important role in PLP binding because it has different conformations in the apo and holo structures of LbTDC. After binding to PLP, H241 rotated to the position adjacent to the PLP pyridine ring. Alanine scanning mutagenesis revealed several crucial regions that determine the substrate specificity and catalytic activity. Among the mutants, the S586A variant displayed increased catalytic efficiency and substrate affinity, which is attributed to decreased steric hindrance and increased hydrophobicity, as verified by the saturation mutagenesis at S586. Our results provide structural information about the residues important for the protein engineering of TDC to improve catalytic efficiency in the green manufacturing of tyramine. PMID:27292129

  20. Crystal structure of tyrosine decarboxylase and identification of key residues involved in conformational swing and substrate binding.

    Science.gov (United States)

    Zhu, Haixia; Xu, Guochao; Zhang, Kai; Kong, Xudong; Han, Ruizhi; Zhou, Jiahai; Ni, Ye

    2016-01-01

    Tyrosine decarboxylase (TDC) is a pyridoxal 5-phosphate (PLP)-dependent enzyme and is mainly responsible for the synthesis of tyramine, an important biogenic amine. In this study, the crystal structures of the apo and holo forms of Lactobacillus brevis TDC (LbTDC) were determined. The LbTDC displays only 25% sequence identity with the only reported TDC structure. Site-directed mutagenesis of the conformationally flexible sites and catalytic center was performed to investigate the potential catalytic mechanism. It was found that H241 in the active site plays an important role in PLP binding because it has different conformations in the apo and holo structures of LbTDC. After binding to PLP, H241 rotated to the position adjacent to the PLP pyridine ring. Alanine scanning mutagenesis revealed several crucial regions that determine the substrate specificity and catalytic activity. Among the mutants, the S586A variant displayed increased catalytic efficiency and substrate affinity, which is attributed to decreased steric hindrance and increased hydrophobicity, as verified by the saturation mutagenesis at S586. Our results provide structural information about the residues important for the protein engineering of TDC to improve catalytic efficiency in the green manufacturing of tyramine. PMID:27292129

  1. Monitoring of urinary L-type fatty acid-binding protein predicts histological severity of acute kidney injury.

    Science.gov (United States)

    Negishi, Kousuke; Noiri, Eisei; Doi, Kent; Maeda-Mamiya, Rui; Sugaya, Takeshi; Portilla, Didier; Fujita, Toshiro

    2009-04-01

    The present study aimed to evaluate whether levels of urinary L-type fatty acid-binding protein (L-FABP) could be used to monitor histological injury in acute kidney injury (AKI) induced by cis-platinum (CP) injection and ischemia reperfusion (IR). Different degrees of AKI severity were induced by several renal insults (CP dose and ischemia time) in human L-FABP transgenic mice. Renal histological injury scores increased with both CP dose and ischemic time. In CP-induced AKI, urinary L-FABP levels increased exponentially even in the lowest dose group as early as 2 hours, whereas blood urea nitrogen (BUN) levels increased at 48 hours. In IR-induced AKI, BUN levels increased only in the 30-minute ischemia group 24 hours after reperfusion; however, urinary L-FABP levels increased more than 100-fold, even in the 5-minute ischemia group after 1 hour. In both AKI models, urinary L-FABP levels showed a better correlation with final histological injury scores and glomerular filtration rates measured by fluorescein isothiocyanate-labeled inulin injection than with levels of BUN and urinary N-acetyl-D-glucosaminidase, especially at earlier time points. Receiver operating characteristic curve analysis demonstrated that urinary L-FABP was superior to other biomarkers for the detection of significant histological injuries and functional declines. In conclusion, urinary L-FABP levels are better suited to allow the accurate and earlier detection of both histological and functional insults in ischemic and nephrotoxin-induced AKI compared with conventional renal markers.

  2. IGF-1 receptor and IGF binding protein-3 might predict prognosis of patients with resectable pancreatic cancer

    International Nuclear Information System (INIS)

    The present study aimed to elucidate the clinicopathologic role of insulin-like growth factor-1 receptor (IGF1R) and IGF binding protein-3 (IGFBP3) in patients with pancreatic cancer. The function of IGFBP3 is controversial, because both inhibition and facilitation of the action of IGF as well as IGF-independent effects have been reported. In this study, IGF1R and IGFBP3 expression was examined, and their potential roles as prognostic markers in patients with pancreatic cancer were evaluated. Clinicopathological features of 122 patients with curatively resected pancreatic cancer were retrospectively reviewed, and expression of IGF1R and IGFBP3 was immunohistochemically analyzed. Expression of IGF1R and IGFBP3 was observed in 50 (41.0%) and 37 (30.3%) patients, respectively. IGF1R expression was significantly associated with histological grade (p = 0.037). IGFBP3 expression had a significant association with tumor location (p = 0.023), and a significant inverse association with venous invasion (p = 0.037). Tumors with IGF1R-positive and IGFBP3-negative expression (n = 32) were significantly frequently Stage II and III (p = 0.011). The prognosis for IGF1R positive patients was significantly poorer than that for IGF1R negative patients (p = 0.0181). IGFBP3 protein expression did not correlate significantly with patient survival. The subset of patients with both positive IGF1R and negative IGFBP3 had worse overall survival (8.8 months versus 12.6 months, respectively, p < 0.001). IGF1R signaling might be associated with tumor aggressiveness, and IGFBP3 might show antiproliferative effects in pancreatic cancer. Both high IGF1R expression and low IGFBP3 expression represent useful prognostic markers for patients with curatively resected pancreatic cancer

  3. In situ study of binding of copper by fulvic acid: comparison of differential absorbance data and model predictions.

    Science.gov (United States)

    Yan, Mingquan; Dryer, Deborah; Korshin, Gregory V; Benedetti, Marc F

    2013-02-01

    This study examined the binding of copper(II) by Suwannee River fulvic acid (SRFA) using the method of differential absorbance that was used at environmentally-relevant concentrations of copper and SRFA. The pH- and metal-differential spectra were processed via numeric deconvolution to establish commonalities seen in the changes of absorbance caused by deprotonation of SRFA and its interactions with copper(II) ions. Six Gaussian bands were determined to be present in both the pH- and Cu-differential spectra. Their maxima were located, in the order of increasing wavelengths at 208 nm, 242 nm, 276 nm, 314 nm, 378 nm and 551 nm. The bands with these maxima were denoted as A0, A1, A2, A3, A4 and A5, respectively. Properties of these bands were compared with those existing in the spectra of model compounds such as sulfosalicylic acid (SSA), tannic acid (TA), and polystyrenesulfonic acid-co-maleic acid (PSMA). While none of the features observed in differential spectra of the model compound were identical to those present in the case of SRFA, Gaussian bands A1, A3 and possibly A2 were concluded to be largely attributable to a combination of responses of salicylic- and polyhydroxyphenolic groups. In contrast, bands A4 and A5 were detected in the differential spectra of SRFA only. Their nature remains to be elucidated. To examine correlations between the amount of copper(II) bound by SRFA and changes of its absorbance, differential absorbances measured at indicative wavelengths 250 nm and 400 nm were compared with the total amount of SRFA-bound copper estimated based on Visual MINTEQ calculations. This examination showed that the differential absorbances of SRFA in a wide range of pH values and copper concentrations were strongly correlated with the concentration of SRFA-bound copper. The approach presented in this study can be used to generate in situ information concerning the nature of functional groups in humic substances engaged in interactions with metals ions. This

  4. Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA as a model region.

    Directory of Open Access Journals (Sweden)

    Marie-Laure Endale Ahanda

    Full Text Available THE SLA (swine leukocyte antigen, MHC: SLA genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3'-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs. Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1 are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered mi

  5. Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA) as a model region.

    Science.gov (United States)

    Endale Ahanda, Marie-Laure; Fritz, Eric R; Estellé, Jordi; Hu, Zhi-Liang; Madsen, Ole; Groenen, Martien A M; Beraldi, Dario; Kapetanovic, Ronan; Hume, David A; Rowland, Robert R R; Lunney, Joan K; Rogel-Gaillard, Claire; Reecy, James M; Giuffra, Elisabetta

    2012-01-01

    THE SLA (swine leukocyte antigen, MHC: SLA) genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3'-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs). Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1) are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation patterns.

  6. Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions

    Directory of Open Access Journals (Sweden)

    Merkulova Tatyana I

    2007-12-01

    Full Text Available Abstract Background Reliable transcription factor binding site (TFBS prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. Results To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-κB, ISGF3, IRF1, STAT1, obesity and lipid metabolism (PPAR, SREBP, HNF4, regulation of the steroidogenic (SF-1 and cell cycle (E2F genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA with a discriminant function of locally positioned dinucleotide (LPD frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together to sequences in the Eukaryotic Promoter Database (EPD. The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied

  7. Molecular Models of STAT5A Tetramers Complexed to DNA Predict Relative Genome-Wide Frequencies of the Spacing between the Two Dimer Binding Motifs of the Tetramer Binding Sites.

    Science.gov (United States)

    Sathyanarayana, Bangalore K; Li, Peng; Lin, Jian-Xin; Leonard, Warren J; Lee, Byungkook

    2016-01-01

    STAT proteins bind DNA as dimers and tetramers to control cellular development, differentiation, survival, and expansion. The tetramer binding sites are comprised of two dimer-binding sites repeated in tandem. The genome-wide distribution of the spacings between the dimer binding sites shows a distinctive, non-random pattern. Here, we report on estimating the feasibility of building possible molecular models of STAT5A tetramers bound to a DNA double helix with all possible spacings between the dimer binding sites. We found that the calculated feasibility estimates correlated well with the experimentally measured frequency of tetramer-binding sites. This suggests that the feasibility of forming the tetramer complex was a major factor in the evolution of this DNA sequence variation. PMID:27537504

  8. Urinary Tissue Inhibitor of Metalloproteinase-2 (TIMP-2) • Insulin-Like Growth Factor-Binding Protein 7 (IGFBP7) Predicts Adverse Outcome in Pediatric Acute Kidney Injury

    Science.gov (United States)

    Westhoff, Jens H.; Tönshoff, Burkhard; Waldherr, Sina; Pöschl, Johannes; Teufel, Ulrike; Westhoff, Timm H.; Fichtner, Alexander

    2015-01-01

    Background The G1 cell cycle inhibitors tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) have been identified as promising biomarkers for the prediction of adverse outcomes including renal replacement therapy (RRT) and mortality in critically ill adult patients who develop acute kidney injury (AKI). However, the prognostic value of urinary TIMP-2 and IGFBP7 in neonatal and pediatric AKI for adverse outcome has not been investigated yet. Methods The product of the urinary concentration of TIMP-2 and IGFBP7 ([TIMP-2]•[IGFBP7]) was assessed by a commercially available immunoassay (NephroCheck™) in a prospective cohort study in 133 subjects aged 0–18 years including 46 patients with established AKI according to pRIFLE criteria, 27 patients without AKI (non-AKI group I) and 60 apparently healthy neonates and children (non-AKI group II). AKI etiologies were: dehydration/hypovolemia (n = 7), hemodynamic instability (n = 7), perinatal asphyxia (n = 9), septic shock (n = 7), typical hemolytic-uremic syndrome (HUS; n = 5), interstitial nephritis (n = 5), vasculitis (n = 4), nephrotoxic injury (n = 1) and renal vein thrombosis (n = 1). Results When AKI patients were classified into pRIFLE criteria, 6/46 (13%) patients fulfilled the criteria for the category “Risk”, 13/46 (28%) for “Injury”, 26/46 (57%) for “Failure” and 1/46 (2%) for “Loss”. Patients in the “Failure” stage had a median 3.7-fold higher urinary [TIMP-2]•[IGFBP7] compared to non-AKI subjects (P<0.001). When analyzed for AKI etiology, highest [TIMP-2]•[IGFBP7] values were found in patients with septic shock (P<0.001 vs. non-AKI I+II). Receiver operating characteristic (ROC) curve analyses in the AKI group revealed good performance of [TIMP-2]•[IGFBP7] in predicting 30-day (area under the curve (AUC) 0.79; 95% CI, 0.61–0.97) and 3-month mortality (AUC 0.84; 95% CI, 0.67–0.99) and moderate performance in predicting RRT

  9. Urinary Tissue Inhibitor of Metalloproteinase-2 (TIMP-2 • Insulin-Like Growth Factor-Binding Protein 7 (IGFBP7 Predicts Adverse Outcome in Pediatric Acute Kidney Injury.

    Directory of Open Access Journals (Sweden)

    Jens H Westhoff

    Full Text Available The G1 cell cycle inhibitors tissue inhibitor of metalloproteinase-2 (TIMP-2 and insulin-like growth factor-binding protein 7 (IGFBP7 have been identified as promising biomarkers for the prediction of adverse outcomes including renal replacement therapy (RRT and mortality in critically ill adult patients who develop acute kidney injury (AKI. However, the prognostic value of urinary TIMP-2 and IGFBP7 in neonatal and pediatric AKI for adverse outcome has not been investigated yet.The product of the urinary concentration of TIMP-2 and IGFBP7 ([TIMP-2]•[IGFBP7] was assessed by a commercially available immunoassay (NephroCheck™ in a prospective cohort study in 133 subjects aged 0-18 years including 46 patients with established AKI according to pRIFLE criteria, 27 patients without AKI (non-AKI group I and 60 apparently healthy neonates and children (non-AKI group II. AKI etiologies were: dehydration/hypovolemia (n = 7, hemodynamic instability (n = 7, perinatal asphyxia (n = 9, septic shock (n = 7, typical hemolytic-uremic syndrome (HUS; n = 5, interstitial nephritis (n = 5, vasculitis (n = 4, nephrotoxic injury (n = 1 and renal vein thrombosis (n = 1.When AKI patients were classified into pRIFLE criteria, 6/46 (13% patients fulfilled the criteria for the category "Risk", 13/46 (28% for "Injury", 26/46 (57% for "Failure" and 1/46 (2% for "Loss". Patients in the "Failure" stage had a median 3.7-fold higher urinary [TIMP-2]•[IGFBP7] compared to non-AKI subjects (P<0.001. When analyzed for AKI etiology, highest [TIMP-2]•[IGFBP7] values were found in patients with septic shock (P<0.001 vs. non-AKI I+II. Receiver operating characteristic (ROC curve analyses in the AKI group revealed good performance of [TIMP-2]•[IGFBP7] in predicting 30-day (area under the curve (AUC 0.79; 95% CI, 0.61-0.97 and 3-month mortality (AUC 0.84; 95% CI, 0.67-0.99 and moderate performance in predicting RRT (AUC 0.67; 95% CI, 0.50-0.84.This study shows that urinary [TIMP

  10. Predictive Effects of Urinary Liver-Type Fatty Acid–Binding Protein for Deteriorating Renal Function and Incidence of Cardiovascular Disease in Type 2 Diabetic Patients Without Advanced Nephropathy

    OpenAIRE

    Araki, Shin-ichi; Haneda, Masakazu; Koya, Daisuke; Sugaya, Takeshi; Isshiki, Keiji; Kume, Shinji; Kashiwagi, Atsunori; Uzu, Takashi; Maegawa, Hiroshi

    2013-01-01

    OBJECTIVE To improve prognosis, it is important to predict the incidence of renal failure and cardiovascular disease in type 2 diabetic patients before the progression to advanced nephropathy. We investigated the predictive effects of urinary liver-type fatty acid–binding protein (L-FABP), which is associated with renal tubulointerstitial damage, in renal and cardiovascular prognosis. RESEARCH DESIGN AND METHODS Japanese type 2 diabetic patients (n = 618) with serum creatinine ≤1.0 mg/dL and ...

  11. Performance of the TPSS Functional on Predicting Core Level Binding Energies of Main Group Elements Containing Molecules: A Good Choice for Molecules Adsorbed on Metal Surfaces.

    Science.gov (United States)

    Pueyo Bellafont, Noèlia; Viñes, Francesc; Illas, Francesc

    2016-01-12

    Here we explored the performance of Hartree-Fock (HF), Perdew-Burke-Ernzerhof (PBE), and Tao-Perdew-Staroverov-Scuseria (TPSS) functionals in predicting core level 1s binding energies (BEs) and BE shifts (ΔBEs) for a large set of 68 molecules containing a wide variety of functional groups for main group elements B → F and considering up to 185 core levels. A statistical analysis comparing with X-ray photoelectron spectroscopy (XPS) experiments shows that BEs estimations are very accurate, TPSS exhibiting the best performance. Considering ΔBEs, the three methods yield very similar and excellent results, with mean absolute deviations of ∼0.25 eV. When considering relativistic effects, BEs deviations drop approaching experimental values. So, the largest mean percentage deviation is of 0.25% only. Linear trends among experimental and estimated values have been found, gaining offsets with respect to ideality. By adding relativistic effects to offsets, HF and TPSS methods underestimate experimental values by solely 0.11 and 0.05 eV, respectively, well within XPS chemical precision. TPSS is posed as an excellent choice for the characterization, by XPS, of molecules on metal solid substrates, given its suitability in describing metal substrates bonds and atomic and/or molecular orbitals.

  12. NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets

    DEFF Research Database (Denmark)

    Nielsen, Morten; Andreatta, Massimo

    2016-01-01

    Background: Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells.Results: Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining informat......Background: Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells.Results: Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining...

  13. Prediction of the Occurrence of the ADP-binding βαβ-fold in Proteins, Using an Amino Acid Sequence Fingerprint

    NARCIS (Netherlands)

    Wierenga, Rik K.; Terpstra, Peter; Hol, Wim G.J.

    1986-01-01

    An amino acid sequence "fingerprint” has been derived that can be used to test if a particular sequence will fold into a βαβ-unit with ADP-binding properties. It was deduced from a careful analysis of the known three-dimensional structures of ADP-binding βαβ-folds. This fingerprint is in fact a set

  14. A modern approach for epitope prediction: identification of foot-and-mouth disease virus peptides binding bovine leukocyte antigen (BoLA) class I molecules

    Science.gov (United States)

    Major histocompatibility complex (MHC) class I molecules regulate adaptive immune responses through the presentation of antigenic peptides to CD8positive T-cells. Polymorphisms in the peptide binding region of class I molecules determine peptide binding affinity and stability during antigen presenta...

  15. Detection of C3d-Binding Donor-Specific Anti-HLA Antibodies at Diagnosis of Humoral Rejection Predicts Renal Graft Loss

    Science.gov (United States)

    Sicard, Antoine; Ducreux, Stéphanie; Rabeyrin, Maud; Couzi, Lionel; McGregor, Brigitte; Badet, Lionel; Scoazec, Jean Yves; Bachelet, Thomas; Lepreux, Sébastien; Visentin, Jonathan; Merville, Pierre; Fremeaux-Bacchi, Véronique; Morelon, Emmanuel; Taupin, Jean-Luc; Dubois, Valérie

    2015-01-01

    Antibody-mediated rejection (AMR) is a major cause of kidney graft loss, yet assessment of individual risk at diagnosis is impeded by the lack of a reliable prognosis assay. Here, we tested whether the capacity of anti-HLA antibodies to bind complement components allows accurate risk stratification at the time of AMR diagnosis. Among 938 kidney transplant recipients for whom a graft biopsy was performed between 2004 and 2012 at the Lyon University Hospitals, 69 fulfilled the diagnosis criteria for AMR and were enrolled. Sera banked at the time of the biopsy were screened for the presence of donor-specific anti-HLA antibodies (DSAs) and their ability to bind C1q and C3d using flow bead assays. In contrast with C4d graft deposition, the presence of C3d-binding DSA was associated with a higher risk of graft loss (P<0.001). Despite similar trend, the difference did not reach significance with a C1q-binding assay (P=0.06). The prognostic value of a C3d-binding assay was further confirmed in an independent cohort of 39 patients with AMR (P=0.04). Patients with C3d-binding antibodies had worse eGFR and higher DSA mean fluorescence intensity. In a multivariate analysis, only eGFR<30 ml/min per 1.73 m2 (hazard ratio [HR], 3.56; 95% confidence interval [CI], 1.46 to 8.70; P=0.005) and the presence of circulating C3d-binding DSA (HR, 2.80; 95% CI, 1.12 to 6.95; P=0.03) were independent predictors for allograft loss at AMR diagnosis. We conclude that assessment of the C3d-binding capacity of DSA at the time of AMR diagnosis allows for identification of patients at risk for allograft loss. PMID:25125383

  16. The 3D structure of the defense-related rice protein Pir7b predicted by homology modeling and ligand binding studies.

    Science.gov (United States)

    Luo, Quan; Han, Wei-Wei; Zhou, Yi-Han; Yao, Yuan; Li, Ze-Sheng

    2008-07-01

    To better understand the ligand-binding mechanism of protein Pir7b, important part in detoxification of a pathogen-derived compound against Pyricularia oryzae, a 3D structure model of protein Pir7b was constructed based on the structure of the template SABP2. Three substrates were docking to this protein, two of them were proved to be active, and some critical residues are identified, which had not been confirmed by the experiments. His87 and Leu17 considered as 'oxyanion hole' contribute to initiating the Ser86 nucleophilic attack. Gln187 and Asp139 can form hydrogen bonds with the anilid group to maintain the active binding orientation with the substrates. The docking model can well interpret the specificity of protein Pir7b towards the anilid moiety of the substrates and provide valuable structure information about the ligand binding to protein Pir7b. PMID:18449577

  17. A modern approach for epitope prediction: identification of foot-and-mouth disease virus peptides binding bovine leukocyte antigen (BoLA) class I molecules

    DEFF Research Database (Denmark)

    Pandya, Mital; Rasmussen, Michael; Hansen, Andreas;

    2015-01-01

    pathogens, such as foot-and-mouth disease virus (FMDV). Six synthetic BoLA class I (BoLA-I) molecules were produced, and the peptide binding motif was generated for five of the six molecules using a combined approach of positional scanning combinatorial peptide libraries (PSCPLs) and neural network...

  18. Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA.

    Science.gov (United States)

    Carra, Claudio; Cucinotta, Francis A

    2012-06-01

    The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation. PMID:22116609

  19. Molecular modeling of human APOBEC3G to predict the binding modes of the inhibitor compounds IMB26 and IMB35

    Directory of Open Access Journals (Sweden)

    Zhixin Zhang

    2013-07-01

    Full Text Available APOBEC3G(A3G is a host cytidine deaminase that incorporates into HIV-1 virions and efficiently inhibits viral replication. The virally encoded protein Vif binds to A3G and induces its degradation, thereby counteracting the antiviral activity of A3G. Vif-mediated A3G degradation clearly represents a potential target for anti-HIV drug development. Currently, there is an urgent need for understanding the three dimensional structure of full-length A3G. In this work, we use a homology modeling approach to propose a structure for A3G based on the crystal structure of APOBEC2 (APO2 and the catalytic domain structure of A3G. Two compounds, IMB26 and IMB35, which have been shown to bind to A3G and block degradation by Vif, were docked into the A3G model and the binding modes were generated for further analysis. The results may be used to design or optimize molecules targeting Vif–A3G interaction, and lead to the development of novel anti-HIV drugs.

  20. MetaGeneAnnotator: Detecting Species-Specific Patterns of Ribosomal Binding Site for Precise Gene Prediction in Anonymous Prokaryotic and Phage Genomes

    OpenAIRE

    Noguchi, Hideki; Taniguchi, Takeaki; Itoh, Takehiko

    2008-01-01

    Recent advances in DNA sequencers are accelerating genome sequencing, especially in microbes, and complete and draft genomes from various species have been sequenced in rapid succession. Here, we present a comprehensive gene prediction tool, the MetaGeneAnnotator (MGA), which precisely predicts all kinds of prokaryotic genes from a single or a set of anonymous genomic sequences having a variety of lengths. The MGA integrates statistical models of prophage genes, in addition to those of bacter...

  1. Molecular Cloning, Expression Pattern, and 3D Structural Prediction of the Cold Inducible RNA - Binding Protein (CIRP) in Japanese Flounder (Paralichthys olivaceus)

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao; WANG Zhigang; ZHANG Quanqi; GAO Jinning; MA Liman; LI Zan; WANG Wenji; WANG Zhongkai; YU Haiyang; QI Jie; WANG Xubo

    2015-01-01

    Cold-inducible RNA-binding protein (CIRP) is a kind of RNA binding proteins that plays important roles in many physiological processes. The CIRP has been widely studied in mammals and amphibians since it was first cloned from mammals. On the contrary, there are little reports in teleosts. In this study, the PoCIRP gene of the Japanese flounder was cloned and sequenced. The genomic sequence consists of seven exons and six introns. The putative PoCIRP protein of flounder was 198 amino acid residues long containing the RNA recognition motif (RRM). Phylogenetic analysis showed that the flounder PoCIRP is highly conserved with other teleost CIRPs. The 5’ flanking sequence was cloned by genome walking and many transcription factor binding sites were iden-tified. There is a CpGs region located in promoter and exon I region and the methylation state is low. Quantitative real-time PCR analysis uncovered that PoCIRP gene was widely expressed in adult tissues with the highest expression level in the ovary. The mRNA of the PoCIRP was maternally deposited and the expression level of the gene was regulated up during the gastrula and neu-rula stages. In order to gain the information how the protein interacts with mRNA, we performed the modeling of the 3D structure of the flounder PoCIRP. The results showed a cleft existing the surface of the molecular. Taken together, the results indicate that the CIRP is a multifunctional molecular in teleosts and the findings about the structure provide valuable information for understanding the basis of this protein’s function.

  2. Molecular cloning, expression pattern, and 3D structural prediction of the cold inducible RNA-binding protein (CIRP) in Japanese flounder ( Paralichthys olivaceus)

    Science.gov (United States)

    Yang, Xiao; Gao, Jinning; Ma, Liman; Li, Zan; Wang, Wenji; Wang, Zhongkai; Yu, Haiyang; Qi, Jie; Wang, Xubo; Wang, Zhigang; Zhang, Quanqi

    2015-02-01

    Cold-inducible RNA-binding protein (CIRP) is a kind of RNA binding proteins that plays important roles in many physiological processes. The CIRP has been widely studied in mammals and amphibians since it was first cloned from mammals. On the contrary, there are little reports in teleosts. In this study, the Po CIRP gene of the Japanese flounder was cloned and sequenced. The genomic sequence consists of seven exons and six introns. The putative PoCIRP protein of flounder was 198 amino acid residues long containing the RNA recognition motif (RRM). Phylogenetic analysis showed that the flounder PoCIRP is highly conserved with other teleost CIRPs. The 5' flanking sequence was cloned by genome walking and many transcription factor binding sites were identified. There is a CpGs region located in promoter and exon I region and the methylation state is low. Quantitative real-time PCR analysis uncovered that Po CIRP gene was widely expressed in adult tissues with the highest expression level in the ovary. The mRNA of the Po CIRP was maternally deposited and the expression level of the gene was regulated up during the gastrula and neurula stages. In order to gain the information how the protein interacts with mRNA, we performed the modeling of the 3D structure of the flounder PoCIRP. The results showed a cleft existing the surface of the molecular. Taken together, the results indicate that the CIRP is a multifunctional molecular in teleosts and the findings about the structure provide valuable information for understanding the basis of this protein's function.

  3. In Silico Prediction of Estrogen Receptor Subtype Binding Affinity and Selectivity Using Statistical Methods and Molecular Docking with 2-Arylnaphthalenes and 2-Arylquinolines

    Directory of Open Access Journals (Sweden)

    Yonghua Wang

    2010-09-01

    Full Text Available Over the years development of selective estrogen receptor (ER ligands has been of great concern to researchers involved in the chemistry and pharmacology of anticancer drugs, resulting in numerous synthesized selective ER subtype inhibitors. In this work, a data set of 82 ER ligands with ERα and ERβ inhibitory activities was built, and quantitative structure-activity relationship (QSAR methods based on the two linear (multiple linear regression, MLR, partial least squares regression, PLSR and a nonlinear statistical method (Bayesian regularized neural network, BRNN were applied to investigate the potential relationship of molecular structural features related to the activity and selectivity of these ligands. For ERα and ERβ, the performances of the MLR and PLSR models are superior to the BRNN model, giving more reasonable statistical properties (ERα: for MLR, Rtr2 = 0.72, Qte2 = 0.63; for PLSR, Rtr2 = 0.92, Qte2 = 0.84. ERβ: for MLR, Rtr2 = 0.75, Qte2 = 0.75; for PLSR, Rtr2 = 0.98, Qte2 = 0.80. The MLR method is also more powerful than other two methods for generating the subtype selectivity models, resulting in Rtr2 = 0.74 and Qte2 = 0.80. In addition, the molecular docking method was also used to explore the possible binding modes of the ligands and a relationship between the 3D-binding modes and the 2D-molecular structural features of ligands was further explored. The results show that the binding affinity strength for both ERα and ERβ is more correlated with the atom fragment type, polarity, electronegativites and hydrophobicity. The substitutent in position 8 of the naphthalene or the quinoline plane and the space orientation of these two planes contribute the most to the subtype selectivity on the basis of similar hydrogen bond interactions between binding ligands and both ER subtypes. The QSAR models built together with the docking procedure should be of great advantage for screening and designing ER ligands with improved affinity

  4. Binding Procurement

    Science.gov (United States)

    Rao, Gopalakrishna M.; Vaidyanathan, Hari

    2007-01-01

    This viewgraph presentation reviews the use of the binding procurement process in purchasing Aerospace Flight Battery Systems. NASA Engineering and Safety Center (NESC) requested NASA Aerospace Flight Battery Systems Working Group to develop a set of guideline requirements document for Binding Procurement Contracts.

  5. Promiscuous prediction and conservancy analysis of CTL binding epitopes of HCV 3a viral proteome from Punjab Pakistan: an In Silico Approach

    Directory of Open Access Journals (Sweden)

    Idrees Muhammad

    2011-02-01

    Full Text Available Abstract Background HCV is a positive sense RNA virus affecting approximately 180 million people world wide and about 10 million Pakistani populations. HCV genotype 3a is the major cause of infection in Pakistani population. One of the major problems of HCV infection especially in the developing countries that limits the limits the antiviral therapy is the long term treatment, high dosage and side effects. Studies of antigenic epitopes of viral sequences of a specific origin can provide an effective way to overcome the mutation rate and to determine the promiscuous binders to be used for epitope based subunit vaccine design. An in silico approach was applied for the analysis of entire HCV proteome of Pakistani origin, aimed to identify the viral epitopes and their conservancy in HCV genotypes 1, 2 and 3 of diverse origin. Results Immunoinformatic tools were applied for the predictive analysis of HCV 3a antigenic epitopes of Pakistani origin. All the predicted epitopes were then subjected for their conservancy analysis in HCV genotypes 1, 2 and 3 of diverse origin (worldwide. Using freely available web servers, 150 MHC II epitopes were predicted as promiscuous binders against 51 subjected alleles. E2 protein represented the 20% of all the predicted MHC II epitopes. 75.33% of the predicted MHC II epitopes were (77-100% conserve in genotype 3; 47.33% and 40.66% in genotype 1 and 2 respectively. 69 MHC I epitopes were predicted as promiscuous binders against 47 subjected alleles. NS4b represented 26% of all the MHC I predicted epitopes. Significantly higher epitope conservancy was represented by genotype 3 i.e. 78.26% and 21.05% for genotype 1 and 2. Conclusions The study revealed comprehensive catalogue of potential HCV derived CTL epitopes from viral proteome of Pakistan origin. A considerable number of predicted epitopes were found to be conserved in different HCV genotype. However, the number of conserved epitopes in HCV genotype 3 was

  6. The Binding Mode Prediction and Similar Ligand Potency in the Active Site of Vitamin D Receptor with QM/MM Interaction, MESP, and MD Simulation.

    Science.gov (United States)

    Selvaraman, Nagamani; Selvam, Saravana Kumar; Muthusamy, Karthikeyan

    2016-08-01

    Non-secosteroidal ligands are well-known vitamin D receptor (VDR) agonists. In this study, we described a combined QM/MM to define the protein-ligand interaction energy a strong positive correlation in both QM-MM interaction energy and binding free energy against the biological activity. The molecular dynamics simulation study was performed, and specific interactions were extensively studied. The molecular docking results and surface analysis shed light on steric and electrostatic complementarities of these non-secosteroidal ligands to VDR. Finally, the drug likeness properties were also calculated and found within the acceptable range. The results show that bulky group substitutions in side chain decrease the VDR activity, whereas a small substitution increased it. Functional analyses of H393A and H301A mutations substantiate their roles in the VDR agonistic and antagonistic activities. Apart from the His393 and His301, two other amino acids in the hinge region viz. Ser233 and Arg270 acted as an electron donor/acceptor specific to the agonist in the distinct ligand potency. The results from this study disclose the binding mechanism of VDR agonists and structural modifications required to improve the selectivity.

  7. The Binding Mode Prediction and Similar Ligand Potency in the Active Site of Vitamin D Receptor with QM/MM Interaction, MESP, and MD Simulation.

    Science.gov (United States)

    Selvaraman, Nagamani; Selvam, Saravana Kumar; Muthusamy, Karthikeyan

    2016-08-01

    Non-secosteroidal ligands are well-known vitamin D receptor (VDR) agonists. In this study, we described a combined QM/MM to define the protein-ligand interaction energy a strong positive correlation in both QM-MM interaction energy and binding free energy against the biological activity. The molecular dynamics simulation study was performed, and specific interactions were extensively studied. The molecular docking results and surface analysis shed light on steric and electrostatic complementarities of these non-secosteroidal ligands to VDR. Finally, the drug likeness properties were also calculated and found within the acceptable range. The results show that bulky group substitutions in side chain decrease the VDR activity, whereas a small substitution increased it. Functional analyses of H393A and H301A mutations substantiate their roles in the VDR agonistic and antagonistic activities. Apart from the His393 and His301, two other amino acids in the hinge region viz. Ser233 and Arg270 acted as an electron donor/acceptor specific to the agonist in the distinct ligand potency. The results from this study disclose the binding mechanism of VDR agonists and structural modifications required to improve the selectivity. PMID:26945790

  8. Peptide-binding motif prediction by using phage display library for SasaUBA*0301, a resistance haplotype of MHC class I molecule from Atlantic Salmon (Salmo salar)

    DEFF Research Database (Denmark)

    Zhao, Heng; Hermsen, Trudi; Stet, Rene J M;

    2008-01-01

    -terminus. Meanwhile, phage display peptide library encoding random 12mer peptides was also screened against beta(2)m/SasaUBA*0301. Eighty-five percentages of the corresponding peptides have an enrichment of leucine, methionine, valine, or isoleucine at the C-terminus. We predict that this particular allele of Salmon...

  9. Candidate SNP Markers of Chronopathologies Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

    Directory of Open Access Journals (Sweden)

    Petr Ponomarenko

    2016-01-01

    Full Text Available Variations in human genome (e.g., single nucleotide polymorphisms, SNPs may be associated with hereditary diseases, their complications, comorbidities, and drug responses. Using Web service SNP_TATA_Comparator presented in our previous paper, here we analyzed immediate surroundings of known SNP markers of diseases and identified several candidate SNP markers that can significantly change the affinity of TATA-binding protein for human gene promoters, with circadian consequences. For example, rs572527200 may be related to asthma, where symptoms are circadian (worse at night, and rs367732974 may be associated with heart attacks that are characterized by a circadian preference (early morning. By the same method, we analyzed the 90 bp proximal promoter region of each protein-coding transcript of each human gene of the circadian clock core. This analysis yielded 53 candidate SNP markers, such as rs181985043 (susceptibility to acute Q fever in male patients, rs192518038 (higher risk of a heart attack in patients with diabetes, and rs374778785 (emphysema and lung cancer in smokers. If they are properly validated according to clinical standards, these candidate SNP markers may turn out to be useful for physicians (to select optimal treatment for each patient and for the general population (to choose a lifestyle preventing possible circadian complications of diseases.

  10. Candidate SNP Markers of Chronopathologies Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

    Science.gov (United States)

    Ponomarenko, Petr; Rasskazov, Dmitry; Suslov, Valentin; Sharypova, Ekaterina; Savinkova, Ludmila; Podkolodnaya, Olga; Podkolodny, Nikolay L.; Tverdokhleb, Natalya N.; Chadaeva, Irina; Kolchanov, Nikolay

    2016-01-01

    Variations in human genome (e.g., single nucleotide polymorphisms, SNPs) may be associated with hereditary diseases, their complications, comorbidities, and drug responses. Using Web service SNP_TATA_Comparator presented in our previous paper, here we analyzed immediate surroundings of known SNP markers of diseases and identified several candidate SNP markers that can significantly change the affinity of TATA-binding protein for human gene promoters, with circadian consequences. For example, rs572527200 may be related to asthma, where symptoms are circadian (worse at night), and rs367732974 may be associated with heart attacks that are characterized by a circadian preference (early morning). By the same method, we analyzed the 90 bp proximal promoter region of each protein-coding transcript of each human gene of the circadian clock core. This analysis yielded 53 candidate SNP markers, such as rs181985043 (susceptibility to acute Q fever in male patients), rs192518038 (higher risk of a heart attack in patients with diabetes), and rs374778785 (emphysema and lung cancer in smokers). If they are properly validated according to clinical standards, these candidate SNP markers may turn out to be useful for physicians (to select optimal treatment for each patient) and for the general population (to choose a lifestyle preventing possible circadian complications of diseases).

  11. Increase in skin autofluorescence and release of heart-type fatty acid binding protein in plasma predicts mortality of hemodialysis patients.

    Science.gov (United States)

    Arsov, Stefan; Trajceska, Lada; van Oeveren, Wim; Smit, Andries J; Dzekova, Pavlina; Stegmayr, Bernd; Sikole, Aleksandar; Rakhorst, Gerhard; Graaff, Reindert

    2013-07-01

    Advanced glycation end-products (AGEs) are uremic toxins that accumulate progressively in hemodialysis (HD) patients. The aim of this study was to assess the 1-year increase in skin autofluorescence (ΔAF), a measure of AGEs accumulation and plasma markers, as predictors of mortality in HD patients. One hundred sixty-nine HD patients were enrolled in this study. Skin autofluorescence was measured twice, 1 year apart using an AGE Reader (DiagnOptics Technologies BV, Groningen, The Netherlands). Besides routine blood chemistry, additional plasma markers including superoxide dismutase, myeloperoxydase, intercellular adhesion molecule 1 (ICAM-1), C-reactive protein (hs-CRP), heart-type fatty acid binding protein (H-FABP), and von Willebrand factor were measured at baseline. The mortality of HD patients was followed for 36 months. Skin autofluorescence values of the HD patients at the two time points were significantly higher (P < 0.001) than those of healthy subjects of the same age. Mean 1-year ΔAF of HD patients was 0.16 ± 0.06, which was around seven- to ninefold higher than 1-year ΔAF in healthy subjects. Multivariate Cox regression showed that age, hypertension, 1-year ΔAF, hs-CRP, ICAM-1, and H-FABP were independent predictors of overall mortality. Hypertension, 1-year ΔAF, hs-CRP, and H-FABP were also independent predictors of cardiovascular mortality. One-year ΔAF and plasma H-FABP, used separately and in combination, are strong predictors of overall and cardiovascular mortality in HD patients.

  12. Increase in skin autofluorescence and release of heart-type fatty acid binding protein in plasma predicts mortality of hemodialysis patients.

    Science.gov (United States)

    Arsov, Stefan; Trajceska, Lada; van Oeveren, Wim; Smit, Andries J; Dzekova, Pavlina; Stegmayr, Bernd; Sikole, Aleksandar; Rakhorst, Gerhard; Graaff, Reindert

    2013-07-01

    Advanced glycation end-products (AGEs) are uremic toxins that accumulate progressively in hemodialysis (HD) patients. The aim of this study was to assess the 1-year increase in skin autofluorescence (ΔAF), a measure of AGEs accumulation and plasma markers, as predictors of mortality in HD patients. One hundred sixty-nine HD patients were enrolled in this study. Skin autofluorescence was measured twice, 1 year apart using an AGE Reader (DiagnOptics Technologies BV, Groningen, The Netherlands). Besides routine blood chemistry, additional plasma markers including superoxide dismutase, myeloperoxydase, intercellular adhesion molecule 1 (ICAM-1), C-reactive protein (hs-CRP), heart-type fatty acid binding protein (H-FABP), and von Willebrand factor were measured at baseline. The mortality of HD patients was followed for 36 months. Skin autofluorescence values of the HD patients at the two time points were significantly higher (P < 0.001) than those of healthy subjects of the same age. Mean 1-year ΔAF of HD patients was 0.16 ± 0.06, which was around seven- to ninefold higher than 1-year ΔAF in healthy subjects. Multivariate Cox regression showed that age, hypertension, 1-year ΔAF, hs-CRP, ICAM-1, and H-FABP were independent predictors of overall mortality. Hypertension, 1-year ΔAF, hs-CRP, and H-FABP were also independent predictors of cardiovascular mortality. One-year ΔAF and plasma H-FABP, used separately and in combination, are strong predictors of overall and cardiovascular mortality in HD patients. PMID:23635017

  13. Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

    Science.gov (United States)

    Ponomarenko, Mikhail P.; Arkova, Olga; Rasskazov, Dmitry; Ponomarenko, Petr; Savinkova, Ludmila; Kolchanov, Nikolay

    2016-01-01

    Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine. PMID:27092142

  14. Computer-assisted prediction of HLA-DR binding and experimental analysis for human promiscuous Th1-cell peptides in the 24 kDa secreted lipoprotein (LppX) of Mycobacterium tuberculosis.

    Science.gov (United States)

    Al-Attiyah, R; Mustafa, A S

    2004-01-01

    The secreted 24 kDa lipoprotein (LppX) is an antigen that is specific for Mycobacterium tuberculosis complex and M. leprae. The present study was carried out to identify the promiscuous T helper 1 (Th1)-cell epitopes of the M. tuberculosis LppX (MT24, Rv2945c) antigen by using 15 overlapping synthetic peptides (25 mers overlapping by 10 residues) covering the sequence of the complete protein. The analysis of Rv2945c sequence for binding to 51 alleles of nine serologically defined HLA-DR molecules, by using a virtual matrix-based prediction program (propred), showed that eight of the 15 peptides of Rv2945c were predicted to bind promiscuously to >/=10 alleles from more than or equal to three serologically defined HLA-DR molecules. The Th1-cell reactivity of all the peptides was assessed in antigen-induced proliferation and interferon-gamma (IFN-gamma)-secretion assays with peripheral blood mononuclear cells (PBMCs) from 37 bacille Calmette-Guérin (BCG)-vaccinated healthy subjects. The results showed that 17 of the 37 donors, which represented an HLA-DR-heterogeneous group, responded to one or more peptides of Rv2945c in the Th1-cell assays. Although each peptide stimulated PBMCs from one or more donors in the above assays, the best positive responses (12/17 (71%) responders) were observed with the peptide p14 (aa 196-220). This suggested a highly promiscuous presentation of p14 to Th1 cells. In addition, the sequence of p14 is completely identical among the LppX of M. tuberculosis, M. bovis and M. leprae, which further supports the usefulness of Rv2945c and p14 in the subunit vaccine design against both tuberculosis and leprosy.

  15. Diagnostic and Predictive Levels of Calcium-binding Protein A8 and Tumor Necrosis Factor Receptor-associated Factor 6 in Sepsis-associated Encephalopathy: A Prospective Observational Study

    Institute of Scientific and Technical Information of China (English)

    Li-Na Zhang; Xiao-Hong Wang; Long Wu; Li Huang; Chun-Guang Zhao; Qian-Yi Peng; Yu-Hang Ai

    2016-01-01

    Background:Despite its high prevalence,morbidity,and mortality,sepsis-associated encephalopathy (SAE) is still poorly understood.The aim of this prospective and observational study was to investigate the clinical significance of calcium-binding protein A8 (S100A8) in serum and tumor necrosis factor receptor-associated factor 6 (TRAF6) in peripheral blood mononuclear cells (PBMCs) in diagnosing SAE and predicting its prognosis.Methods:Data of septic patients were collected within 24 h after Intensive Care Unit admission from July 2014 to March 2015.Healthy medical personnel served as the control group.SAE was defined as cerebral dysfunction in the presence of sepsis that fulfilled the exclusion criteria.The biochemical indicators,Glasgow Coma Scale,Acute Physiology and Chronic Health Evaluation score Ⅱ,TRAF6 in PBMC,serum S 100A8,S 100β,and neuron-specific enolase were evaluated in SAE patients afresh.TRAF6 and S 100A8 were also measured in the control group.Results:Of the 57 enrolled patients,29 were diagnosed with SAE.The S 100A8 and TRAF6 concentrations in SAE patients were both significantly higher than that in no-encephalopathy (NE) patients,and higher in NE than that in controls (3.74 ± 3.13 vs.1.08 ± 0.75 vs.0.37 ± 0.14 ng/ml,P < 0.01;3.18 ± 1.55 vs.1.02 ± 0.63 vs.0.47 ± 0.10,P < 0.01).S 100A8 levels of 1.93 ng/ml were diagnostic of SAE with 92.90% specificity and 69.00% sensitivity in the receiver operating characteristic (ROC) curve,and the area under the curve was 0.86 (95% confidence interval [CI]:0.76-0.95).TRAF6-relative levels of 1.44 were diagnostic of SAE with 85.70% specificity and 86.20% sensitivity,and the area under the curve was 0.94 (95% CI:0.88-0.99).In addition,S 100A8 levels of 2.41 ng/ml predicted 28-day mortality of SAE with 90.00% specificity and 73.70% sensitivity in the ROC curve,and the area under the curve was 0.88.TRAF6 relative levels of 2.94 predicted 28-day mortality of SAE with 80.00% specificity

  16. Solute-vacancy binding in aluminum

    International Nuclear Information System (INIS)

    Previous efforts to understand solute-vacancy binding in aluminum alloys have been hampered by a scarcity of reliable, quantitative experimental measurements. Here, we report a large database of solute-vacancy binding energies determined from first-principles density functional calculations. The calculated binding energies agree well with accurate measurements where available, and provide an accurate predictor of solute-vacancy binding in other systems. We find: (i) some common solutes in commercial Al alloys (e.g., Cu and Mg) possess either very weak (Cu), or even repulsive (Mg), binding energies. Hence, we assert that some previously reported large binding energies for these solutes are erroneous. (ii) Large binding energies are found for Sn, Cd and In, confirming the proposed mechanism for the reduced natural aging in Al-Cu alloys containing microalloying additions of these solutes. (iii) In addition, we predict that similar reduction in natural aging should occur with additions of Si, Ge and Au. (iv) Even larger binding energies are found for other solutes (e.g., Pb, Bi, Sr, Ba), but these solutes possess essentially no solubility in Al. (v) We have explored the physical effects controlling solute-vacancy binding in Al. We find that there is a strong correlation between binding energy and solute size, with larger solute atoms possessing a stronger binding with vacancies. (vi) Most transition-metal 3d solutes do not bind strongly with vacancies, and some are even energetically strongly repelled from vacancies, particularly for the early 3d solutes, Ti and V

  17. Analyzing binding data.

    Science.gov (United States)

    Motulsky, Harvey J; Neubig, Richard R

    2010-07-01

    Measuring the rate and extent of radioligand binding provides information on the number of binding sites, and their affinity and accessibility of these binding sites for various drugs. This unit explains how to design and analyze such experiments.

  18. Total iron binding capacity

    Science.gov (United States)

    ... page: //medlineplus.gov/ency/article/003489.htm Total iron binding capacity To use the sharing features on this page, please enable JavaScript. Total iron binding capacity (TIBC) is a blood test to ...

  19. Plant Hormone Binding Sites

    OpenAIRE

    Napier, Richard

    2004-01-01

    • Aims Receptors for plant hormones are becoming identified with increasing rapidity, although a frustrating number remain unknown. There have also been many more hormone‐binding proteins described than receptors. This Botanical Briefing summarizes what has been discovered about hormone binding sites, their discovery and descriptions, and will not dwell on receptor functions or activities except where these are relevant to understand binding.

  20. Analysis of binding heterogeneity.

    NARCIS (Netherlands)

    Nederlof, M.M.

    1992-01-01

    Binding heterogeneity, due to different functional groups on a reactive surface, plays an important role in the binding of small molecules or ions to many adsorbents, both in industrial processes and in natural environments. The binding heterogeneity is described by a distribution of affinity consta

  1. Analyzing radioligand binding data.

    Science.gov (United States)

    Motulsky, Harvey; Neubig, Richard

    2002-08-01

    Radioligand binding experiments are easy to perform, and provide useful data in many fields. They can be used to study receptor regulation, discover new drugs by screening for compounds that compete with high affinity for radioligand binding to a particular receptor, investigate receptor localization in different organs or regions using autoradiography, categorize receptor subtypes, and probe mechanisms of receptor signaling, via measurements of agonist binding and its regulation by ions, nucleotides, and other allosteric modulators. This unit reviews the theory of receptor binding and explains how to analyze experimental data. Since binding data are usually best analyzed using nonlinear regression, this unit also explains the principles of curve fitting with nonlinear regression.

  2. Metal binding stoichiometry and isotherm choice in biosorption

    Energy Technology Data Exchange (ETDEWEB)

    Schiewer, S.; Wong, M.H.

    1999-11-01

    Seaweeds that possess a high metal binding capacity may be used as biosorbents for the removal of toxic heavy metals from wastewater. The binding of Cu and Ni by three brown algae (Sargassum, Colpomenia, Petalonia) and one green alga (Ulva) was investigated at pH 4.0 and pH 3.0. The greater binding strength of Cu is reflected in a binding constant that is about 10 times as high as that of Ni. The extent of metal binding followed the order Petalonia {approximately} Sargassum > Colpomenia > Ulva. This was caused by a decreasing number of binding sites and by much lower metal binding constants for Ulva as compared to the brown algae. Three different stoichiometric assumptions are compared for describing the metal binding, which assume either that each metal ion M binds to one binding site B forming a BM complex or that a divalent metal ion M binds to two monovalent sites B forming BM{sub 0.5} or B{sub 2}M complexes, respectively. Stoichiometry plots are proposed as tools to discern the relevant binding stoichiometry. The pH effect in metal binding and the change in proton binding were well predicted for the B{sub 2}M or BM{sub 0.5} stoichiometries with the former being better for Cu and the latter preferable for Ni. Overall, the BM{sub 0.5} model is recommended because it avoids iterations.

  3. Prediction of the outcome of growth hormone provocative testing in short children by measurement of serum levels of insulin-like growth factor I and insulin-like growth factor binding protein 3

    DEFF Research Database (Denmark)

    Juul, A; Skakkebaek, N E

    1997-01-01

    Serum levels of insulin-like growth factor I (IGF-I) and insulin-like growth factor binding protein 3 (IGFBP-3) reflect the secretion of endogenous growth hormone (GH) in healthy children and exhibit little diurnal variation, which makes them potential candidates for screening of GH deficiency (GHD......). We evaluated serum IGF-I and IGFBP-3 levels in relation to the outcome of GH provocative testing in 203 children and adolescents (111 boys and 92 girls) in whom GHD was suspected. A total of 1030 children served as control subjects. In children less than 10 years of age, IGF-I levels were below...

  4. Strong binding and shrinkage of single and double kbar~nuclear systems (K^-pp, K^-ppn, K^-K^-p and K^-K^-pp) predicted by Faddeev-Yakubovsky calculations

    CERN Document Server

    Maeda, Shuji; Yamazaki, Toshimitsu

    2013-01-01

    Non-relativistic Faddeev and Faddeev-Yakubovsky calculations were made for K^-pp, K^-ppn, K^-K^-p and K^-K^-pp kaonic nuclear clusters, where the quasi bound states were treated as bound states by employing real separable potential models for the K^-K^- and the K^-nucleon interactions as well as for the nucleon-nucleon interaction. The binding energies and spatial shrinkages of these states, obtained for various values of the KbarN interaction, were found to increase rapidly with the KbarN interaction strength. Their behaviors are shown in a reference diagram to overview possible changes by varying the KbarN interaction in the dense nuclear medium. Using the Lambda(1405) ansatz with a PDG mass of 1405 MeV/c^2 for K^-p, the following ground-state binding energies together with the wavefunctions were obtained: 51.5 MeV (K^-pp), 69 MeV (K^-ppn), 30.4 MeV (K^-K^-p) and 93 MeV (K^-K^-pp), which are in good agreement with previous results of variational calculation based on the Akaishi-Yamazaki coupled-channel pote...

  5. Python bindings for libcloudph++

    OpenAIRE

    Jarecka, Dorota; Arabas, Sylwester; Del Vento, Davide

    2015-01-01

    This technical note introduces the Python bindings for libcloudph++. The libcloudph++ is a C++ library of algorithms for representing atmospheric cloud microphysics in numerical models. The bindings expose the complete functionality of the library to the Python users. The bindings are implemented using the Boost.Python C++ library and use NumPy arrays. This note includes listings with Python scripts exemplifying the use of selected library components. An example solution for using the Python ...

  6. DNS & Bind Cookbook

    CERN Document Server

    Liu, Cricket

    2011-01-01

    The DNS & BIND Cookbook presents solutions to the many problems faced by network administrators responsible for a name server. Following O'Reilly's popular problem-and-solution cookbook format, this title is an indispensable companion to DNS & BIND, 4th Edition, the definitive guide to the critical task of name server administration. The cookbook contains dozens of code recipes showing solutions to everyday problems, ranging from simple questions, like, "How do I get BIND?" to more advanced topics like providing name service for IPv6 addresses. It's full of BIND configuration files that yo

  7. Python bindings for libcloudph++

    CERN Document Server

    Jarecka, Dorota; Del Vento, Davide

    2015-01-01

    This technical note introduces the Python bindings for libcloudph++. The libcloudph++ is a C++ library of algorithms for representing atmospheric cloud microphysics in numerical models. The bindings expose the complete functionality of the library to the Python users. The bindings are implemented using the Boost.Python C++ library and use NumPy arrays. This note includes listings with Python scripts exemplifying the use of selected library components. An example solution for using the Python bindings to access libcloudph++ from Fortran is presented.

  8. Melanin-binding radiopharmaceuticals

    Energy Technology Data Exchange (ETDEWEB)

    Packer, S; Fairchild, R G; Watts, K P; Greenberg, D; Hannon, S J

    1980-01-01

    The scope of this paper is limited to an analysis of the factors that are important to the relationship of radiopharmaceuticals to melanin. While the authors do not attempt to deal with differences between melanin-binding vs. melanoma-binding, a notable variance is assumed. (PSB)

  9. DNS BIND Server Configuration

    Directory of Open Access Journals (Sweden)

    Radu MARSANU

    2011-01-01

    Full Text Available After a brief presentation of the DNS and BIND standard for Unix platforms, the paper presents an application which has a principal objective, the configuring of the DNS BIND 9 server. The general objectives of the application are presented, follow by the description of the details of designing the program.

  10. Prediction of binding modes between protein L-isoaspartyl (D-aspartyl) O-methyltransferase and peptide substrates including isomerized aspartic acid residues using in silico analytic methods for the substrate screening.

    Science.gov (United States)

    Oda, Akifumi; Noji, Ikuhiko; Fukuyoshi, Shuichi; Takahashi, Ohgi

    2015-12-10

    Because the aspartic acid (Asp) residues in proteins are occasionally isomerized in the human body, not only l-α-Asp but also l-β-Asp, D-α-Asp and D-β-Asp are found in human proteins. In these isomerized aspartic acids, the proportion of D-β-Asp is the largest and the proportions of l-β-Asp and D-α-Asp found in human proteins are comparatively small. To explain the proportions of aspartic acid isomers, the possibility of an enzyme able to repair l-β-Asp and D-α-Asp is frequently considered. The protein L-isoaspartyl (D-aspartyl) O-methyltransferase (PIMT) is considered one of the possible repair enzymes for l-β-Asp and D-α-Asp. Human PIMT is an enzyme that recognizes both l-β-Asp and D-α-Asp, and catalyzes the methylation of their side chains. In this study, the binding modes between PIMT and peptide substrates containing l-β-Asp or D-α-Asp residues were investigated using computational protein-ligand docking and molecular dynamics simulations. The results indicate that carboxyl groups of both l-β-Asp and D-α-Asp were recognized in similar modes by PIMT and that the C-terminal regions of substrate peptides were located in similar positions on PIMT for both the l-β-Asp and D-α-Asp peptides. In contrast, for peptides containing l-α-Asp or D-β-Asp residues, which are not substrates of PIMT, the computationally constructed binding modes between PIMT and peptides greatly differed from those between PIMT and substrates. In the nonsubstrate peptides, not inter- but intra-molecular hydrogen bonds were observed, and the conformations of peptides were more rigid than those of substrates. Thus, the in silico analytical methods were able to distinguish substrates from nonsubstrates and the computational methods are expected to complement experimental analytical methods.

  11. Shared Binding Sites in Lepidoptera for Bacillus thuringiensis Cry1Ja and Cry1A Toxins

    OpenAIRE

    Herrero, Salvador; González-Cabrera, Joel; Tabashnik, Bruce E; Ferré, Juan

    2001-01-01

    Bacillus thuringiensis toxins act by binding to specific target sites in the insect midgut epithelial membrane. The best-known mechanism of resistance to B. thuringiensis toxins is reduced binding to target sites. Because alteration of a binding site shared by several toxins may cause resistance to all of them, knowledge of which toxins share binding sites is useful for predicting cross-resistance. Conversely, cross-resistance among toxins suggests that the toxins share a binding site. At lea...

  12. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    leucocyte antigen (HLA) molecules, are encoded by extremely polymorphic genes on chromosome 6. Due to this polymorphism, thousands of different MHC molecules exist, making the experimental identification of peptide-MHC interactions a very costly procedure. This has primed the need for in silico peptide......-MHC prediction methods, and over the last decade several such methods have been successfully developed and used for epitope discovery purposes. My PhD project has been dedicated to improve methods for predicting peptide-MHC interactions by developing new strategies for training prediction algorithms based...... on machine learning techniques. Several MHC class I binding prediction algorithms have been developed and due to their high accuracy they are used by many immunologists to facilitate the conventional experimental process of epitope discovery. However, the accuracy of these methods depends on data defining...

  13. Haptenation: Chemical Reactivity and Protein Binding

    Directory of Open Access Journals (Sweden)

    Itai Chipinda

    2011-01-01

    Full Text Available Low molecular weight chemical (LMW allergens are commonly referred to as haptens. Haptens must complex with proteins to be recognized by the immune system. The majority of occupationally related haptens are reactive, electrophilic chemicals, or are metabolized to reactive metabolites that form covalent bonds with nucleophilic centers on proteins. Nonelectrophilic protein binding may occur through disulfide exchange, coordinate covalent binding onto metal ions on metalloproteins or of metal allergens, themselves, to the major histocompatibility complex. Recent chemical reactivity kinetic studies suggest that the rate of protein binding is a major determinant of allergenic potency; however, electrophilic strength does not seem to predict the ability of a hapten to skew the response between Th1 and Th2. Modern proteomic mass spectrometry methods that allow detailed delineation of potential differences in protein binding sites may be valuable in predicting if a chemical will stimulate an immediate or delayed hypersensitivity. Chemical aspects related to both reactivity and protein-specific binding are discussed.

  14. Electrostatically biased binding of kinesin to microtubules.

    Directory of Open Access Journals (Sweden)

    Barry J Grant

    2011-11-01

    Full Text Available The minimum motor domain of kinesin-1 is a single head. Recent evidence suggests that such minimal motor domains generate force by a biased binding mechanism, in which they preferentially select binding sites on the microtubule that lie ahead in the progress direction of the motor. A specific molecular mechanism for biased binding has, however, so far been lacking. Here we use atomistic Brownian dynamics simulations combined with experimental mutagenesis to show that incoming kinesin heads undergo electrostatically guided diffusion-to-capture by microtubules, and that this produces directionally biased binding. Kinesin-1 heads are initially rotated by the electrostatic field so that their tubulin-binding sites face inwards, and then steered towards a plus-endwards binding site. In tethered kinesin dimers, this bias is amplified. A 3-residue sequence (RAK in kinesin helix alpha-6 is predicted to be important for electrostatic guidance. Real-world mutagenesis of this sequence powerfully influences kinesin-driven microtubule sliding, with one mutant producing a 5-fold acceleration over wild type. We conclude that electrostatic interactions play an important role in the kinesin stepping mechanism, by biasing the diffusional association of kinesin with microtubules.

  15. SHBG (Sex Hormone Binding Globulin)

    Science.gov (United States)

    ... as: Testosterone-estrogen Binding Globulin; TeBG Formal name: Sex Hormone Binding Globulin Related tests: Testosterone , Free Testosterone, ... I should know? How is it used? The sex hormone binding globulin (SHBG) test may be used ...

  16. Oligosaccharide binding to barley alpha-amylase 1

    DEFF Research Database (Denmark)

    Robert, X.; Haser, R.; Mori, H.;

    2005-01-01

    Enzymatic subsite mapping earlier predicted 10 binding subsites in the active site substrate binding cleft of barley alpha-amylase isozymes. The three-dimensional structures of the oligosaccharide complexes with barley alpha-amylase isozyme 1 (AMY1) described here give for the first time a thorough...... in barley alpha-amylase isozyme 2 (AMY2), and the sugar binding modes are compared between the two isozymes. The "sugar tongs" surface binding site discovered in the AMY1-thio-DP4 complex is confirmed in the present work. A site that putatively serves as an entrance for the substrate to the active site...

  17. Thermodynamic prediction of glass formation tendency, cluster-in-jellium model for metallic glasses, ab initio tight-binding calculations, and new density functional theory development for systems with strong electron correlation

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Yongxin [Iowa State Univ., Ames, IA (United States)

    2009-01-01

    also plays an important role, as it may directly track the movement of every atom. Simulation time is a major limit for molecular dynamics, not only because of “slow” computer speed, but also because of the accumulation error in the numerical treatment of the motion equations. There is also a great concern about the reliability of the emperical potentials if using classical molecular dynamics. Ab initio methods based on density functional theory(DFT) do not have this problem, however, it suffers from small simulation cells and is more demanding computationally. When crystal phase is involved, size effect of the simulation cell is more pronounced since long-range elastic energy would be established. Simulation methods which are more efficient in computation but yet have similar reliability as the ab initio methods, like tight-binding method, are highly desirable. While the complexity of metallic glasses comes from the atomistic level, there is also a large field which deals with the complexity from electronic level. The only “ab initio” method applicable to solid state systems is density functional theory with local density approximation( LDA) or generalized gradient approximation(GGA) for the exchange-correlation energy. It is very successful for simple sp element, where it reaches an high accuracy for determining the surface reconstruction. However, there is a large class of materials with strong electron correlation, where DFT based on LDA or GGA fails in a fundamental way. An “ab initio” method which can generally apply to correlated materials, as LDA for simple sp element, is still to be developed. The thesis is prepared to address some of the above problems.

  18. Cooperative binding of copper(I) to the metal binding domains in Menkes disease protein

    DEFF Research Database (Denmark)

    Jensen, P Y; Bonander, N; Møller, L B;

    1999-01-01

    We have optimised the overexpression and purification of the N-terminal end of the Menkes disease protein expressed in Escherichia coli, containing one, two and six metal binding domains (MBD), respectively. The domain(s) have been characterised using circular dichroism (CD) and fluorescence...... spectroscopy, and their copper(I) binding properties have been determined. Structure prediction derived from far-UV CD indicates that the secondary structure is similar in the three proteins and dominated by beta-sheet. The tryptophan fluorescence maximum is blue-shifted in the constructs containing two...... and six MBDs relative to the monomer, suggesting more structurally buried tryptophan(s), compared to the single MBD construct. Copper(I) binding has been studied by equilibrium dialysis under anaerobic conditions. We show that the copper(I) binding to constructs containing two and six domains...

  19. Gamma Oscillations and Visual Binding

    Science.gov (United States)

    Robinson, Peter A.; Kim, Jong Won

    2006-03-01

    At the root of visual perception is the mechanism the brain uses to analyze features in a scene and bind related ones together. Experiments show this process is linked to oscillations of brain activity in the 30-100 Hz gamma band. Oscillations at different sites have correlation functions (CFs) that often peak at zero lag, implying simultaneous firing, even when conduction delays are large. CFs are strongest between cells stimulated by related features. Gamma oscillations are studied here by modeling mm-scale patchy interconnections in the visual cortex. Resulting predictions for gamma responses to stimuli account for numerous experimental findings, including why oscillations and zero-lag synchrony are associated, observed connections with feature preferences, the shape of the zero-lag peak, and variations of CFs with attention. Gamma waves are found to obey the Schroedinger equation, opening the possibility of cortical analogs of quantum phenomena. Gamma instabilities are tied to observations of gamma activity linked to seizures and hallucinations.

  20. Electron binding energies using perturbative delta-SCF method

    Science.gov (United States)

    Bhusal, Shusil; Baruah, Tunna; Zope, Rajendra

    The knowledge of fundamental and optical gaps is of significant importance for organic photovoltaics. The electron binding energies estimated from the Kohn-Sham eigenvalues are significantly underestimated. Here, we use our recently outlined perturbative delta-SCF approach to compute the electron binding energies of a number of aromatic organic molecules commonly used in organic photovoltaics. Further, the electron affinities are also computed for the C60, C70 and PCBM. The results show that the perturbative delta-SCF provide adequate description of valence electron binding energies. We also applied the method to compute the core binding energies and the core-valence excited states. While the method can successfully predict the core-valence excited states the results on the core-binding energies are mixed. The strategies for improvement of the core binding energies will be discussed.

  1. A model for positron binding to polar molecules

    CERN Document Server

    Gribakin, G F

    2015-01-01

    A model for positron binding to polar molecules is considered by combining the dipole potential outside the molecule with a strongly repulsive core of a given radius. Using existing experimental data on binding energies leads to unphysically small core radii for all of the molecules studied. This suggests that electron-positron correlations neglected in the simple model play a large role in determining the binding energy. We account for these by including polarization potential via perturbation theory. The improved model enables reliable predictions of binding energies to be made for a range of polar organic molecules and hydrogen cyanide, whose binding energy is known from accurate quantum chemistry calculations. The model explains the linear dependence of the binding energies on the polarizability inferred from the experimental data [Danielson et al 2009 J. Phys. B: At. Mol. Opt. Phys. 42 235203].

  2. Conformational heterogeneity of the calmodulin binding interface

    Science.gov (United States)

    Shukla, Diwakar; Peck, Ariana; Pande, Vijay S.

    2016-04-01

    Calmodulin (CaM) is a ubiquitous Ca2+ sensor and a crucial signalling hub in many pathways aberrantly activated in disease. However, the mechanistic basis of its ability to bind diverse signalling molecules including G-protein-coupled receptors, ion channels and kinases remains poorly understood. Here we harness the high resolution of molecular dynamics simulations and the analytical power of Markov state models to dissect the molecular underpinnings of CaM binding diversity. Our computational model indicates that in the absence of Ca2+, sub-states in the folded ensemble of CaM's C-terminal domain present chemically and sterically distinct topologies that may facilitate conformational selection. Furthermore, we find that local unfolding is off-pathway for the exchange process relevant for peptide binding, in contrast to prior hypotheses that unfolding might account for binding diversity. Finally, our model predicts a novel binding interface that is well-populated in the Ca2+-bound regime and, thus, a candidate for pharmacological intervention.

  3. Cellulose binding domain proteins

    Energy Technology Data Exchange (ETDEWEB)

    Shoseyov, Oded (Karmey Yosef, IL); Shpiegl, Itai (Rehovot, IL); Goldstein, Marc (Davis, CA); Doi, Roy (Davis, CA)

    1998-01-01

    A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production thereof. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques.

  4. Sequential memory: Binding dynamics

    Science.gov (United States)

    Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

    2015-10-01

    Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

  5. Lectin binding in meningiomas.

    Science.gov (United States)

    Kleinert, R; Radner, H

    1987-01-01

    Forty-two meningiomas of different morphological sub-type were examined to determine their pattern of binding to 11 different lectins which characterize cell surface components such as carbohydrate residues. Histiocytic and xanthoma cells within meningiomas could be demonstrated with six different lectins: wheat germ agglutinin (WGA), peanut agglutinin (PNA) Bauhinia purpurea agglutinin (BPA), Helix pomatia agglutinin (HPA), Vicia fava agglutinin (VFA) and Soyabean agglutinin (SBA). Vascular elements including endothelial cells and intimal cells, bound Ulex europaeus agglutinin type 1 (UEA 1), WGA and HPA. The fibrous stroma in fibrous and fibroblastic meningiomas bound PNA, Laburnum alpinum agglutinin (LAA) and SBA. Tumour cells in meningotheliomatous meningiomas and some areas of anaplastic meningiomas bound Concanavalin A, PNA, LAA and VFA whereas tumour cells in fibrous and fibroblastic meningiomas bound BPA, LAA and VFA. Lectin binding has proved to be of value in detecting histiocytic and xanthoma cells together with vascular elements within meningiomas. In addition, the different lectin binding patterns allow different histological sub-types of meningioma to be distinguished although the biological significance of the binding patterns is unclear. PMID:3658105

  6. Predicting RNA-RNA Interactions Using RNAstructure.

    Science.gov (United States)

    DiChiacchio, Laura; Mathews, David H

    2016-01-01

    RNA-RNA binding is a required step for many regulatory and catalytic processes in the cell. Identifying RNA-RNA hybridization sites is challenging because of the competition between intramolecular and intermolecular structure formation. A complete picture of RNA-RNA binding includes an understanding of single-stranded folding and binding site accessibility, and is strongly concentration-dependent. This chapter provides guidance for using RNAstructure to predict RNA-RNA binding sites and RNA-RNA structures, utilizing free energy minimization and partition function calculations. RNAstructure is freely available at http://rna.urmc.rochester.edu/RNAstructure.html . PMID:27665592

  7. Glycan masking of Plasmodium vivax Duffy Binding Protein for probing protein binding function and vaccine development.

    Directory of Open Access Journals (Sweden)

    Sowmya Sampath

    Full Text Available Glycan masking is an emerging vaccine design strategy to focus antibody responses to specific epitopes, but it has mostly been evaluated on the already heavily glycosylated HIV gp120 envelope glycoprotein. Here this approach was used to investigate the binding interaction of Plasmodium vivax Duffy Binding Protein (PvDBP and the Duffy Antigen Receptor for Chemokines (DARC and to evaluate if glycan-masked PvDBPII immunogens would focus the antibody response on key interaction surfaces. Four variants of PVDBPII were generated and probed for function and immunogenicity. Whereas two PvDBPII glycosylation variants with increased glycan surface coverage distant from predicted interaction sites had equivalent binding activity to wild-type protein, one of them elicited slightly better DARC-binding-inhibitory activity than wild-type immunogen. Conversely, the addition of an N-glycosylation site adjacent to a predicted PvDBP interaction site both abolished its interaction with DARC and resulted in weaker inhibitory antibody responses. PvDBP is composed of three subdomains and is thought to function as a dimer; a meta-analysis of published PvDBP mutants and the new DBPII glycosylation variants indicates that critical DARC binding residues are concentrated at the dimer interface and along a relatively flat surface spanning portions of two subdomains. Our findings suggest that DARC-binding-inhibitory antibody epitope(s lie close to the predicted DARC interaction site, and that addition of N-glycan sites distant from this site may augment inhibitory antibodies. Thus, glycan resurfacing is an attractive and feasible tool to investigate protein structure-function, and glycan-masked PvDBPII immunogens might contribute to P. vivax vaccine development.

  8. Protein-ligand binding affinities from large-scale quantum mechanical simulations

    OpenAIRE

    Fox, Stephen J.

    2012-01-01

    The accurate prediction of protein-drug binding affinities is a major aim of computational drug optimisation and development. A quantitative measure of binding affinity is provided by the free energy of binding, and such calculations typically require extensive configurational sampling of entities such as proteins with thousands of atoms. Current binding free energy methods use force fields to perform the configurational sampling and to compute interaction energies. Due to the empirical natur...

  9. Domain-based small molecule binding site annotation

    Directory of Open Access Journals (Sweden)

    Dumontier Michel

    2006-03-01

    Full Text Available Abstract Background Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID, a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB. More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. Description Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60% of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. Conclusion By

  10. Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

    Directory of Open Access Journals (Sweden)

    Arnoldo J Müller-Molina

    Full Text Available To know the map between transcription factors (TFs and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

  11. Analysis of Peptide Ligand Binding to FGFR1

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Simulating annealing algorithm was used in docking computation to predict a selected peptide VYMSPF(P2) binding site on the ectodomain of FGFR1. The peptide is located on the hydrophobic surface of the receptor, which is critical for FGF binding. The synthesized peptide can effectively inhibit the mitogenic activity of aFGF, and has a potential to become a therapeutic agent as an aFGF antagonist.

  12. Polypharmacology within CXCR4: Multiple binding sites and allosteric behavior

    Science.gov (United States)

    Planesas, Jesús M.; Pérez-Nueno, Violeta I.; Borrell, José I.; Teixidó, Jordi

    2014-10-01

    CXCR4 is a promiscuous receptor, which binds multiple diverse ligands. As usual in promiscuous proteins, CXCR4 has a large binding site, with multiple subsites, and high flexibility. Hence, it is not surprising that it is involved in the phenomenon of allosteric modulation. However, incomplete knowledge of allosteric ligand-binding sites has hampered an in-depth molecular understanding of how these inhibitors work. For example, it is known that lipidated fragments of intracellular GPCR loops, so called pepducins, such as pepducin ATI-2341, modulate CXCR4 activity using an agonist allosteric mechanism. Nevertheless, there are also examples of small organic molecules, such as AMD11070 and GSK812397, which may act as antagonist allosteric modulators. Here, we give new insights into this issue by proposing the binding interactions between the CXCR4 receptor and the above-mentioned allosteric modulators. We propose that CXCR4 has minimum two topographically different allosteric binding sites. One allosteric site would be in the intracellular loop 1 (ICL1) where pepducin ATI-2341 would bind to CXCR4, and the second one, in the extracellular side of CXCR4 in a subsite into the main orthosteric binding pocket, delimited by extracellular loops n° 1, 2, and the N-terminal end, where antagonists AMD11070 and GSK812397 would bind. Prediction of allosteric interactions between CXCR4 and pepducin ATI-2341 were studied first by rotational blind docking to determine the main binding region and a subsequent refinement of the best pose was performed using flexible docking methods and molecular dynamics. For the antagonists AMD11070 and GSK812397, the entire CXCR4 protein surface was explored by blind docking to define the binding region. A second docking analysis by subsites of the identified binding region was performed to refine the allosteric interactions. Finally, we identified the binding residues that appear to be essential for CXCR4 (agonists and antagonists) allosteric

  13. Drosophila Stathmins Bind Tubulin Heterodimers with High and Variable Stoichiometries*

    Science.gov (United States)

    Lachkar, Sylvie; Lebois, Marion; Steinmetz, Michel O.; Guichet, Antoine; Lal, Neha; Curmi, Patrick A.; Sobel, André; Ozon, Sylvie

    2010-01-01

    In vertebrates, stathmins form a family of proteins possessing two tubulin binding repeats (TBRs), which each binds one soluble tubulin heterodimer. The stathmins thus sequester two tubulins in a phosphorylation-dependent manner, providing a link between signal transduction and microtubule dynamics. In Drosophila, we show here that a single stathmin gene (stai) encodes a family of D-stathmin proteins. Two of the D-stathmins are maternally deposited and then restricted to germ cells, and the other two are detected in the nervous system during embryo development. Like in vertebrates, the nervous system-enriched stathmins contain an N-terminal domain involved in subcellular targeting. All the D-stathmins possess a domain containing three or four predicted TBRs, and we demonstrate here, using complementary biochemical and biophysical methods, that all four predicted TBR domains actually bind tubulin. D-stathmins can indeed bind up to four tubulins, the resulting complex being directly visualized by electron microscopy. Phylogenetic analysis shows that the presence of regulated multiple tubulin sites is a conserved characteristic of stathmins in invertebrates and allows us to predict key residues in stathmin for the binding of tubulin. Altogether, our results reveal that the single Drosophila stathmin gene codes for a stathmin family similar to the multigene vertebrate one, but with particular tubulin binding properties. PMID:20145240

  14. Drosophila stathmins bind tubulin heterodimers with high and variable stoichiometries.

    Science.gov (United States)

    Lachkar, Sylvie; Lebois, Marion; Steinmetz, Michel O; Guichet, Antoine; Lal, Neha; Curmi, Patrick A; Sobel, André; Ozon, Sylvie

    2010-04-01

    In vertebrates, stathmins form a family of proteins possessing two tubulin binding repeats (TBRs), which each binds one soluble tubulin heterodimer. The stathmins thus sequester two tubulins in a phosphorylation-dependent manner, providing a link between signal transduction and microtubule dynamics. In Drosophila, we show here that a single stathmin gene (stai) encodes a family of D-stathmin proteins. Two of the D-stathmins are maternally deposited and then restricted to germ cells, and the other two are detected in the nervous system during embryo development. Like in vertebrates, the nervous system-enriched stathmins contain an N-terminal domain involved in subcellular targeting. All the D-stathmins possess a domain containing three or four predicted TBRs, and we demonstrate here, using complementary biochemical and biophysical methods, that all four predicted TBR domains actually bind tubulin. D-stathmins can indeed bind up to four tubulins, the resulting complex being directly visualized by electron microscopy. Phylogenetic analysis shows that the presence of regulated multiple tubulin sites is a conserved characteristic of stathmins in invertebrates and allows us to predict key residues in stathmin for the binding of tubulin. Altogether, our results reveal that the single Drosophila stathmin gene codes for a stathmin family similar to the multigene vertebrate one, but with particular tubulin binding properties. PMID:20145240

  15. Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2008-01-01

    Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate...

  16. Binding leverage as a molecular basis for allosteric regulation.

    Directory of Open Access Journals (Sweden)

    Simon Mitternacht

    2011-09-01

    Full Text Available Allosteric regulation involves conformational transitions or fluctuations between a few closely related states, caused by the binding of effector molecules. We introduce a quantity called binding leverage that measures the ability of a binding site to couple to the intrinsic motions of a protein. We use Monte Carlo simulations to generate potential binding sites and either normal modes or pairs of crystal structures to describe relevant motions. We analyze single catalytic domains and multimeric allosteric enzymes with complex regulation. For the majority of the analyzed proteins, we find that both catalytic and allosteric sites have high binding leverage. Furthermore, our analysis of the catabolite activator protein, which is allosteric without conformational change, shows that its regulation involves other types of motion than those modulated at sites with high binding leverage. Our results point to the importance of incorporating dynamic information when predicting functional sites. Because it is possible to calculate binding leverage from a single crystal structure it can be used for characterizing proteins of unknown function and predicting latent allosteric sites in any protein, with implications for drug design.

  17. Megalin binds and mediates cellular internalization of folate binding protein

    DEFF Research Database (Denmark)

    Birn, Henrik; Zhai, Xiaoyue; Holm, Jan;

    2005-01-01

    Folate is an essential vitamin involved in a number of biological processes. High affinity folate binding proteins (FBPs) exist both as glycosylphosphatidylinositol-linked, membrane associated folate binding proteins and as soluble FBPs in plasma and some secretory fluids such as milk, saliva...... to bind and mediate cellular uptake of FBP. Surface plasmon resonance analysis shows binding of bovine and human milk FBP to immobilized megalin, but not to low density lipoprotein receptor related protein. Binding of (125)I-labeled folate binding protein (FBP) to sections of kidney proximal tubule, known...... to express high levels of megalin, is inhibitable by excess unlabeled FBP and by receptor associated protein, a known inhibitor of binding to megalin. Immortalized rat yolk sac cells, representing an established model for studying megalin-mediated uptake, reveal (125)I-labeled FBP uptake which is inhibited...

  18. A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data.

    Directory of Open Access Journals (Sweden)

    Xin He

    Full Text Available BACKGROUND: How transcription factors (TFs interact with cis-regulatory sequences and interact with each other is a fundamental, but not well understood, aspect of gene regulation. METHODOLOGY/PRINCIPAL FINDINGS: We present a computational method to address this question, relying on the established biophysical principles. This method, STAP (sequence to affinity prediction, takes into account all combinations and configurations of strong and weak binding sites to analyze large scale transcription factor (TF-DNA binding data to discover cooperative interactions among TFs, infer sequence rules of interaction and predict TF target genes in new conditions with no TF-DNA binding data. The distinctions between STAP and other statistical approaches for analyzing cis-regulatory sequences include the utility of physical principles and the treatment of the DNA binding data as quantitative representation of binding strengths. Applying this method to the ChIP-seq data of 12 TFs in mouse embryonic stem (ES cells, we found that the strength of TF-DNA binding could be significantly modulated by cooperative interactions among TFs with adjacent binding sites. However, further analysis on five putatively interacting TF pairs suggests that such interactions may be relatively insensitive to the distance and orientation of binding sites. Testing a set of putative Nanog motifs, STAP showed that a novel Nanog motif could better explain the ChIP-seq data than previously published ones. We then experimentally tested and verified the new Nanog motif. A series of comparisons showed that STAP has more predictive power than several state-of-the-art methods for cis-regulatory sequence analysis. We took advantage of this power to study the evolution of TF-target relationship in Drosophila. By learning the TF-DNA interaction models from the ChIP-chip data of D. melanogaster (Mel and applying them to the genome of D. pseudoobscura (Pse, we found that only about half of the

  19. Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data.

    Directory of Open Access Journals (Sweden)

    Yaron Orenstein

    Full Text Available The new technology of protein binding microarrays (PBMs allows simultaneous measurement of the binding intensities of a transcription factor to tens of thousands of synthetic double-stranded DNA probes, covering all possible 10-mers. A key computational challenge is inferring the binding motif from these data. We present a systematic comparison of four methods developed specifically for reconstructing a binding site motif represented as a positional weight matrix from PBM data. The reconstructed motifs were evaluated in terms of three criteria: concordance with reference motifs from the literature and ability to predict in vivo and in vitro bindings. The evaluation encompassed over 200 transcription factors and some 300 assays. The results show a tradeoff between how the methods perform according to the different criteria, and a dichotomy of method types. Algorithms that construct motifs with low information content predict PBM probe ranking more faithfully, while methods that produce highly informative motifs match reference motifs better. Interestingly, in predicting high-affinity binding, all methods give far poorer results for in vivo assays compared to in vitro assays.

  20. Ligand-Binding Properties of the Carboxyl-Terminal Repeat Domain of Streptococcus mutans Glucan-Binding Protein A

    OpenAIRE

    Haas, Wolfgang; Banas, Jeffrey A.

    2000-01-01

    Streptococcus mutans glucan-binding protein A (GbpA) has sequence similarity in its carboxyl-terminal domain with glucosyltransferases (GTFs), the enzymes responsible for catalyzing the synthesis of the glucans to which GbpA and GTFs can bind and which promote S. mutans attachment to and accumulation on the tooth surface. It was predicted that this C-terminal region, comprised of what have been termed YG repeats, represents the GbpA glucan-binding domain (GBD). In an effort to test this hypot...

  1. A deep learning framework for modeling structural features of RNA-binding protein targets.

    Science.gov (United States)

    Zhang, Sai; Zhou, Jingtian; Hu, Hailin; Gong, Haipeng; Chen, Ligong; Cheng, Chao; Zeng, Jianyang

    2016-02-29

    RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this paper, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https

  2. A deep learning framework for modeling structural features of RNA-binding protein targets

    Science.gov (United States)

    Zhang, Sai; Zhou, Jingtian; Hu, Hailin; Gong, Haipeng; Chen, Ligong; Cheng, Chao; Zeng, Jianyang

    2016-01-01

    RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this paper, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https

  3. Carboplatin binding to histidine

    Energy Technology Data Exchange (ETDEWEB)

    Tanley, Simon W. M. [University of Manchester, Brunswick Street, Manchester M13 9PL (United Kingdom); Diederichs, Kay [University of Konstanz, D-78457 Konstanz (Germany); Kroon-Batenburg, Loes M. J. [Utrecht University, Padualaan 8, 3584 CH Utrecht (Netherlands); Levy, Colin [University of Manchester, 131 Princess Street, Manchester M1 7DN (United Kingdom); Schreurs, Antoine M. M. [Utrecht University, Padualaan 8, 3584 CH Utrecht (Netherlands); Helliwell, John R., E-mail: john.helliwell@manchester.ac.uk [University of Manchester, Brunswick Street, Manchester M13 9PL (United Kingdom)

    2014-08-29

    An X-ray crystal structure showing the binding of purely carboplatin to histidine in a model protein has finally been obtained. This required extensive crystallization trials and various novel crystal structure analyses. Carboplatin is a second-generation platinum anticancer agent used for the treatment of a variety of cancers. Previous X-ray crystallographic studies of carboplatin binding to histidine (in hen egg-white lysozyme; HEWL) showed the partial conversion of carboplatin to cisplatin owing to the high NaCl concentration used in the crystallization conditions. HEWL co-crystallizations with carboplatin in NaBr conditions have now been carried out to confirm whether carboplatin converts to the bromine form and whether this takes place in a similar way to the partial conversion of carboplatin to cisplatin observed previously in NaCl conditions. Here, it is reported that a partial chemical transformation takes place but to a transplatin form. Thus, to attempt to resolve purely carboplatin binding at histidine, this study utilized co-crystallization of HEWL with carboplatin without NaCl to eliminate the partial chemical conversion of carboplatin. Tetragonal HEWL crystals co-crystallized with carboplatin were successfully obtained in four different conditions, each at a different pH value. The structural results obtained show carboplatin bound to either one or both of the N atoms of His15 of HEWL, and this particular variation was dependent on the concentration of anions in the crystallization mixture and the elapsed time, as well as the pH used. The structural details of the bound carboplatin molecule also differed between them. Overall, the most detailed crystal structure showed the majority of the carboplatin atoms bound to the platinum centre; however, the four-carbon ring structure of the cyclobutanedicarboxylate moiety (CBDC) remained elusive. The potential impact of the results for the administration of carboplatin as an anticancer agent are described.

  4. The MHC motif viewer: a visualization tool for MHC binding motifs

    DEFF Research Database (Denmark)

    Rapin, Nicolas; Hoof, Ilka; Lund, Ole;

    2010-01-01

    In vertebrates, the onset of cellular immune reactions is controlled by presentation of peptides in complex with major histocompatibility complex (MHC) molecules to T cell receptors. In humans, MHCs are called human leukocyte antigens (HLAs). Different MHC molecules present different subsets of...... peptides, and knowledge of their binding specificities is important for understanding differences in the immune response between individuals. Algorithms predicting which peptides bind a given MHC molecule have recently been developed with high prediction accuracy. The utility of these algorithms is...... binding motif for each MHC molecule is predicted using state-of-the-art, pan-specific peptide-MHC binding-prediction methods, and is visualized as a sequence logo, in a format that allows for a comprehensive interpretation of binding motif anchor positions and amino acid preferences....

  5. Causal binding of actions to their effects.

    Science.gov (United States)

    Buehner, Marc J; Humphreys, Gruffydd R

    2009-10-01

    According to widely held views in cognitive science harking back to David Hume, causality cannot be perceived directly, but instead is inferred from patterns of sensory experience, and the quality of these inferences is determined by perceivable quantities such as contingency and contiguity. We report results that suggest a reversal of Hume's conjecture: People's sense of time is warped by the experience of causality. In a stimulus-anticipation task, participants' response behavior reflected a shortened experience of time in the case of target stimuli participants themselves had generated, relative to equidistant, equally predictable stimuli they had not caused. These findings suggest that causality in the mind leads to temporal binding of cause and effect, and extend and generalize beyond earlier claims of intentional binding between action and outcome.

  6. Comparison of Transcription Factor Binding Site Models

    KAUST Repository

    Bhuyan, Sharifulislam

    2012-05-01

    Modeling of transcription factor binding sites (TFBSs) and TFBS prediction on genomic sequences are important steps to elucidate transcription regulatory mechanism. Dependency of transcription regulation on a great number of factors such as chemical specificity, molecular structure, genomic and epigenetic characteristics, long distance interaction, makes this a challenging problem. Different experimental procedures generate evidence that DNA-binding domains of transcription factors show considerable DNA sequence specificity. Probabilistic modeling of TFBSs has been moderately successful in identifying patterns from a family of sequences. In this study, we compare performances of different probabilistic models and try to estimate their efficacy over experimental TFBSs data. We build a pipeline to calculate sensitivity and specificity from aligned TFBS sequences for several probabilistic models, such as Markov chains, hidden Markov models, Bayesian networks. Our work, containing relevant statistics and evaluation for the models, can help researchers to choose the most appropriate model for the problem at hand.

  7. Tetrapyrrole binding affinity of the murine and human p22HBP heme-binding proteins.

    Science.gov (United States)

    Micaelo, Nuno M; Macedo, Anjos L; Goodfellow, Brian J; Félix, Vítor

    2010-11-01

    We present the first systematic molecular modeling study of the binding properties of murine (mHBP) and human (hHBP) p22HBP protein (heme-binding protein) with four tetrapyrrole ring systems belonging to the heme biosynthetic pathway: iron protoporphyrin IX (HEMIN), protoporphyrin IX (PPIX), coproporphyrin III (CPIII), coproporphyrin I (CPI). The relative binding affinities predicted by our computational study were found to be similar to those observed experimentally, providing a first rational structural analysis of the molecular recognition mechanism, by p22HBP, toward a number of different tetrapyrrole ligands. To probe the structure of these p22HBP protein complexes, docking, molecular dynamics and MM-PBSA methodologies supported by experimental NMR ring current shift data have been employed. The tetrapyrroles studied were found to bind murine p22HBP with the following binding affinity order: HEMIN> PPIX> CPIII> CPI, which ranged from -22.2 to -6.1 kcal/mol. In general, the protein-tetrapyrrole complexes are stabilized by non-bonded interactions between the tetrapyrrole propionate groups and basic residues of the protein, and by the preferential solvation of the complex compared to the unbound components. PMID:20800521

  8. Mycobacterial PE_PGRS Proteins Contain Calcium-Binding Motifs with Parallel β-roll Folds

    Institute of Scientific and Technical Information of China (English)

    Nandita; Bachhawat; Balvinder; Singh

    2007-01-01

    The PE_PGRS family of proteins unique to mycobacteria is demonstrated to con- rain multiple calcium-binding and glycine-rich sequence motifs GGXGXD/NXUX. This sequence repeat constitutes a calcium-binding parallel/3-roll or parallel β-helix structure and is found in RTX toxins secreted by many Gram-negative bacteria. It is predicted that the highly homologous PE_PGRS proteins containing multiple copies of the nona-peptide motif could fold into similar calcium-binding structures. The implication of the predicted calcium-binding property of PE_PGRS proteins in the Ught of macrophage-pathogen interaction and pathogenesis is presented.

  9. Substrate Specificity and Ionic Regulation of GlnPQ from Lactococcus lactis. An ATP-Binding Cassette Transporter with Four Extracytoplasmic Substrate-Binding Domains

    NARCIS (Netherlands)

    Schuurman-Wolters, Gea K.; Poolman, Bert

    2005-01-01

    We report on the functional characterization of GlnPQ, an ATP-binding cassette transporter with four extracytoplasmic substrate-binding domains. The first predicted transmembrane helix of GlnP was cleaved off in the mature protein and most likely serves as the signal sequence for the extracytoplasmi

  10. Predictions versus high-throughput experiments in T-cell epitope discovery: competition or synergy?

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2012-01-01

    and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest. MHC binding prediction methods are today of a very high quality and can predict MHC binding peptides with high accuracy. This is possible...

  11. Analytic QCD Binding Potentials

    CERN Document Server

    Fried, H M; Grandou, T; Sheu, Y -M

    2011-01-01

    This paper applies the analytic forms of a recent non-perturbative, manifestly gauge- and Lorentz-invariant description (of the exchange of all possible virtual gluons between quarks ($Q$) and/or anti-quarks ($\\bar{Q}$) in a quenched, eikonal approximation) to extract analytic forms for the binding potentials generating a model $Q$-$\\bar{Q}$ "pion", and a model $QQQ$ "nucleon". Other, more complicated $Q$, $\\bar{Q}$ contributions to such color-singlet states may also be identified analytically. An elementary minimization technique, relevant to the ground states of such bound systems, is adopted to approximate the solutions to a more proper, but far more complicated Schroedinger/Dirac equation; the existence of possible contributions to the pion and nucleon masses due to spin, angular momentum, and "deformation" degrees of freedom is noted but not pursued. Neglecting electromagnetic and weak interactions, this analysis illustrates how the one new parameter making its appearance in this exact, realistic formali...

  12. LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone

    KAUST Repository

    Chen, Peng

    2014-12-03

    Background Protein-ligand binding is important for some proteins to perform their functions. Protein-ligand binding sites are the residues of proteins that physically bind to ligands. Despite of the recent advances in computational prediction for protein-ligand binding sites, the state-of-the-art methods search for similar, known structures of the query and predict the binding sites based on the solved structures. However, such structural information is not commonly available. Results In this paper, we propose a sequence-based approach to identify protein-ligand binding residues. We propose a combination technique to reduce the effects of different sliding residue windows in the process of encoding input feature vectors. Moreover, due to the highly imbalanced samples between the ligand-binding sites and non ligand-binding sites, we construct several balanced data sets, for each of which a random forest (RF)-based classifier is trained. The ensemble of these RF classifiers forms a sequence-based protein-ligand binding site predictor. Conclusions Experimental results on CASP9 and CASP8 data sets demonstrate that our method compares favorably with the state-of-the-art protein-ligand binding site prediction methods.

  13. Mechanisms of in vivo binding site selection of the hematopoietic master transcription factor PU.1.

    Science.gov (United States)

    Pham, Thu-Hang; Minderjahn, Julia; Schmidl, Christian; Hoffmeister, Helen; Schmidhofer, Sandra; Chen, Wei; Längst, Gernot; Benner, Christopher; Rehli, Michael

    2013-07-01

    The transcription factor PU.1 is crucial for the development of many hematopoietic lineages and its binding patterns significantly change during differentiation processes. However, the 'rules' for binding or not-binding of potential binding sites are only partially understood. To unveil basic characteristics of PU.1 binding site selection in different cell types, we studied the binding properties of PU.1 during human macrophage differentiation. Using in vivo and in vitro binding assays, as well as computational prediction, we show that PU.1 selects its binding sites primarily based on sequence affinity, which results in the frequent autonomous binding of high affinity sites in DNase I inaccessible regions (25-45% of all occupied sites). Increasing PU.1 concentrations and the availability of cooperative transcription factor interactions during lineage differentiation both decrease affinity thresholds for in vivo binding and fine-tune cell type-specific PU.1 binding, which seems to be largely independent of DNA methylation. Occupied sites were predominantly detected in active chromatin domains, which are characterized by higher densities of PU.1 recognition sites and neighboring motifs for cooperative transcription factors. Our study supports a model of PU.1 binding control that involves motif-binding affinity, PU.1 concentration, cooperativeness with neighboring transcription factor sites and chromatin domain accessibility, which likely applies to all PU.1 expressing cells.

  14. Comparison of the insulin-like growth factor-binding protein-1 and the cervical Bishop score in predicting the onset of delivery%胰岛素样生长因子结合蛋白-1与宫颈Bishop评分在预测临产时间中的比较

    Institute of Scientific and Technical Information of China (English)

    马秀华; 宋风丽; 马丽丽; 贺笑茜

    2012-01-01

    Objectives The aim of this study is to compare the clinical significanc of phosphorylated insulin-like growth factor-binding protein-1 ( IGFBP-1 ) in cervical secretions of full term pregnancy women, and that of cervical Bishop score in predicting the onset of delivery. Methods A total of 200 pregnant women of 37-41 weeks, with intact fetal membranes were enrolled in this study.The IGFBP-1 was determined by immunochromatography and its successful rate in predicting the onset of delivery within 72 hours was assessed by comparison with cervical Bishop score. Results When the cervix Bishop score was greater than or equal to 7, the positive percentage of IGFBP-1 was 95.12%; and when it was less than 7, the positive percentage of IGFBP-1 was 49.69%, the difference was significant (P< 0.001). As cervix maturity degree increased, the positive percentage of IGFBP-1 was rising gradually. There was a significant positive correlation between the cervix maturity and the positive rate of IGFBP-1. Among 110 cases of the onset of delivery within 72 hours, there were 108 cases (98.18%) positive for IGFBP-1, while 2 cases (1.82%) were negative for IGFBP-1. Among 90 cases of the onset of delivery more than 72 hours, there were 10 cases (11.11%) positive for IGFBP-1, while 80 cases (88.89%) were negative for IGFBP-1, the difference was significant (P < 0.001). Within 72 hours before the onset of delivery, the sensitivity, specificity, positive predictive value and negative predictive value of IGFBP-1 were 98.18%, 88.89%, 91.53% and 97.56%, respectively, While, these values of the Bishop score were 31.82%, 93.33%, 85.37%, 52.83%. Conclusions IGFBP-1 reflects cervical maturation, and it can serve as an objective indicator for predicting the onset of delivery. Determining IGFBP-1 is obviously better than using cervical Bishop score in predicting the onset of delivery, and the positive IGFBP-1 could predict the onset of delivery within 72 hours.%目的:探讨足月妊娠妇女宫颈分

  15. Computational design of a PAK1 binding protein.

    Science.gov (United States)

    Jha, Ramesh K; Leaver-Fay, Andrew; Yin, Shuangye; Wu, Yibing; Butterfoss, Glenn L; Szyperski, Thomas; Dokholyan, Nikolay V; Kuhlman, Brian

    2010-07-01

    We describe a computational protocol, called DDMI, for redesigning scaffold proteins to bind to a specified region on a target protein. The DDMI protocol is implemented within the Rosetta molecular modeling program and uses rigid-body docking, sequence design, and gradient-based minimization of backbone and side-chain torsion angles to design low-energy interfaces between the scaffold and target protein. Iterative rounds of sequence design and conformational optimization were needed to produce models that have calculated binding energies that are similar to binding energies calculated for native complexes. We also show that additional conformation sampling with molecular dynamics can be iterated with sequence design to further lower the computed energy of the designed complexes. To experimentally test the DDMI protocol, we redesigned the human hyperplastic discs protein to bind to the kinase domain of p21-activated kinase 1 (PAK1). Six designs were experimentally characterized. Two of the designs aggregated and were not characterized further. Of the remaining four designs, three bound to the PAK1 with affinities tighter than 350 muM. The tightest binding design, named Spider Roll, bound with an affinity of 100 muM. NMR-based structure prediction of Spider Roll based on backbone and (13)C(beta) chemical shifts using the program CS-ROSETTA indicated that the architecture of human hyperplastic discs protein is preserved. Mutagenesis studies confirmed that Spider Roll binds the target patch on PAK1. Additionally, Spider Roll binds to full-length PAK1 in its activated state but does not bind PAK1 when it forms an auto-inhibited conformation that blocks the Spider Roll target site. Subsequent NMR characterization of the binding of Spider Roll to PAK1 revealed a comparably small binding 'on-rate' constant (design the site of novel protein-protein interactions is an important step towards creating new proteins that are useful as therapeutics or molecular probes.

  16. Successful Predictions

    Science.gov (United States)

    Pierrehumbert, R.

    2012-12-01

    In an observational science, it is not possible to test hypotheses through controlled laboratory experiments. One can test parts of the system in the lab (as is done routinely with infrared spectroscopy of greenhouse gases), but the collective behavior cannot be tested experimentally because a star or planet cannot be brought into the lab; it must, instead, itself be the lab. In the case of anthropogenic global warming, this is all too literally true, and the experiment would be quite exciting if it weren't for the unsettling fact that we and all our descendents for the forseeable future will have to continue making our home in the lab. There are nonetheless many routes though which the validity of a theory of the collective behavior can be determined. A convincing explanation must not be a"just-so" story, but must make additional predictions that can be verified against observations that were not originally used in formulating the theory. The field of Earth and planetary climate has racked up an impressive number of such predictions. I will also admit as "predictions" statements about things that happened in the past, provided that observations or proxies pinning down the past climate state were not available at the time the prediction was made. The basic prediction that burning of fossil fuels would lead to an increase of atmospheric CO2, and that this would in turn alter the Earth's energy balance so as to cause tropospheric warming, is one of the great successes of climate science. It began in the lineage of Fourier, Tyndall and Arrhenius, and was largely complete with the the radiative-convective modeling work of Manabe in the 1960's -- all well before the expected warming had progressed far enough to be observable. Similarly, long before the increase in atmospheric CO2 could be detected, Bolin formulated a carbon cycle model and used it to predict atmospheric CO2 out to the year 2000; the actual values come in at the high end of his predicted range, for

  17. Quarkonium Binding and Entropic Force

    CERN Document Server

    Satz, Helmut

    2015-01-01

    A Q-Qbar bound state represents a balance between repulsive kinetic and attractive potential energy. In a hot quark-gluon plasma, the interaction potential experiences medium effects. Color screening modifies the attractive binding force between the quarks, while the increase of entropy with Q-Qbar separation gives rise to a growing repulsion. We study the role of these phenomena for in-medium Q-Qbar binding and dissociation. It is found that the relevant potential for Q-Qbar binding is the free energy F; with increasing Q-Qbar separation, further binding through the internal energy U is compensated by repulsive entropic effects.

  18. RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

    Directory of Open Access Journals (Sweden)

    Hilal Kazan

    Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.

  19. TAL Effector DNA-Binding Principles and Specificity.

    Science.gov (United States)

    Richter, Annekatrin; Streubel, Jana; Boch, Jens

    2016-01-01

    Transcription activator-like effectors (TALEs) are proteins with a unique DNA-binding domain that confers both a predictable and programmable specificity. The DNA-binding domain consists typically of 34-amino acid near-identical repeats. The repeats form a right-handed superhelical structure that wraps around the DNA double helix and exposes the variable amino acids at position 13 of each repeat to the sense strand DNA bases. Each repeat binds one base in a highly specific, non-overlapping, and comma-free fashion. Although TALE specificities are encoded in a simple way, sophisticated rules can be taken into account to build highly efficient DNA-binding modules for biotechnological use. PMID:26443210

  20. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael;

    2014-01-01

    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...

  1. Binding Energy and Equilibrium of Compact Objects

    Directory of Open Access Journals (Sweden)

    Germano M.

    2014-04-01

    Full Text Available The theoretical analysis of the existence of a limit mass for compact astronomic ob- jects requires the solution of the Einstein’s equations of g eneral relativity together with an appropriate equation of state. Analytical solutions exi st in some special cases like the spherically symmetric static object without energy sou rces that is here considered. Solutions, i.e. the spacetime metrics, can have a singular m athematical form (the so called Schwarzschild metric due to Hilbert or a nonsingula r form (original work of Schwarzschild. The former predicts a limit mass and, conse quently, the existence of black holes above this limit. Here it is shown that, the origi nal Schwarzschild met- ric permits compact objects, without mass limit, having rea sonable values for central density and pressure. The lack of a limit mass is also demonst rated analytically just imposing reasonable conditions on the energy-matter densi ty, of positivity and decreas- ing with radius. Finally the ratio between proper mass and to tal mass tends to 2 for high values of mass so that the binding energy reaches the lim it m (total mass seen by a distant observer. As it is known the negative binding energ y reduces the gravitational mass of the object; the limit of m for the binding energy provides a mechanism for stable equilibrium of any amount of mass to contrast the gravitatio nal collapse.

  2. Prediction of peptide bonding affinity: kernel methods for nonlinear modeling

    CERN Document Server

    Bergeron, Charles; Sundling, C Matthew; Krein, Michael; Katt, Bill; Sukumar, Nagamani; Breneman, Curt M; Bennett, Kristin P

    2011-01-01

    This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporation of transferable atom equivalent features improves predictive capability.

  3. Quantitative models of the mechanisms that control genome-wide patterns of transcription factor binding during early Drosophila development.

    Directory of Open Access Journals (Sweden)

    Tommy Kaplan

    Full Text Available Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6-0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription

  4. Alcohol Binding to the Odorant Binding Protein LUSH: Multiple Factors Affecting Binding Affinities

    OpenAIRE

    Ader, Lauren; Jones, David N. M.; Lin, Hai

    2010-01-01

    Density function theory (DFT) calculations have been carried out to investigate the binding of alcohols to the odorant binding protein LUSH from Drosophila melanogaster. LUSH is one of the few proteins known to bind to ethanol at physiologically relevant concentrations and where high-resolution structural information is available for the protein bound to alcohol at these concentrations. The structures of the LUSH–alcohol complexes identify a set of specific hydrogen-bonding interactions as cr...

  5. Sarcomere lattice geometry influences cooperative myosin binding in muscle.

    Directory of Open Access Journals (Sweden)

    Bertrand C W Tanner

    2007-07-01

    Full Text Available In muscle, force emerges from myosin binding with actin (forming a cross-bridge. This actomyosin binding depends upon myofilament geometry, kinetics of thin-filament Ca(2+ activation, and kinetics of cross-bridge cycling. Binding occurs within a compliant network of protein filaments where there is mechanical coupling between myosins along the thick-filament backbone and between actin monomers along the thin filament. Such mechanical coupling precludes using ordinary differential equation models when examining the effects of lattice geometry, kinetics, or compliance on force production. This study uses two stochastically driven, spatially explicit models to predict levels of cross-bridge binding, force, thin-filament Ca(2+ activation, and ATP utilization. One model incorporates the 2-to-1 ratio of thin to thick filaments of vertebrate striated muscle (multi-filament model, while the other comprises only one thick and one thin filament (two-filament model. Simulations comparing these models show that the multi-filament predictions of force, fractional cross-bridge binding, and cross-bridge turnover are more consistent with published experimental values. Furthermore, the values predicted by the multi-filament model are greater than those values predicted by the two-filament model. These increases are larger than the relative increase of potential inter-filament interactions in the multi-filament model versus the two-filament model. This amplification of coordinated cross-bridge binding and cycling indicates a mechanism of cooperativity that depends on sarcomere lattice geometry, specifically the ratio and arrangement of myofilaments.

  6. Prediction of cytochrome P450 mediated metabolism

    DEFF Research Database (Denmark)

    Olsen, Lars; Oostenbrink, Chris; Jørgensen, Flemming Steen

    2015-01-01

    to rationalize what metabolites these enzymes generate. In recent years, many different in silico approaches have been developed to predict binding or regioselective product formation for the different CYP isoforms. These comprise ligand-based methods that are trained on experimental CYP data and structure......-based methods that consider how the substrate is oriented in the active site or/and how reactive the part of the substrate that is accessible to the heme group is. We will review key aspects for various approaches that are available to predict binding and site of metabolism (SOM), what outcome can be expected...

  7. MORPHEUS, a webtool for transcription factor binding analysis using position weight matrices with dependency

    OpenAIRE

    Eugenio Gómez Minguet; Stéphane Segard; Céline Charavay; François Parcy

    2015-01-01

    Transcriptional networks are central to any biological process and changes affecting transcription factors or their binding sites in the genome are a key factor driving evolution. As more organisms are being sequenced, tools are needed to easily predict transcription factor binding sites (TFBS) presence and affinity from mere inspection of genomic sequences. Although many TFBS discovery algorithms exist, tools for using the DNA binding models they generate are relatively scarce and their use ...

  8. DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues

    OpenAIRE

    Ozbek, Pemra; Soner, Seren; Erman, Burak; Haliloglu, Turkan

    2010-01-01

    DNABINDPROT is designed to predict DNA-binding residues, based on the fluctuations of residues in high-frequency modes by the Gaussian network model. The residue pairs that display high mean-square distance fluctuations are analyzed with respect to DNA binding, which are then filtered with their evolutionary conservation profiles and ranked according to their DNA-binding propensities. If the analyses are based on the exact outcome of fluctuations in the highest mode, using a conservation thre...

  9. Binding Energy and Enzymatic Catalysis.

    Science.gov (United States)

    Hansen, David E.; Raines, Ronald T.

    1990-01-01

    Discussed is the fundamental role that the favorable free energy of binding of the rate-determining transition state plays in catalysis. The principle that all of the catalytic factors discussed are realized by the use of this binding energy is reviewed. (CW)

  10. Proton binding to soil humic and fulvic acids: Experiments and NICA-Donnan modelling

    NARCIS (Netherlands)

    Tan, W.; Xiong, J.; Li, Y.; Wang, M.; Weng, L.; Koopal, L.K.

    2013-01-01

    Proton binding to one soil fulvic acid (JGFA), two soil humic acids (JGHA, JLHA) and a lignite-based humic acid (PAHA) was investigated. The results were fitted to NICA-Donnan model and compared directly with the predictions using the generic parameters. NICA-Donnan model can describe proton binding

  11. Computational Investigation of Glycosylation Effects on a Family 1 Carbohydrate-Binding Module

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, C. B.; Talib, M. F.; McCabe, C.; Bu, L.; Adney, W. S.; Himmel, M. E.; Crowley, M. F.; Beckham, G. T.

    2012-01-27

    Carbohydrate-binding modules (CBMs) are ubiquitous components of glycoside hydrolases, which degrade polysaccharides in nature. CBMs target specific polysaccharides, and CBM binding affinity to cellulose is known to be proportional to cellulase activity, such that increasing binding affinity is an important component of performance improvement. To ascertain the impact of protein and glycan engineering on CBM binding, we use molecular simulation to quantify cellulose binding of a natively glycosylated Family 1 CBM. To validate our approach, we first examine aromatic-carbohydrate interactions on binding, and our predictions are consistent with previous experiments, showing that a tyrosine to tryptophan mutation yields a 2-fold improvement in binding affinity. We then demonstrate that enhanced binding of 3-6-fold over a nonglycosylated CBM is achieved by the addition of a single, native mannose or a mannose dimer, respectively, which has not been considered previously. Furthermore, we show that the addition of a single, artificial glycan on the anterior of the CBM, with the native, posterior glycans also present, can have a dramatic impact on binding affinity in our model, increasing it up to 140-fold relative to the nonglycosylated CBM. These results suggest new directions in protein engineering, in that modifying glycosylation patterns via heterologous expression, manipulation of culture conditions, or introduction of artificial glycosylation sites, can alter CBM binding affinity to carbohydrates and may thus be a general strategy to enhance cellulase performance. Our results also suggest that CBM binding studies should consider the effects of glycosylation on binding and function.

  12. The Functional Consequences of Variation in Transcription Factor Binding

    Science.gov (United States)

    Cusanovich, Darren A.; Pavlovic, Bryan; Pritchard, Jonathan K.; Gilad, Yoav

    2014-01-01

    One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as “active enhancers.” PMID:24603674

  13. The functional consequences of variation in transcription factor binding.

    Directory of Open Access Journals (Sweden)

    Darren A Cusanovich

    2014-03-01

    Full Text Available One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as "active enhancers."

  14. Structural and Histone Binding Ability Characterizations of Human PWWP Domains

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Hong; Zeng, Hong; Lam, Robert; Tempel, Wolfram; Amaya, Maria F.; Xu, Chao; Dombrovski, Ludmila; Qiu, Wei; Wang, Yanming; Min, Jinrong (Toronto); (Penn)

    2013-09-25

    The PWWP domain was first identified as a structural motif of 100-130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain 'Royal Family', which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently. The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other 'Royal Family' members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3. PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical {beta}-barrel core, an insertion motif between the second and third {beta}-strands and a C-terminal {alpha}-helix bundle. Both the canonical {beta}-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones.

  15. 胰岛素样生长因子结合蛋白-1在预测早产中的应用价值%The Value of Cervicovaginal Insulin Like Growth Factor Binding Protein-1 in the Prediction of Preterm Labor

    Institute of Scientific and Technical Information of China (English)

    王坤; 郭亚琼; 崔建设; 孙瑞华

    2014-01-01

    Objective to study the value of phosphorylated insulin like growth factor binding protein-1(iGfBP-1)in the prediction of premature labor.Methods 82 pregnant women with threatened premature labor were selected as research subjects, while 45 normal pregnant women as controls. iGfBP-1 in cervical secretion was measured by immunochromatography. Results In those with threatened premature labor, the positive rate of IGFBP-1 was 48.78%, signiifcantly higher than that of the controls(p<0.05). there were 40 cases with iGfBP-1 positive in the study group and the occurrence rate of childbirth within 1 week was 50.12%, which was signiifcantly higher than that of the negative ones(8.50%)(p<0.05). However, there were 3 cases with positive iGfBP-1 in the control group with an occurrence rate of childbirth within 1 week 54.62%, which was higher than that of the negative ones(5.41%)(p<0.05).Conclusion iGfBP-1 can be used in the prediction of premature labor.%目的:评价磷酸化胰岛素样生长因子结合蛋白-1(iGfBP-1)预测早产的应用价值。方法选取我院先兆早产孕妇82例作为检测标本组,正常近孕周或足月待产孕妇45例作为对照组,运用免疫层析法检测宫颈分泌物中的iGfBP-1。结果先兆早产组iGfBP-1阳性率48.78%,对照组iGfBP-1阳性率6.67%,两组差异有显著性(P<0.05);先兆早产组中iGfBP-1阳性40例,一周内分娩率50.12%,阴性42例,一周内分娩率8.50%,两者比较有统计学差异(P<0.05);对照组中iGfBP-1阳性3例,一周内分娩率66.67%,阴性42例,一周内分娩率4.76%,两者比较有统计学差异(P<0.05)。结论检测宫颈分泌物中iGfBP-1可作为预测早产的检测指标,方法简单易行,有推广价值。

  16. Cooperative binding: a multiple personality.

    Science.gov (United States)

    Martini, Johannes W R; Diambra, Luis; Habeck, Michael

    2016-06-01

    Cooperative binding has been described in many publications and has been related to or defined by several different properties of the binding behavior of the ligand to the target molecule. In addition to the commonly used Hill coefficient, other characteristics such as a sigmoidal shape of the overall titration curve in a linear plot, a change of ligand affinity of the other binding sites when a site of the target molecule becomes occupied, or complex roots of the binding polynomial have been used to define or to quantify cooperative binding. In this work, we analyze how the different properties are related in the most general model for binding curves based on the grand canonical partition function and present several examples which highlight differences between the cooperativity characterizing properties which are discussed. Our results mainly show that among the presented definitions there are not two which fully coincide. Moreover, this work poses the question whether it can make sense to distinguish between positive and negative cooperativity based on the macroscopic binding isotherm only. This article shall emphasize that scientists who investigate cooperative effects in biological systems could help avoiding misunderstandings by stating clearly which kind of cooperativity they discuss.

  17. Structural Allostery and Binding of the Transferring Receptor Complex

    Energy Technology Data Exchange (ETDEWEB)

    Xu,G.; Liu, R.; Zak, O.; Aisen, P.; Chance, M.

    2005-01-01

    The structural allostery and binding interface for the human serum transferrin (Tf){center_dot}transferrin receptor (TfR) complex were identified using radiolytic footprinting and mass spectrometry. We have determined previously that the transferrin C-lobe binds to the receptor helical domain. In this study we examined the binding interactions of full-length transferrin with receptor and compared these data with a model of the complex derived from cryoelectron microscopy (cryo-EM) reconstructions. The footprinting results provide the following novel conclusions. First, we report characteristic oxidations of acidic residues in the C-lobe of native Tf and basic residues in the helical domain of TfR that were suppressed as a function of complex formation; this confirms ionic interactions between these protein segments as predicted by cryo-EM data and demonstrates a novel method for detecting ion pair interactions in the formation of macromolecular complexes. Second, the specific side-chain interactions between the C-lobe and N-lobe of transferrin and the corresponding interactions sites on the transferrin receptor predicted from cryo-EM were confirmed in solution. Last, the footprinting data revealed allosteric movements of the iron binding C- and N-lobes of Tf that sequester iron as a function of complex formation; these structural changes promote tighter binding of the metal ion and facilitate efficient ion transport during endocytosis.

  18. Molecular Mechanisms of Pharmaceutical Drug Binding into Calsequestrin

    Directory of Open Access Journals (Sweden)

    ChulHee Kang

    2012-11-01

    Full Text Available Calsequestrin (CASQ is a major Ca2+-storage/buffer protein present in the sarcoplasmic reticulum of both skeletal (CASQ1 and cardiac (CASQ2 muscles. CASQ has significant affinity for a number of pharmaceutical drugs with known muscular toxicities. Our approach, with in silico molecular docking, single crystal X-ray diffraction, and isothermal titration calorimetry (ITC, identified three distinct binding pockets on the surface of CASQ2, which overlap with 2-methyl-2,4-pentanediol (MPD binding sites observed in the crystal structure. Those three receptor sites based on canine CASQ1 crystal structure gave a high correlation (R2 = 0.80 to our ITC data. Daunomycin, doxorubicin, thioridazine, and trifluoperazine showed strong affinity to the S1 site, which is a central cavity formed between three domains of CASQ2. Some of the moderate-affinity drugs and some high-affinity drugs like amlodipine and verapamil displayed their binding into S2 sites, which are the thioredoxin-like fold present in each CASQ domain. Docking predictions combined with dissociation constants imply that presence of large aromatic cores and less flexible functional groups determines the strength of binding affinity to CASQ. In addition, the predicted binding pockets for both caffeine and epigallocatechin overlapped with the S1 and S2 sites, suggesting competitive inhibition by these natural compounds as a plausible explanation for their antagonistic effects on cardiotoxic side effects.

  19. [3]tetrahydrotrazodone binding. Association with serotonin binding sites

    International Nuclear Information System (INIS)

    High (17 nM) and low (603 nM) affinity binding sites for [3]tetrahydrotrazodone ([3] THT), a biologically active analogue of trazodone, have been identified in rat brain membranes. The substrate specificity, concentration, and subcellular and regional distributions of these sites suggest that they may represent a component of the serotonin transmitter system. Pharmacological analysis of [3]THT binding, coupled with brain lesion and drug treatment experiments, revealed that, unlike other antidepressants, [3] THT does not attach to either a biogenic amine transporter or serotonin binding sites. Rather, it would appear that [3]THT may be an antagonist ligand for the serotonin binding site. This probe may prove of value in defining the mechanism of action of trazodone and in further characterizing serotonin receptors

  20. Computational redesign of endonuclease DNA binding and cleavage specificity

    Science.gov (United States)

    Ashworth, Justin; Havranek, James J.; Duarte, Carlos M.; Sussman, Django; Monnat, Raymond J.; Stoddard, Barry L.; Baker, David

    2006-06-01

    The reprogramming of DNA-binding specificity is an important challenge for computational protein design that tests current understanding of protein-DNA recognition, and has considerable practical relevance for biotechnology and medicine. Here we describe the computational redesign of the cleavage specificity of the intron-encoded homing endonuclease I-MsoI using a physically realistic atomic-level forcefield. Using an in silico screen, we identified single base-pair substitutions predicted to disrupt binding by the wild-type enzyme, and then optimized the identities and conformations of clusters of amino acids around each of these unfavourable substitutions using Monte Carlo sampling. A redesigned enzyme that was predicted to display altered target site specificity, while maintaining wild-type binding affinity, was experimentally characterized. The redesigned enzyme binds and cleaves the redesigned recognition site ~10,000 times more effectively than does the wild-type enzyme, with a level of target discrimination comparable to the original endonuclease. Determination of the structure of the redesigned nuclease-recognition site complex by X-ray crystallography confirms the accuracy of the computationally predicted interface. These results suggest that computational protein design methods can have an important role in the creation of novel highly specific endonucleases for gene therapy and other applications.

  1. Application of quantitative structure-activity relationship to the determination of binding constant based on fluorescence quenching

    Energy Technology Data Exchange (ETDEWEB)

    Wen Yingying [Department of Applied Chemistry, Yantai University, Yantai 264005 (China); Liu Huitao, E-mail: liuht-ytu@163.co [Department of Applied Chemistry, Yantai University, Yantai 264005 (China); Luan Feng; Gao Yuan [Department of Applied Chemistry, Yantai University, Yantai 264005 (China)

    2011-01-15

    Quantitative structure-activity relationship (QSAR) model was used to predict and explain binding constant (log K) determined by fluorescence quenching. This method allowed us to predict binding constants of a variety of compounds with human serum albumin (HSA) based on their structures alone. Stepwise multiple linear regression (MLR) and nonlinear radial basis function neural network (RBFNN) were performed to build the models. The statistical parameters provided by the MLR model (R{sup 2}=0.8521, RMS=0.2678) indicated satisfactory stability and predictive ability while the RBFNN predictive ability is somewhat superior (R{sup 2}=0.9245, RMS=0.1736). The proposed models were used to predict the binding constants of two bioactive components in traditional Chinese medicines (isoimperatorin and chrysophanol) whose experimental results were obtained in our laboratory and the predicted results were in good agreement with the experimental results. This QSAR approach can contribute to a better understanding of structural factors of the compounds responsible for drug-protein interactions, and can be useful in predicting the binding constants of other compounds. - Research Highlights: QSAR models for binding constants of some compounds to HSA were developed. The models provide a simple and straightforward way to predict binding constant. QSAR can give some insight into structural features related to binding behavior.

  2. Global analysis of small molecule binding to related protein targets.

    Directory of Open Access Journals (Sweden)

    Felix A Kruger

    2012-01-01

    Full Text Available We report on the integration of pharmacological data and homology information for a large scale analysis of small molecule binding to related targets. Differences in small molecule binding have been assessed for curated pairs of human to rat orthologs and also for recently diverged human paralogs. Our analysis shows that in general, small molecule binding is conserved for pairs of human to rat orthologs. Using statistical tests, we identified a small number of cases where small molecule binding is different between human and rat, some of which had previously been reported in the literature. Knowledge of species specific pharmacology can be advantageous for drug discovery, where rats are frequently used as a model system. For human paralogs, we demonstrate a global correlation between sequence identity and the binding of small molecules with equivalent affinity. Our findings provide an initial general model relating small molecule binding and sequence divergence, containing the foundations for a general model to anticipate and predict within-target-family selectivity.

  3. Architecture and RNA binding of the human negative elongation factor

    Science.gov (United States)

    Vos, Seychelle M; Pöllmann, David; Caizzi, Livia; Hofmann, Katharina B; Rombaut, Pascaline; Zimniak, Tomasz; Herzog, Franz; Cramer, Patrick

    2016-01-01

    Transcription regulation in metazoans often involves promoter-proximal pausing of RNA polymerase (Pol) II, which requires the 4-subunit negative elongation factor (NELF). Here we discern the functional architecture of human NELF through X-ray crystallography, protein crosslinking, biochemical assays, and RNA crosslinking in cells. We identify a NELF core subcomplex formed by conserved regions in subunits NELF-A and NELF-C, and resolve its crystal structure. The NELF-AC subcomplex binds single-stranded nucleic acids in vitro, and NELF-C associates with RNA in vivo. A positively charged face of NELF-AC is involved in RNA binding, whereas the opposite face of the NELF-AC subcomplex binds NELF-B. NELF-B is predicted to form a HEAT repeat fold, also binds RNA in vivo, and anchors the subunit NELF-E, which is confirmed to bind RNA in vivo. These results reveal the three-dimensional architecture and three RNA-binding faces of NELF. DOI: http://dx.doi.org/10.7554/eLife.14981.001 PMID:27282391

  4. Binding in light nuclei: Statistical NN uncertainties vs Computational accuracy

    CERN Document Server

    Perez, R Navarro; Amaro, J E; Arriola, E Ruiz

    2016-01-01

    We analyse the impact of the statistical uncertainties of the the nucleon-nucleon interaction, based on the Granada-2013 np-pp database, on the binding energies of the triton and the alpha particle using a bootstrap method, by solving the Faddeev equations for $^3$H and the Yakubovsky equations for $^4$He respectively. We check that in practice about 30 samples prove enough for a reliable error estimate. An extrapolation of the well fulfilled Tjon-line correlation predicts the experimental binding of the alpha particle within uncertainties.

  5. Structural studies of sugar binding proteins

    OpenAIRE

    Sooriyaarachchi, Sanjeewani

    2010-01-01

    Binding proteins, which are themselves non-enzymatic, play an important role in enzymatic reactions as well as non-enzymatic processes by providing a binding platform for the specific recognition of particular molecules. For example, periplasmic binding proteins play a vital role in nutrient uptake in Gram-negative bacteria. In the present study, three sugar binding proteins, including two periplasmic binding proteins and a β-glucan binding protein, are described. The glucose/galactose bindin...

  6. The binding sites for cocaine and dopamine in the dopamine transporter overlap

    DEFF Research Database (Denmark)

    Beuming, Thijs; Kniazeff, Julie; Bergmann, Marianne L;

    2008-01-01

    T. Our models suggest that the binding site for cocaine and cocaine analogs is deeply buried between transmembrane segments 1, 3, 6 and 8, and overlaps with the binding sites for the substrates dopamine and amphetamine, as well as for benztropine-like DAT inhibitors. We validated our models by detailed...... mutagenesis and by trapping the radiolabeled cocaine analog [3H]CFT in the transporter, either by cross-linking engineered cysteines or with an engineered Zn2+-binding site that was situated extracellularly to the predicted common binding pocket. Our data demonstrate the molecular basis for the competitive...

  7. Probing the human estrogen receptor-α binding requirements for phenolic mono- and di-hydroxyl compounds: a combined synthesis, binding and docking study.

    Science.gov (United States)

    McCullough, Christopher; Neumann, Terrence S; Gone, Jayapal Reddy; He, Zhengjie; Herrild, Christian; Wondergem Nee Lukesh, Julie; Pandey, Rajesh K; Donaldson, William A; Sem, Daniel S

    2014-01-01

    Various estrogen analogs were synthesized and tested for binding to human ERα using a fluorescence polarization displacement assay. Binding affinity and orientation were also predicted using docking calculations. Docking was able to accurately predict relative binding affinity and orientation for estradiol, but only if a tightly bound water molecule bridging Arg394/Glu353 is present. Di-hydroxyl compounds sometimes bind in two orientations, which are flipped in terms of relative positioning of their hydroxyl groups. Di-hydroxyl compounds were predicted to bind with their aliphatic hydroxyl group interacting with His524 in ERα. One nonsteroid-based dihdroxyl compound was 1000-fold specific for ERβ over ERα, and was also 25-fold specific for agonist ERβ versus antagonist activity. Docking predictions suggest this specificity may be due to interaction of the aliphatic hydroxyl with His475 in the agonist form of ERβ, versus with Thr299 in the antagonist form. But, the presence of this aliphatic hydroxyl is not required in all compounds, since mono-hydroxyl (phenolic) compounds bind ERα with high affinity, via hydroxyl hydrogen bonding interactions with the ERα Arg394/Glu353/water triad, and van der Waals interactions with the rest of the molecule.

  8. Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Worning, Peder;

    2004-01-01

    binding peptides and to guiding the process of rational vaccine design. Results: We apply the motif sampler method to the complex problem of MHC class II binding. The input to the method is amino acid peptide sequences extracted from the public databases of SYFPEITHI and MHCPEP and known to bind......Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus...

  9. Value of urinary liver-type fatty acid binding protein in prediction of renal function progression in patients with chronic glomerulonephritis%尿肝型脂肪酸结合蛋白预测慢性肾小球肾炎进展的价值

    Institute of Scientific and Technical Information of China (English)

    徐维佳; 李佳琳; 王琴; 施蓓莉; 牟姗; 倪兆慧

    2012-01-01

    Objective To evaluate the value of urinary liver-type fatty acid binding protein (L-FABP)as a biomarker in prediction of renal function progression in patients with chronic glomerulonephritis (CGN). Methods A total of 123 patients with newly diagnosed CGN by renal biopsy in Shanghai Renji Hospital between 2004 January and 2005 December were enrolled in the study,Twenty-eight healthy subjects were used as control group.Urine samples were collected before biopsy and treatment,and urinary L-FABP was measured by ELISA.The patients with follow-up every three months for 5 years were divided into progressive group and nonprogressive group.The progression of kidney function impairment was defined as a reduction of GFR ≥ 5 ml·min-1·(1.73 m2)-1·year-1 during follow-up.The risk factors of progressive renal function were evaluated and the Spearman correlation analysis was performed to find out the prognostic indicator of renal function deterioration. Results Urinary L-FABP level of CGN patients was significantly higher than that of healthy control group (P<0.01).Urinary L-FABP in CGN patients was negatively correlated with eGFR (r=-0.565,P<0.01) and positively correhted with proteinuria (r=0.501,P<0.01) and Scr (r=0.601,P<0.01).Kaplan-Meier analysis showed that urinary L-FABP excretion>76.58 μg/g·cr predicted progression of renal function.The AUC of urinary L-FABP for prognosis of CGN progression was 0.95,with 87.5% of sensitivity and 90.5%of specificity at the cutoff value of 119.8 μg/g·cr,which revealed its great value of predicting the prognosis of CGN patients. Conclusion Urinary L-FABP can be a novel biomarker of evaluation for renal injury and early progressive renal function deterioration in patients with CGN.%目的 评估尿肝型脂肪酸结合蛋白(L-FABP)预测慢性肾小球肾炎(CGN)病情进展的临床价值.方法 前瞻性入选2004年1月至2005年12月期间在我院行肾穿刺活检明确病理诊断的原发性CGN患者123

  10. Identification of ligands that target the HCV-E2 binding site on CD81.

    Science.gov (United States)

    Olaby, Reem Al; Azzazy, Hassan M; Harris, Rodney; Chromy, Brett; Vielmetter, Jost; Balhorn, Rod

    2013-04-01

    Hepatitis C is a global health problem. While many drug companies have active R&D efforts to develop new drugs for treating Hepatitis C virus (HCV), most target the viral enzymes. The HCV glycoprotein E2 has been shown to play an essential role in hepatocyte invasion by binding to CD81 and other cell surface receptors. This paper describes the use of AutoDock to identify ligand binding sites on the large extracellular loop of the open conformation of CD81 and to perform virtual screening runs to identify sets of small molecule ligands predicted to bind to two of these sites. The best sites selected by AutoLigand were located in regions identified by mutational studies to be the site of E2 binding. Thirty-six ligands predicted by AutoDock to bind to these sites were subsequently tested experimentally to determine if they bound to CD81-LEL. Binding assays conducted using surface Plasmon resonance revealed that 26 out of 36 (72 %) of the ligands bound in vitro to the recombinant CD81-LEL protein. Competition experiments performed using dual polarization interferometry showed that one of the ligands predicted to bind to the large cleft between the C and D helices was also effective in blocking E2 binding to CD81-LEL.

  11. A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

    Directory of Open Access Journals (Sweden)

    Suganthan PN

    2007-09-01

    Full Text Available Abstract Background Odorant binding proteins (OBPs are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as odorant presenters. Although several sequence based search methods have been exploited for protein family prediction, less effort has been devoted to the prediction of OBPs from sequence data and this area is more challenging due to poor sequence identity between these proteins. Results In this paper, we propose a new algorithm that uses Regularized Least Squares Classifier (RLSC in conjunction with multiple physicochemical properties of amino acids to predict odorant-binding proteins. The algorithm was applied to the dataset derived from Pfam and GenDiS database and we obtained overall prediction accuracy of 97.7% (94.5% and 98.4% for positive and negative classes respectively. Conclusion Our study suggests that RLSC is potentially useful for predicting the odorant binding proteins from sequence-derived properties irrespective of sequence similarity. Our method predicts 92.8% of 56 odorant binding proteins non-homologous to any protein in the swissprot database and 97.1% of the 414 independent dataset proteins, suggesting the usefulness of RLSC method for facilitating the prediction of odorant binding proteins from sequence information.

  12. rVISTA for Comparative Sequence-Based Discovery of Functional Transcription Factor Binding Sites

    Energy Technology Data Exchange (ETDEWEB)

    Loots, Gabriela G.; Ovcharenko, Ivan; Pachter, Lior; Dubchak, Inna; Rubin, Edward M.

    2002-03-08

    Identifying transcriptional regulatory elements represents a significant challenge in annotating the genomes of higher vertebrates. We have developed a computational tool, rVISTA, for high-throughput discovery of cis-regulatory elements that combines transcription factor binding site prediction and the analysis of inter-species sequence conservation. Here, we illustrate the ability of rVISTA to identify true transcription factor binding sites through the analysis of AP-1 and NFAT binding sites in the 1 Mb well-annotated cytokine gene cluster1 (Hs5q31; Mm11). The exploitation of orthologous human-mouse data set resulted in the elimination of 95 percent of the 38,000 binding sites predicted upon analysis of the human sequence alone, while it identified 87 percent of the experimentally verified binding sites in this region.

  13. DNA and RNA Quadruplex-Binding Proteins

    Directory of Open Access Journals (Sweden)

    Václav Brázda

    2014-09-01

    Full Text Available Four-stranded DNA structures were structurally characterized in vitro by NMR, X-ray and Circular Dichroism spectroscopy in detail. Among the different types of quadruplexes (i-Motifs, minor groove quadruplexes, G-quadruplexes, etc., the best described are G-quadruplexes which are featured by Hoogsteen base-paring. Sequences with the potential to form quadruplexes are widely present in genome of all organisms. They are found often in repetitive sequences such as telomeric ones, and also in promoter regions and 5' non-coding sequences. Recently, many proteins with binding affinity to G-quadruplexes have been identified. One of the initially portrayed G-rich regions, the human telomeric sequence (TTAGGGn, is recognized by many proteins which can modulate telomerase activity. Sequences with the potential to form G-quadruplexes are often located in promoter regions of various oncogenes. The NHE III1 region of the c-MYC promoter has been shown to interact with nucleolin protein as well as other G-quadruplex-binding proteins. A number of G-rich sequences are also present in promoter region of estrogen receptor alpha. In addition to DNA quadruplexes, RNA quadruplexes, which are critical in translational regulation, have also been predicted and observed. For example, the RNA quadruplex formation in telomere-repeat-containing RNA is involved in interaction with TRF2 (telomere repeat binding factor 2 and plays key role in telomere regulation. All these fundamental examples suggest the importance of quadruplex structures in cell processes and their understanding may provide better insight into aging and disease development.

  14. Metal ion binding to iron oxides

    Science.gov (United States)

    Ponthieu, M.; Juillot, F.; Hiemstra, T.; van Riemsdijk, W. H.; Benedetti, M. F.

    2006-06-01

    The biogeochemistry of trace elements (TE) is largely dependent upon their interaction with heterogeneous ligands including metal oxides and hydrous oxides of iron. The modeling of TE interactions with iron oxides has been pursued using a variety of chemical models. The objective of this work is to show that it is possible to model the adsorption of protons and TE on a crystallized oxide (i.e., goethite) and on an amorphous oxide (HFO) in an identical way. Here, we use the CD-MUSIC approach in combination with valuable and reliable surface spectroscopy information about the nature of surface complexes of the TE. The other objective of this work is to obtain generic parameters to describe the binding of the following elements (Cd, Co, Cu, Ni, Pb, and Zn) onto both iron oxides for the CD-MUSIC approach. The results show that a consistent description of proton and metal ion binding is possible for goethite and HFO with the same set of model parameters. In general a good prediction of almost all the collected experimental data sets corresponding to metal ion binding to HFO is obtained. Moreover, dominant surface species are in agreement with the recently published surface complexes derived from X-ray absorption spectroscopy (XAS) data. Until more detailed information on the structure of the two iron oxides is available, the present option seems a reasonable approximation and can be used to describe complex geochemical systems. To improve our understanding and modeling of multi-component systems we need more data obtained at much lower metal ion to iron oxide ratios in order to be able to account eventually for sites that are not always characterized in spectroscopic studies.

  15. Ethylene binding to Au/Cu alloy nanoparticles

    Science.gov (United States)

    Gammage, Michael D.; Stauffer, Shannon; Henkelman, Graeme; Becker, Michael F.; Keto, John W.; Kovar, Desiderio

    2016-11-01

    Weak chemisorption of ethylene has been shown to be an important characteristic in the use of metals for the separation of ethylene from ethane. Previously, density functional theory (DFT) has been used to predict the binding energies of various metals and alloys, with Ag having the lowest chemisorption energy amongst the metals and alloys studied. Here Au/Cu alloys are investigated by a combination of DFT calculations and experimental measurements. It is inferred from experiments that the binding energy between a Au/Cu alloy and ethylene is lower than to either of the pure metals, and DFT calculations confirm that this is the case when Au segregates to the particle surface. Implications of this work suggest that it may be possible to further tune the binding energy with ethylene by compositional and morphological control of films produced from Au-surface segregated alloys.

  16. Investigating the Binding of Peptides to Graphene Surfaces for Biosensing Applications

    Science.gov (United States)

    Garley, Amanda; Saikia, Nabanita; Barr, Stephen; Leuty, Gary; Berry, Rajiv; Heinz, Hendrik

    The Air Force Research Lab is focused on developing highly selective and sensitive graphene-based sensors functionalized with peptides for biomolecule detection. To achieve this there is a need to model interfacial binding interactions between the organic and inorganic components to complement ongoing experimental investigations. It is important to characterize the binding behavior of individual amino acids, with the goal of predicting binding of large peptides. Since polarization is important in graphene systems, a new force field which includes polarizability is used. This allows for an in depth exploration of pi-pi interactions, electrostatics and van der Waals forces involved with binding. The binding strength is determined via enthalpy and free energy calculations. Additionally, structural quantities are computed, such as how aromatic rings align with the graphene surface and the arrangement of various residue substituents in relation to the surface and water layers. Computational results are useful in guiding experimental methods focused on rapidly screening optimal peptide sequence for binding.

  17. Computational Prediction of Protein-Protein Interactions of Human Tyrosinase

    Directory of Open Access Journals (Sweden)

    Su-Fang Wang

    2012-01-01

    Full Text Available The various studies on tyrosinase have recently gained the attention of researchers due to their potential application values and the biological functions. In this study, we predicted the 3D structure of human tyrosinase and simulated the protein-protein interactions between tyrosinase and three binding partners, four and half LIM domains 2 (FHL2, cytochrome b-245 alpha polypeptide (CYBA, and RNA-binding motif protein 9 (RBM9. Our interaction simulations showed significant binding energy scores of −595.3 kcal/mol for FHL2, −859.1 kcal/mol for CYBA, and −821.3 kcal/mol for RBM9. We also investigated the residues of each protein facing toward the predicted site of interaction with tyrosinase. Our computational predictions will be useful for elucidating the protein-protein interactions of tyrosinase and studying its binding mechanisms.

  18. 心肌型脂肪酸结合蛋白对血流动力学稳定的急性肺栓塞患者近期预后的预测价值%Value of Heart Fatty Acid Binding Protein in Predicting the Recent Prognosis of Acute Pulmonary Embolism Patients with Stable Hemodynamics

    Institute of Scientific and Technical Information of China (English)

    何磊; 魏庆民

    2012-01-01

    To evaluate the predictive value of heart - type fatty acid - binding protein ( H - FABP ) for the recent prognosis of acute pulmonary embolism patients with stable hemodynamics. Methods Totally 102 patients with MDCT pulmonary artery imaging - confirmed acute pulmonary embolism were enrolled in this study. Patients were divided into two groups according to the serum H - FABP levels: positive groups ( H - FABP ≥10 μg/L, n = 26 ) and negative groups ( H -FABP<10 μg/L, n=76). The symptoms, signs, blood gas profiles, and echocardiography results were recorded and com-pared between these two groups, Furthermore, the major adverse events such as mechanical ventilation and death were also coin-pared. Results The incidences of dyspnea, cyanosis, engorgement of the neck veins, and P2 hyperthyroidism were significantly different between H - FABP positive group and negative group ( P < 0. 05 ). Significant differences were found in terms of PaO2, PaCO2, andP(A-a) O2 (P<0. 05). Indicators for the right ventricular function including the diameter of right ventricle, pulmonary artery pressure, and right ventricular wall motion also showed significant differences ( P < 0. 05 ). The incidences of syncope, shock, right heart dysfunction, fihrinolytic therapy, and mechanical ventilation in the positive group were much higher than those in negative group. Conclusion Plasma H - FABP level can distinguish RV dysfunction to some degree in acute pulmonary embolism patients. Increased H - FABP level predicts poor prognosis and therefore is useful for risk stratification in patients with acute pulmonary embolism.%目的 评价心肌型脂肪酸结合蛋白(H-FABP)对血流动力学稳定的急性肺栓塞(APE)患者近期预后的预测价值.方法 选取2009年8月-2011年12月我院住院的APE患者共102例,均经过多层螺旋CT肺动脉造影确诊.根据血H-FABP测定值分为两组:阳性组:H-FABP≥10 μg/L(n=26),阴性组:H-FABP<10 μg /L(n=76).比较两组患者的

  19. Minimalistic predictor of protein binding energy: contribution of solvation factor to protein binding.

    Science.gov (United States)

    Choi, Jeong-Mo; Serohijos, Adrian W R; Murphy, Sean; Lucarelli, Dennis; Lofranco, Leo L; Feldman, Andrew; Shakhnovich, Eugene I

    2015-02-17

    It has long been known that solvation plays an important role in protein-protein interactions. Here, we use a minimalistic solvation-based model for predicting protein binding energy to estimate quantitatively the contribution of the solvation factor in protein binding. The factor is described by a simple linear combination of buried surface areas according to amino-acid types. Even without structural optimization, our minimalistic model demonstrates a predictive power comparable to more complex methods, making the proposed approach the basis for high throughput applications. Application of the model to a proteomic database shows that receptor-substrate complexes involved in signaling have lower affinities than enzyme-inhibitor and antibody-antigen complexes, and they differ by chemical compositions on interfaces. Also, we found that protein complexes with components that come from the same genes generally have lower affinities than complexes formed by proteins from different genes, but in this case the difference originates from different interface areas. The model was implemented in the software PYTHON, and the source code can be found on the Shakhnovich group webpage: http://faculty.chemistry.harvard.edu/shakhnovich/software. PMID:25692584

  20. A probabilistic approach to microRNA-target binding

    Energy Technology Data Exchange (ETDEWEB)

    Ogul, Hasan, E-mail: hogul@baskent.edu.tr [Department of Computer Engineering, Baskent University, Baglica TR-06810, Ankara (Turkey); Umu, Sinan U. [Department of Chemistry, Middle East Technical University, Cankaya TR-06800, Ankara (Turkey); Bioinformatics Program, Informatics Institute, Middle East Technical University, Cankaya TR-06800, Ankara (Turkey); Tuncel, Y. Yener [Bioinformatics Program, Informatics Institute, Middle East Technical University, Cankaya TR-06800, Ankara (Turkey); Akkaya, Mahinur S. [Department of Chemistry, Middle East Technical University, Cankaya TR-06800, Ankara (Turkey)

    2011-09-16

    Highlights: {yields} A new probabilistic model is introduced for microRNA-target binding. {yields} The new model significantly outperforms RNAHybrid and miRTif. {yields} The experiments can unveil the effects of the type and directions of distinct base pairings. -- Abstract: Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interactions of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set-up a probabilistic model to explain the binding preferences between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new sequence and defines the likelihood of this sequence using a Variable Length Markov Chain. It offers a complementary representation of microRNA-mRNA pairs for microRNA target prediction tools or other probabilistic frameworks of integrative gene regulation analysis. The performance of present model is evaluated by its ability to predict microRNA-target mRNA interaction given a mature microRNA sequence and a putative mRNA binding site. In regard to classification accuracy, it outperforms two recent methods based on thermodynamic stability and sequence complementarity. The experiments can also unveil the effects of base pairing types and non-seed region in duplex formation.

  1. Probing protein phosphatase substrate binding

    DEFF Research Database (Denmark)

    Højlys-Larsen, Kim B.; Sørensen, Kasper Kildegaard; Jensen, Knud Jørgen;

    2012-01-01

    profile of the integrin-linked kinase associated phosphatase (ILKAP), a member of the protein phosphatase 2C (PP2C) family. Phosphatases can potentially dephosphorylate these phosphopeptide substrates but, interestingly, performing the binding studies at 4 °C allowed efficient binding to phosphopeptides...... around the phosphorylated residue are important for the binding affinity of ILKAP. We conclude that solid-phase affinity pull-down of proteins from complex mixtures can be applied in phosphoproteomics and systems biology.......Proteomics and high throughput analysis for systems biology can benefit significantly from solid-phase chemical tools for affinity pull-down of proteins from complex mixtures. Here we report the application of solid-phase synthesis of phosphopeptides for pull-down and analysis of the affinity...

  2. Water binding in legume seeds

    Science.gov (United States)

    Vertucci, C. W.; Leopold, A. C.

    1987-01-01

    The physical status of water in seeds has a pivotal role in determining the physiological reactions that can take place in the dry state. Using water sorption isotherms from cotyledon and axis tissue of five leguminous seeds, the strength of water binding and the numbers of binding sites have been estimated using van't Hoff analyses and the D'Arcy/Watt equation. These parameters of water sorption are calculated for each of the three regions of water binding and for a range of temperatures. Water sorption characteristics are reflective of the chemical composition of the biological materials as well as the temperature at which hydration takes place. Changes in the sorption characteristics with temperature and hydration level may suggest hydration-induced structural changes in cellular components.

  3. PRISM offers a comprehensive genomic approach to transcription factor function prediction

    KAUST Repository

    Wenger, A. M.

    2013-02-04

    The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

  4. Shared binding sites in Lepidoptera for Bacillus thuringiensis Cry1Ja and Cry1A toxins.

    Science.gov (United States)

    Herrero, S; González-Cabrera, J; Tabashnik, B E; Ferré, J

    2001-12-01

    Bacillus thuringiensis toxins act by binding to specific target sites in the insect midgut epithelial membrane. The best-known mechanism of resistance to B. thuringiensis toxins is reduced binding to target sites. Because alteration of a binding site shared by several toxins may cause resistance to all of them, knowledge of which toxins share binding sites is useful for predicting cross-resistance. Conversely, cross-resistance among toxins suggests that the toxins share a binding site. At least two strains of diamondback moth (Plutella xylostella) with resistance to Cry1A toxins and reduced binding of Cry1A toxins have strong cross-resistance to Cry1Ja. Thus, we hypothesized that Cry1Ja shares binding sites with Cry1A toxins. We tested this hypothesis in six moth and butterfly species, each from a different family: Cacyreus marshalli (Lycaenidae), Lobesia botrana (Tortricidae), Manduca sexta (Sphingidae), Pectinophora gossypiella (Gelechiidae), P. xylostella (Plutellidae), and Spodoptera exigua (Noctuidae). Although the extent of competition varied among species, experiments with biotinylated Cry1Ja and radiolabeled Cry1Ac showed that Cry1Ja and Cry1Ac competed for binding sites in all six species. A recent report also indicates shared binding sites for Cry1Ja and Cry1A toxins in Heliothis virescens (Noctuidae). Thus, shared binding sites for Cry1Ja and Cry1A occur in all lepidopteran species tested so far. PMID:11722929

  5. Skyrmions with low binding energies

    Directory of Open Access Journals (Sweden)

    Mike Gillard

    2015-06-01

    Full Text Available Nuclear binding energies are investigated in two variants of the Skyrme model: the first replaces the usual Skyrme term with a term that is sixth order in derivatives, and the second includes a potential that is quartic in the pion fields. Solitons in the first model are shown to deviate significantly from ansätze previously assumed in the literature. The binding energies obtained in both models are lower than those obtained from the standard Skyrme model, and those obtained in the second model are close to the experimental values.

  6. Skyrmions with low binding energies

    Energy Technology Data Exchange (ETDEWEB)

    Gillard, Mike, E-mail: m.n.gillard@leeds.ac.uk; Harland, Derek, E-mail: d.g.harland@leeds.ac.uk; Speight, Martin, E-mail: speight@maths.leeds.ac.uk

    2015-06-15

    Nuclear binding energies are investigated in two variants of the Skyrme model: the first replaces the usual Skyrme term with a term that is sixth order in derivatives, and the second includes a potential that is quartic in the pion fields. Solitons in the first model are shown to deviate significantly from ansätze previously assumed in the literature. The binding energies obtained in both models are lower than those obtained from the standard Skyrme model, and those obtained in the second model are close to the experimental values.

  7. POVME: An Algorithm for Measuring Binding-Pocket Volumes

    OpenAIRE

    Durrant, Jacob D; de Oliveira, César Augusto F; McCammon, J. Andrew

    2010-01-01

    Researchers engaged in computer-aided drug design often wish to measure the volume of a ligand-binding pocket in order to predict pharmacology. We have recently developed a simple algorithm, called POVME (POcket Volume MEasurer), for this purpose. POVME is Python implemented, fast, and freely available. To demonstrate its utility, we use the new algorithm to study three members of the matrix-metalloproteinase family of proteins. Despite the structural similarity of these proteins, differences...

  8. EPR studies of cooperative binding of Cu (II) to hemoglobin

    International Nuclear Information System (INIS)

    The investigation of the relative affinities of the two pairs of hemoglobin copper sites by monitoring the EPR spectra of the complexes formed by the reaction of copper with deoxyhemoglobin is reported. A model in which two sites are assumed to accept copper ions in a noncooperative way is not able to predict the experimental results. Thus it is conclude that the binding of these ions to hemoglobin is a cooperative phenomenon. (Author)

  9. On the influence of reward on action-effect binding.

    Science.gov (United States)

    Muhle-Karbe, Paul S; Krebs, Ruth M

    2012-01-01

    Ideomotor theory states that the formation of anticipatory representations about the perceptual consequences of an action [i.e., action-effect (A-E) binding] provides the functional basis of voluntary action control. A host of studies have demonstrated that A-E binding occurs fast and effortlessly, yet little is known about cognitive and affective factors that influence this learning process. In the present study, we sought to test whether the motivational value of an action modulates the acquisition of A-E associations. To this end, we linked specific actions with monetary incentives during the acquisition of novel A-E mappings. In a subsequent test phase, the degree of binding was assessed by presenting the former effect stimuli as task-irrelevant response primes in a forced-choice response task, absent reward. Binding, as indexed by response priming through the former action-effects, was only found for reward-related A-E mappings. Moreover, the degree to which reward associations modulated the binding strength was predicted by individuals' trait sensitivity to reward. These observations indicate that the association of actions and their immediate outcomes depends on the motivational value of the action during learning, as well as on the motivational disposition of the individual. On a larger scale, these findings also highlight the link between ideomotor theories and reinforcement-learning theories, providing an interesting perspective for future research on anticipatory regulation of behavior.

  10. On the influence of reward on action-effect binding

    Directory of Open Access Journals (Sweden)

    Paul Simon Muhle-Karbe

    2012-11-01

    Full Text Available Ideomotor theory states that the formation of anticipatory representations about the perceptual consequences of an action (i.e. action-effect (A-E binding provides the functional basis of voluntary action control. A host of studies has demonstrated that A-E binding occurs fast and effortlessly, yet only little is known about cognitive and affective factors that influence this learning process. In the present study, we sought to test whether the motivational value of an action modulates the acquisition of A-E associations. To this end, we associated specific actions with monetary incentives during the acquisition of novel A-E mappings. In a subsequent test phase, the degree of binding was assessed by presenting the former effect stimuli as task-irrelevant response primes in a forced-choice response task in the absence of any reward. Binding, as indexed by response priming through the former action effects, was only found for reward-related A-E mappings. Moreover, the degree to which reward associations modulated the binding strength was predicted by individuals’ trait sensitivity to reward. These observations indicate that the association of actions and their immediate outcomes depends on the motivational value of the action during learning, as well as on the motivational disposition of the individual. On a larger scale, these findings also highlight the link between ideomotor theories and reinforcement-learning theories, providing an interesting perspective for future research on anticipatory regulation of behavior.

  11. On the influence of reward on action-effect binding.

    Science.gov (United States)

    Muhle-Karbe, Paul S; Krebs, Ruth M

    2012-01-01

    Ideomotor theory states that the formation of anticipatory representations about the perceptual consequences of an action [i.e., action-effect (A-E) binding] provides the functional basis of voluntary action control. A host of studies have demonstrated that A-E binding occurs fast and effortlessly, yet little is known about cognitive and affective factors that influence this learning process. In the present study, we sought to test whether the motivational value of an action modulates the acquisition of A-E associations. To this end, we linked specific actions with monetary incentives during the acquisition of novel A-E mappings. In a subsequent test phase, the degree of binding was assessed by presenting the former effect stimuli as task-irrelevant response primes in a forced-choice response task, absent reward. Binding, as indexed by response priming through the former action-effects, was only found for reward-related A-E mappings. Moreover, the degree to which reward associations modulated the binding strength was predicted by individuals' trait sensitivity to reward. These observations indicate that the association of actions and their immediate outcomes depends on the motivational value of the action during learning, as well as on the motivational disposition of the individual. On a larger scale, these findings also highlight the link between ideomotor theories and reinforcement-learning theories, providing an interesting perspective for future research on anticipatory regulation of behavior. PMID:23130005

  12. Prediction of epitopes using neural network based methods

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2011-01-01

    In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We have updated the prediction servers, NetMHC-3.2, NetMHCpan-2.2, and a new consensus method, NetMHCcons, which, in their previous versions, hav...

  13. Synthetic heparin-binding growth factor analogs

    Science.gov (United States)

    Pena, Louis A.; Zamora, Paul; Lin, Xinhua; Glass, John D.

    2007-01-23

    The invention provides synthetic heparin-binding growth factor analogs having at least one peptide chain that binds a heparin-binding growth factor receptor, covalently bound to a hydrophobic linker, which is in turn covalently bound to a non-signaling peptide that includes a heparin-binding domain. The synthetic heparin-binding growth factor analogs are useful as soluble biologics or as surface coatings for medical devices.

  14. Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

    Directory of Open Access Journals (Sweden)

    Selvaraj S

    2011-10-01

    Full Text Available Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as binding propensity, neighboring residues in the vicinity of binding sites, conservation score and conformational switching. Results We observed that the binding propensities of amino acid residues are specific for protein-protein complexes. Further, typical dipeptides and tripeptides showed high preference for binding, which is unique to protein-protein complexes. Most of the binding site residues are highly conserved among homologous sequences. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. Conclusions The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.

  15. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

    Science.gov (United States)

    Gomes, Antonio L C; Wang, Harris H

    2016-04-01

    ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology. PMID:27104615

  16. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

    Directory of Open Access Journals (Sweden)

    Antonio L C Gomes

    2016-04-01

    Full Text Available ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.

  17. Ligand-binding properties of the carboxyl-terminal repeat domain of Streptococcus mutans glucan-binding protein A.

    Science.gov (United States)

    Haas, W; Banas, J A

    2000-02-01

    Streptococcus mutans glucan-binding protein A (GbpA) has sequence similarity in its carboxyl-terminal domain with glucosyltransferases (GTFs), the enzymes responsible for catalyzing the synthesis of the glucans to which GbpA and GTFs can bind and which promote S. mutans attachment to and accumulation on the tooth surface. It was predicted that this C-terminal region, comprised of what have been termed YG repeats, represents the GbpA glucan-binding domain (GBD). In an effort to test this hypothesis and to quantitate the ligand-binding specificities of the GbpA GBD, several fusion proteins were generated and tested by affinity electrophoresis or by precipitation of protein-ligand complexes, allowing the determination of binding constants. It was determined that the 16 YG repeats in GbpA comprise its GBD and that GbpA has a greater affinity for dextran (a water-soluble form of glucan) than for mutan (a water-insoluble form of glucan). Placement of the GBD at the carboxyl terminus was necessary for maximum glucan binding, and deletion of as few as two YG repeats from either end of the GBD reduced the affinity for dextran by over 10-fold. Interestingly, the binding constant of GbpA for dextran was 34-fold higher than that calculated for the GBDs of two S. mutans GTFs, one of which catalyzes the synthesis of water-soluble glucan and the other of which catalyzes the synthesis of water-insoluble glucan. PMID:10633107

  18. Sex hormone binding globulin phenotypes

    DEFF Research Database (Denmark)

    Cornelisse, M M; Bennett, Patrick; Christiansen, M;

    1994-01-01

    Human sex hormone binding globulin (SHBG) is encoded by a normal and a variant allele. The resulting SHBG phenotypes (the homozygous normal SHBG, the heterozygous SHBG and the homozygous variant SHBG phenotype) can be distinguished by their electrophoretic patterns. We developed a novel detection...

  19. BINDING ISOTHERMS SURFACTANT-PROTEINS

    OpenAIRE

    Elena Irina Moater; Cristiana Radulescu; Ionica Ionita

    2011-01-01

    The interactions between surfactants and proteins shows some similarities with interactions between surfactants and polymers, but the hydrophobic amphoteric nature of proteins and their secondary and tertiary structure components make them different from conventional polymer systems. Many studies from the past about surfactant - proteins bonding used the dialysis techniques. Other techniques used to determine the binding isotherm, included ultrafiltration, ultracentrifugation, potentiometry, ...

  20. Cellulose binding domain fusion proteins

    Energy Technology Data Exchange (ETDEWEB)

    Shoseyov, Oded (Karmey Yosef, IL); Shpiegl, Itai (Rehovot, IL); Goldstein, Marc A. (Davis, CA); Doi, Roy H. (Davis, CA)

    1998-01-01

    A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production thereof. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques.

  1. DNA-MATRIX: a tool for constructing transcription factor binding sites Weight matrix

    Directory of Open Access Journals (Sweden)

    Chandra Prakash Singh,

    2009-12-01

    Full Text Available Despite considerable effort to date, DNA transcription factor binding sites prediction in whole genome remains a challenge for the researchers. Currently the genome wide transcription factor binding sites prediction tools required either direct pattern sequence or weight matrix. Although there are known transcription factor binding sites pattern databases and tools for genome level prediction but no tool for weight matrix construction. Considering this, we developed a DNA-MATRIX tool for searching putative transcription factor binding sites in genomic sequences. DNA-MATRIX uses the simple heuristic approach for weight matrix construction, which can be transformed into different formats as per the requirement of researcher’s for further genome wide prediction and therefore provides the possibility to identify the conserved known DNA binding sites in the coregulated genes and also to search for a great variety of different regulatory binding patterns. The user may construct and save specific weight or frequency matrices in different formats derived through user selected set of known motif sequences.

  2. From face to interface recognition: a differential geometric approach to distinguish DNA from RNA binding surfaces.

    Science.gov (United States)

    Shazman, Shula; Elber, Gershon; Mandel-Gutfreund, Yael

    2011-09-01

    Protein nucleic acid interactions play a critical role in all steps of the gene expression pathway. Nucleic acid (NA) binding proteins interact with their partners, DNA or RNA, via distinct regions on their surface that are characterized by an ensemble of chemical, physical and geometrical properties. In this study, we introduce a novel methodology based on differential geometry, commonly used in face recognition, to characterize and predict NA binding surfaces on proteins. Applying the method on experimentally solved three-dimensional structures of proteins we successfully classify double-stranded DNA (dsDNA) from single-stranded RNA (ssRNA) binding proteins, with 83% accuracy. We show that the method is insensitive to conformational changes that occur upon binding and can be applicable for de novo protein-function prediction. Remarkably, when concentrating on the zinc finger motif, we distinguish successfully between RNA and DNA binding interfaces possessing the same binding motif even within the same protein, as demonstrated for the RNA polymerase transcription-factor, TFIIIA. In conclusion, we present a novel methodology to characterize protein surfaces, which can accurately tell apart dsDNA from an ssRNA binding interfaces. The strength of our method in recognizing fine-tuned differences on NA binding interfaces make it applicable for many other molecular recognition problems, with potential implications for drug design.

  3. Structures and Functions Prediction and Expression Profiles of Calreticulin as Calcium Binding Chaperones in Chicken%鸡钙离子结合分子伴侣Calreticulin的结构与功能预测及组织表达特性

    Institute of Scientific and Technical Information of China (English)

    王丽丽; 李楠; 曹嫦妤; 龚都强; 于东; 王伟; 李金龙

    2014-01-01

    内的终端非还原性α-L-阿拉伯呋喃糖苷残基的水解,作用于α-L-阿拉伯呋喃糖苷、含(1,3)和/或(1,5)糖苷键的阿拉伯聚糖、阿拉伯木聚糖和阿拉伯半乳聚糖,能与糖类分子及Ca2+特异性结合,可监控糖蛋白组装折叠及Ca2+调控,且在消化系统中发挥重要作用。%[Objective] The aim of the current study is to reveal the evolutionary relationships, and investigate the protein structure and functions and the expression profiles of calreticulin (CRT) as a key Ca2+ binding molecular chaperone within the endoplasmic reticulum (ER) of chicken.[Method]The nucleotides and amino acids of CRT in 12 species of vertebrates recorded in Gene bank were analyzed for evolutionary relationships by Laser Gene, and the structures and functions of CRT protein in chicken were predicted by bioinformatics, and the expression profiles of CRT in 30 organizations of chicken was analyzed by real-time PCR.[Result]Results of homology analysis showed that compared with the other 11 species of nucleotide sequences of CRT gene in chicken, gallus gallus and oryctolagus cuniculus had the highest nucleotide sequence homology, which was 78.7%, in addition, gallus gallus and oncorhynchus mykiss had the lowest homology, which was 70.5%. In the homology of amino acid sequences, the relationship between gallus gallus and crotalus adamanteus cadam is the closest by 85.0%, and the furthest relationships with gallus gallus is oncorhynchus mykiss which was 69.0% in amino acid sequence, besides, the homology of gallus gallus with cricetulus griseus, macaca mulatta, homo sapiens, oryctolagus cuniculus, sus scrofa, bos taurus, and xenopus (silurana) tropicalisis relatively close to almost above 80.1%. The protein structure and function prediction revealed that the CRT of chicken was constitute with 404 amino acids, and had a relative molecular mass of 46.8802 kD and a theoretical isoelectric point of 4.41, moreover, the negative charge

  4. Effects of unilateral 6-OHDA lesions on [3H]-N-propylnorapomorphine binding in striatum ex vivo and vulnerability to amphetamine-evoked dopamine release in rat

    DEFF Research Database (Denmark)

    Palner, Mikael; Kjaerby, Celia; Knudsen, Gitte M;

    2011-01-01

    in a preferential increase in agonist binding, and a lesser competition from residual dopamine to the agonist binding. To test this hypothesis we used autoradiography to measure [(3)H]NPA and [(3)H]raclopride binding sites in hemi-parkinsonian rats with unilateral 6-OHDA lesions, with and without amphetamine...... challenge. Unilateral lesions were associated with a more distinct increase in [(3)H]NPA binding ex vivo than was seen for [(3)H]raclopride binding in vitro. Furthermore, this preferential asymmetry in [(3)H]NPA binding was more pronounced in amphetamine treated rats. We consequently predict that agonist...

  5. Protein binding assay for hyaluronate

    Energy Technology Data Exchange (ETDEWEB)

    Lacy, B.E.; Underhill, C.B.

    1986-11-01

    A relatively quick and simple assay for hyaluronate was developed using the specific binding protein, hyaluronectin. The hyaluronectin was obtained by homogenizing the brains of Sprague-Dawley rats, and then centrifuging the homogenate. The resulting supernatant was used as a source of crude hyaluronectin. In the binding assay, the hyaluronectin was mixed with (/sup 3/H)hyaluronate, followed by an equal volume of saturated (NH/sub 4/)/sub 2/SO/sub 4/, which precipitated the hyaluronectin and any (/sup 3/H)hyaluronate associated with it, but left free (/sup 3/H)hyaluronate in solution. The mixture was then centrifuged, and the amount of bound (/sup 3/H)hyaluronate in the precipitate was determined. Using this assay, the authors found that hyaluronectin specifically bound hyaluronate, since other glycosaminoglycans failed to compete for the binding protein. In addition, the interaction between hyaluronectin and hyaluronate was of relatively high affinity, and the size of the hyaluronate did not appear to substantially alter the amount of binding. To determine the amount of hyaluronate in an unknown sample, they used a competition assay in which the binding of a set amount of (/sup 3/H)hyaluronate was blocked by the addition of unlabeled hyaluronate. By comparing the degree of competition of the unknown samples with that of known amounts of hyaluronate, it was possible to determine the amount of hyaluronate in the unknowns. They have found that this method is sensitive to 1 ..mu..g or less of hyaluronate, and is unaffected by the presence of proteins.

  6. Structure, Function, and Evolution of Biogenic Amine-binding Proteins in Soft Ticks

    Energy Technology Data Exchange (ETDEWEB)

    Mans, Ben J.; Ribeiro, Jose M.C.; Andersen, John F. (NIH)

    2008-08-19

    Two highly abundant lipocalins, monomine and monotonin, have been isolated from the salivary gland of the soft tick Argas monolakensis and shown to bind histamine and 5-hydroxytryptamine (5-HT), respectively. The crystal structures of monomine and a paralog of monotonin were determined in the presence of ligands to compare the determinants of ligand binding. Both the structures and binding measurements indicate that the proteins have a single binding site rather than the two sites previously described for the female-specific histamine-binding protein (FS-HBP), the histamine-binding lipocalin of the tick Rhipicephalus appendiculatus. The binding sites of monomine and monotonin are similar to the lower, low affinity site of FS-HBP. The interaction of the protein with the aliphatic amine group of the ligand is very similar for the all of the proteins, whereas specificity is determined by interactions with the aromatic portion of the ligand. Interestingly, protein interaction with the imidazole ring of histamine differs significantly between the low affinity binding site of FS-HBP and monomine, suggesting that histamine binding has evolved independently in the two lineages. From the conserved features of these proteins, a tick lipocalin biogenic amine-binding motif could be derived that was used to predict biogenic amine-binding function in other tick lipocalins. Heterologous expression of genes from salivary gland libraries led to the discovery of biogenic amine-binding proteins in soft (Ornithodoros) and hard (Ixodes) tick genera. The data generated were used to reconstruct the most probable evolutionary pathway for the evolution of biogenic amine-binding in tick lipocalins.

  7. Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

    OpenAIRE

    Selvaraj S; Jayaram B; Saranya N; Gromiha M; Fukui Kazuhiko

    2011-01-01

    Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such...

  8. Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1.

    Science.gov (United States)

    Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong; Cho, Sung-Hwan; Xu, Dong; Stacey, Gary

    2016-01-01

    DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecular interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. The in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues. PMID:27583834

  9. Antimicrobial Peptide-Lipid Binding Interactions and Binding Selectivity

    OpenAIRE

    Lad, Mitaben D.; Birembaut, Fabrice; Clifton, Luke A.; Frazier, Richard A.; Webster, John R. P.; Green, Rebecca J.

    2007-01-01

    Surface pressure measurements, external reflection-Fourier transform infrared spectroscopy, and neutron reflectivity have been used to investigate the lipid-binding behavior of three antimicrobial peptides: melittin, magainin II, and cecropin P1. As expected, all three cationic peptides were shown to interact more strongly with the anionic lipid, 1,2 dihexadecanoyl-sn-glycerol-3-(phosphor-rac-(1-glycerol)) (DPPG), compared to the zwitterionic lipid, 1,2 dihexadecanoyl-sn-glycerol-3-phosphocho...

  10. A Cohesive and Integrated Platform for Immunogenicity Prediction.

    Science.gov (United States)

    Dimitrov, Ivan; Atanasova, Mariyana; Patronov, Atanas; Flower, Darren R; Doytchinova, Irini

    2016-01-01

    In silico methods for immunogenicity prediction mine the enormous quantity of data arising from deciphered genomes and proteomes to identify immunogenic proteins. While high and productive immunogenicity is essential for vaccines, therapeutic proteins and monoclonal antibodies should be minimally immunogenic. Here, we present a cohesive platform for immunogenicity and MHC class I and/or II binding affinity prediction. The platform integrates three quasi-independent modular servers: VaxiJen, EpiJen, and EpiTOP. VaxiJen (http://www.ddg-pharmfac.net/vaxijen) predicts immunogenicity of proteins of different origin; EpiJen (http://www.ddg-pharmfac.net/epijen) predicts peptide binding to MHC class I proteins; and EpiTOP (http://www.ddg-pharmfac.net/epitop) predicts peptide binding to MHC class II proteins. The platform is freely accessible and user-friendly. The protocol for immunogenicity prediction is demonstrated by selecting immunogenic proteins from Mycobacterium tuberculosis and predicting how the peptide epitopes within them bind to MHC class I and class II proteins. PMID:27076336

  11. Characteristics of human erythrocyte insulin binding sites.

    OpenAIRE

    Okada, Yoshio

    1981-01-01

    Insulin and human erythrocyte cell membrane interactions were studied with respect to binding and dissociation. The per cent of specific binding of 125I-labeled insulin to erythrocytes was directly proportional to the cell concentration. The optimum pH for binding was 8.1. The initial binding rate was directly proportional to, and the steady state insulin binding was reversely proportional to, the incubation temperature. The per cent of specific binding of 125I-labeled insulin was 12.10 +/- 1...

  12. Self-peptides with intermediate capacity to bind and stabilize MHC class I molecules may be immunogenic

    DEFF Research Database (Denmark)

    Andersen, M L M; Ruhwald, Morten; Nissen, M H;

    2003-01-01

    Thirty self-peptides were selected on the basis of their predicted binding to H-2b molecules. The binding of peptides was ascertained experimentally by biochemical (KD measurements) and cellular [major histocompatibility complex class I (MHC-I) stabilization] assays. A weak, but significant, corr...

  13. Structural and histone binding ability characterizations of human PWWP domains.

    Directory of Open Access Journals (Sweden)

    Hong Wu

    Full Text Available BACKGROUND: The PWWP domain was first identified as a structural motif of 100-130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain 'Royal Family', which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently. METHODOLOGY/PRINCIPAL FINDINGS: The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other 'Royal Family' members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3. CONCLUSIONS: PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical β-barrel core, an insertion motif between the second and third β-strands and a C-terminal α-helix bundle. Both the canonical β-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones. ENHANCED VERSION: This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web

  14. NetMHCcons: a consensus method for the major histocompatibility complex class I predictions

    DEFF Research Database (Denmark)

    Karosiene, Edita; Lundegaard, Claus; Lund, Ole;

    2012-01-01

    A key role in cell-mediated immunity is dedicated to the major histocompatibility complex (MHC) molecules that bind peptides for presentation on the cell surface. Several in silico methods capable of predicting peptide binding to MHC class I have been developed. The accuracy of these methods...... depends on the data available characterizing the binding specificity of the MHC molecules. It has, moreover, been demonstrated that consensus methods defined as combinations of two or more different methods led to improved prediction accuracy. This plethora of methods makes it very difficult for the non......-expert user to choose the most suitable method for predicting binding to a given MHC molecule. In this study, we have therefore made an in-depth analysis of combinations of three state-of-the-art MHC–peptide binding prediction methods (NetMHC, NetMHCpan and PickPocket). We demonstrate that a simple...

  15. Characterization of a fatty acid-binding protein from rat heart.

    Science.gov (United States)

    Offner, G D; Troxler, R F; Brecher, P

    1986-04-25

    A fatty acid-binding protein has been isolated from rat heart and purified by gel filtration chromatography on Sephadex G-75 and anion-exchange chromatography on DE52. The circular dichroic spectrum of this protein was not affected by protein concentration, suggesting that it does not aggregate into multimers. Computer analyses of the circular dichroic spectrum predicted that rat heart fatty acid-binding protein contains approximately 22% alpha-helix, 45% beta-form and 33% unordered structure. Immunological studies showed that the fatty acid-binding proteins from rat heart and rat liver are immunochemically unrelated. The amino acid composition and partial amino acid sequence of the heart protein indicated that it is structurally related to, but distinct from, other fatty acid-binding proteins from liver, intestine, and 3T3 adipocytes. Using a binding assay which measures the transfer of fatty acids between donor liposomes and protein (Brecher, P., Saouaf, R., Sugarman, J. M., Eisenberg, D., and LaRosa, K. (1984) J. Biol. Chem. 259, 13395-13401), it was shown that both rat heart and liver fatty acid-binding proteins bind 2 mol of oleic acid or palmitic acid/mol of protein. The structural and functional relationship of rat heart fatty acid-binding protein to fatty acid-binding proteins from other tissues is discussed. PMID:3957934

  16. Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively.

    Science.gov (United States)

    Clifford, Jacob; Adami, Christoph

    2015-09-02

    Transcription factor binding to the surface of DNA regulatory regions is one of the primary causes of regulating gene expression levels. A probabilistic approach to model protein-DNA interactions at the sequence level is through position weight matrices (PWMs) that estimate the joint probability of a DNA binding site sequence by assuming positional independence within the DNA sequence. Here we construct conditional PWMs that depend on the motif signatures in the flanking DNA sequence, by conditioning known binding site loci on the presence or absence of additional binding sites in the flanking sequence of each site's locus. Pooling known sites with similar flanking sequence patterns allows for the estimation of the conditional distribution function over the binding site sequences. We apply our model to the Dorsal transcription factor binding sites active in patterning the Dorsal-Ventral axis of Drosophila development. We find that those binding sites that cooperate with nearby Twist sites on average contain about 0.5 bits of information about the presence of Twist transcription factor binding sites in the flanking sequence. We also find that Dorsal binding site detectors conditioned on flanking sequence information make better predictions about what is a Dorsal site relative to background DNA than detection without information about flanking sequence features.

  17. Dissection of the Critical Binding Determinants of Cellular Retinoic Acid Binding Protein II by Mutagenesis and Fluorescence Binding Assay

    OpenAIRE

    Vasileiou, Chrysoula; Lee, Kin Sing Stephen; Crist, Rachael M.; Vaezeslami, Soheila; Goins, Sarah M.; Geiger, James H.; Borhan, Babak

    2009-01-01

    The binding of retinoic acid to mutants of Cellular Retinoic Acid Binding Protein II (CRABPII) was evaluated to better understand the importance of the direct protein/ligand interactions. The important role of Arg111 for the correct structure and function of the protein was verified and other residues that directly affect retinoic acid binding have been identified. Furthermore, retinoic acid binding to CRABPII mutants that lack all previously identified interacting amino acids was rescued by ...

  18. Human plasminogen binding protein tetranectin

    DEFF Research Database (Denmark)

    Kastrup, J S; Rasmussen, H; Nielsen, B B;

    1997-01-01

    The recombinant human plasminogen binding protein tetranectin (TN) and the C-type lectin CRD of this protein (TN3) have been crystallized. TN3 crystallizes in the tetragonal space group P4(2)2(1)2 with cell dimensions a = b = 64.0, c = 75.7 A and with one molecule per asymmetric unit. The crystals...... to at least 2.5 A. A full data set has been collected to 3.0 A. The asymmetric unit contains one monomer of TN. Molecular replacement solutions for TN3 and TN have been obtained using the structure of the C-type lectin CRD of rat mannose-binding protein as search model. The rhombohedral space group indicates...

  19. Optical property of iron binding to Suwannee River fulvic acid.

    Science.gov (United States)

    Yan, Mingquan; Li, Mingyang; Wang, Dongsheng; Xiao, Feng

    2013-05-01

    In this work, absorbance and fluorescence spectra were used to study iron binding to standard Suwannee River fulvic acid (SRFA). The differential logarithm-transformed absorbance and fluorescence spectra of SRFA induced by iron binding were processed to examine the nature of the observed phenomena and to investigate the contributions of discrete binding sites present in SRFA. Both the Fe-differential log-transformed absorbance and fluorescence were well correlated to the bound iron concentrations predicted based on the Non-ideal Competitive Adsorption (NICA-Donnan) model at iron concentrations below 10.0μM (R(2)>0.99 for absorbance and R(2)>0.97 for fluorescence) and over a wide pH range of 3.5-8.0. At pH3.5, both the Fe-differential log-transformed absorbance and fluorescence vs. iron bound spectra exhibited significantly lower slopes than those at pH5.0, 7.0, and 8.0. These results suggest that a different set of complexation-active chromophores and fluorophores are responsible for iron binding at low pH values or that the NICA-Donnan model is limited at low pH. Because phenolic and carboxylic complex sites of different fluorophores respond to iron quenching, the fluorescence data indicate three stages of iron binding to phenolic, carboxylic, and Donnan gels (electrostatic interactions) in SRFA (with R(2)>0.99 at each stage). The agreement between observations from spectroscopic indices and established metal-binding models shows that the absorbance and fluorescence spectra provide important information about the involvement of metal complexation of specific functional groups typical for fulvic acids. PMID:23499223

  20. Binding effects and nuclear shadowing

    OpenAIRE

    Indumathi, D.; Wei ZHU

    1996-01-01

    The effects of nuclear binding on nuclear structure functions have so far been studied mainly at fixed target experiments, and there is currently much interest in obtaining a clearer understanding of this phenomenon. We use an existing dynamical model of nuclear structure functions, that gives good agreement with current data, to study this effect in a kinematical regime (low $x$, high $Q^2$) that can possibly be probed by an upgrade of {\\sc hera} at {\\sc desy} into a nuclear accelerator.

  1. Calcium binding by dietary fibre

    International Nuclear Information System (INIS)

    Dietary fibre from plants low in phytate bound calcium in proportion to its uronic-acid content. This binding by the non-cellulosic fraction of fibre reduces the availability of calcium for small-intestinal absorption, but the colonic microbial digestion of uronic acids liberates the calcium. Thus the ability to maintain calcium balance on high-fibre diets may depend on the adaptive capacity on the colon for calcium. (author)

  2. Material Binding Peptides for Nanotechnology

    Directory of Open Access Journals (Sweden)

    Urartu Ozgur Safak Seker

    2011-02-01

    Full Text Available Remarkable progress has been made to date in the discovery of material binding peptides and their utilization in nanotechnology, which has brought new challenges and opportunities. Nowadays phage display is a versatile tool, important for the selection of ligands for proteins and peptides. This combinatorial approach has also been adapted over the past decade to select material-specific peptides. Screening and selection of such phage displayed material binding peptides has attracted great interest, in particular because of their use in nanotechnology. Phage display selected peptides are either synthesized independently or expressed on phage coat protein. Selected phage particles are subsequently utilized in the synthesis of nanoparticles, in the assembly of nanostructures on inorganic surfaces, and oriented protein immobilization as fusion partners of proteins. In this paper, we present an overview on the research conducted on this area. In this review we not only focus on the selection process, but also on molecular binding characterization and utilization of peptides as molecular linkers, molecular assemblers and material synthesizers.

  3. Anion binding in biological systems

    Science.gov (United States)

    Feiters, Martin C.; Meyer-Klaucke, Wolfram; Kostenko, Alexander V.; Soldatov, Alexander V.; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Küpper, Frithjof C.; Hollenstein, Kaspar; Locher, Kaspar P.; Bevers, Loes E.; Hagedoorn, Peter-Leon; Hagen, Wilfred R.

    2009-11-01

    We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L3 (2p3/2) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

  4. Anion binding in biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Feiters, Martin C [Department of Organic Chemistry, Institute for Molecules and Materials, Faculty of Science, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen (Netherlands); Meyer-Klaucke, Wolfram [EMBL Hamburg Outstation at DESY, Notkestrasse 85, D-22607 Hamburg (Germany); Kostenko, Alexander V; Soldatov, Alexander V [Faculty of Physics, Southern Federal University, Sorge 5, Rostov-na-Donu, 344090 (Russian Federation); Leblanc, Catherine; Michel, Gurvan; Potin, Philippe [Centre National de la Recherche Scientifique and Universite Pierre et Marie Curie Paris-VI, Station Biologique de Roscoff, Place Georges Teissier, BP 74, F-29682 Roscoff cedex, Bretagne (France); Kuepper, Frithjof C [Scottish Association for Marine Science, Dunstaffnage Marine Laboratory, Oban, Argyll PA37 1QA, Scotland (United Kingdom); Hollenstein, Kaspar; Locher, Kaspar P [Institute of Molecular Biology and Biophysics, ETH Zuerich, Schafmattstrasse 20, Zuerich, 8093 (Switzerland); Bevers, Loes E; Hagedoorn, Peter-Leon; Hagen, Wilfred R, E-mail: m.feiters@science.ru.n [Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC Delft (Netherlands)

    2009-11-15

    We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L{sub 3} (2p{sub 3/2}) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

  5. Oxpholipin 11D: An Anti-Inflammatory Peptide That Binds Cholesterol and Oxidized Phospholipids

    OpenAIRE

    Piotr Ruchala; Mohamad Navab; Chun-Ling Jung; Susan Hama-Levy; Micewicz, Ewa D.; Hai Luong; Reyles, Jonathan E.; Shantanu Sharma; Waring, Alan J.; Fogelman, Alan M.; Lehrer, Robert I.

    2010-01-01

    BACKGROUND: Many gram-positive bacteria produce pore-forming exotoxins that contain a highly conserved, 12-residue domain (ECTGLAWEWWRT) that binds cholesterol. This domain is usually flanked N-terminally by arginine and C-terminally by valine. We used this 14-residue sequence as a template to create a small library of peptides that bind cholesterol and other lipids. METHODOLOGY/RESULTS: Several of these peptides manifested anti-inflammatory properties in a predictive in vitro monocyte chemot...

  6. Human endothelial actin-binding protein (ABP-280, nonmuscle filamin): a molecular leaf spring

    OpenAIRE

    1990-01-01

    Actin-binding protein (ABP-280, nonmuscle filamin) is a ubiquitous dimeric actin cross-linking phosphoprotein of peripheral cytoplasm, where it promotes orthogonal branching of actin filaments and links actin filaments to membrane glycoproteins. The complete nucleotide sequence of human endothelial cell ABP cDNA predicts a polypeptide subunit chain of 2,647 amino acids, corresponding to 280 kD, also the mass derived from physical measurements of the native protein. The actin-binding domain is...

  7. Calculation of Host-Guest Binding Affinities Using a Quantum-Mechanical Energy Model

    OpenAIRE

    Muddana, Hari S.; Gilson, Michael K.

    2012-01-01

    The prediction of protein-ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports the first mining minima (M2) binding affinity calculations based on a quantum mechanical energy model, rather than an empirical force field. We apply a semi-empirical quantum-mechanical energy functi...

  8. Characterizing Active Pharmaceutical Ingredient Binding to Human Serum Albumin by Spin-Labeling and EPR Spectroscopy.

    Science.gov (United States)

    Hauenschild, Till; Reichenwallner, Jörg; Enkelmann, Volker; Hinderberger, Dariush

    2016-08-26

    Drug binding to human serum albumin (HSA) has been characterized by a spin-labeling and continuous-wave (CW) EPR spectroscopic approach. Specifically, the contribution of functional groups (FGs) in a compound on its albumin-binding capabilities is quantitatively described. Molecules from different drug classes are labeled with EPR-active nitroxide radicals (spin-labeled pharmaceuticals (SLPs)) and in a screening approach CW-EPR spectroscopy is used to investigate HSA binding under physiological conditions and at varying ratios of SLP to protein. Spectral simulations of the CW-EPR spectra allow extraction of association constants (KA ) and the maximum number (n) of binding sites per protein. By comparison of data from 23 SLPs, the mechanisms of drug-protein association and the impact of chemical modifications at individual positions on drug uptake can be rationalized. Furthermore, new drug modifications with predictable protein binding tendency may be envisaged. PMID:27460503

  9. Bacteriophage endolysin Lyt μ1/6: characterization of the C-terminal binding domain.

    Science.gov (United States)

    Tišáková, Lenka; Vidová, Barbora; Farkašovská, Jarmila; Godány, Andrej

    2014-01-01

    The gene product of orf50 from actinophage μ1/6 of Streptomyces aureofaciens is a putative endolysin, Lyt μ1/6. It has a two-domain modular structure, consisting of an N-terminal catalytic and a C-terminal cell wall binding domain (CBD). Comparative analysis of Streptomyces phage endolysins revealed that they all have a modular structure and contain functional C-terminal domains with conserved amino acids, probably associated with their binding function. A blast analysis of Lyt μ1/6 in conjunction with secondary and tertiary structure prediction disclosed the presence of a PG_binding_1 domain within the CBD. The sequence of the C-terminal domain of lyt μ1/6 and truncated forms of it were cloned and expressed in Escherichia coli. The ability of these CBD variants fused to GFP to bind to the surface of S. aureofaciens NMU was shown by specific binding assays.

  10. Impact of Binding Site Comparisons on Medicinal Chemistry and Rational Molecular Design.

    Science.gov (United States)

    Ehrt, Christiane; Brinkjost, Tobias; Koch, Oliver

    2016-05-12

    Modern rational drug design not only deals with the search for ligands binding to interesting and promising validated targets but also aims to identify the function and ligands of yet uncharacterized proteins having impact on different diseases. Additionally, it contributes to the design of inhibitors with distinct selectivity patterns and the prediction of possible off-target effects. The identification of similarities between binding sites of various proteins is a useful approach to cope with those challenges. The main scope of this perspective is to describe applications of different protein binding site comparison approaches to outline their applicability and impact on molecular design. The article deals with various substantial application domains and provides some outstanding examples to show how various binding site comparison methods can be applied to promote in silico drug design workflows. In addition, we will also briefly introduce the fundamental principles of different protein binding site comparison methods.

  11. Analysis of single particle diffusion with transient binding using particle filtering.

    Science.gov (United States)

    Bernstein, Jason; Fricks, John

    2016-07-21

    Diffusion with transient binding occurs in a variety of biophysical processes, including movement of transmembrane proteins, T cell adhesion, and caging in colloidal fluids. We model diffusion with transient binding as a Brownian particle undergoing Markovian switching between free diffusion when unbound and diffusion in a quadratic potential centered around a binding site when bound. Assuming the binding site is the last position of the particle in the unbound state and Gaussian observational error obscures the true position of the particle, we use particle filtering to predict when the particle is bound and to locate the binding sites. Maximum likelihood estimators of diffusion coefficients, state transition probabilities, and the spring constant in the bound state are computed with a stochastic Expectation-Maximization (EM) algorithm.

  12. Analysis of single particle diffusion with transient binding using particle filtering.

    Science.gov (United States)

    Bernstein, Jason; Fricks, John

    2016-07-21

    Diffusion with transient binding occurs in a variety of biophysical processes, including movement of transmembrane proteins, T cell adhesion, and caging in colloidal fluids. We model diffusion with transient binding as a Brownian particle undergoing Markovian switching between free diffusion when unbound and diffusion in a quadratic potential centered around a binding site when bound. Assuming the binding site is the last position of the particle in the unbound state and Gaussian observational error obscures the true position of the particle, we use particle filtering to predict when the particle is bound and to locate the binding sites. Maximum likelihood estimators of diffusion coefficients, state transition probabilities, and the spring constant in the bound state are computed with a stochastic Expectation-Maximization (EM) algorithm. PMID:27107737

  13. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

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

    2004-01-01

    We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given......-to-structure prediction methods....

  14. Prediction of nuclear hormone receptor response elements.

    Science.gov (United States)

    Sandelin, Albin; Wasserman, Wyeth W

    2005-03-01

    The nuclear receptor (NR) class of transcription factors controls critical regulatory events in key developmental processes, homeostasis maintenance, and medically important diseases and conditions. Identification of the members of a regulon controlled by a NR could provide an accelerated understanding of development and disease. New bioinformatics methods for the analysis of regulatory sequences are required to address the complex properties associated with known regulatory elements targeted by the receptors because the standard methods for binding site prediction fail to reflect the diverse target site configurations. We have constructed a flexible Hidden Markov Model framework capable of predicting NHR binding sites. The model allows for variable spacing and orientation of half-sites. In a genome-scale analysis enabled by the model, we show that NRs in Fugu rubripes have a significant cross-regulatory potential. The model is implemented in a web interface, freely available for academic researchers, available at http://mordor.cgb.ki.se/NHR-scan. PMID:15563547

  15. Incorporating evolution of transcription factor binding sites into annotated alignments

    Indian Academy of Sciences (India)

    Abha S Bais; Steffen Grossmann; Martin Vingron

    2007-08-01

    Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield ``conserved TFBSs”. Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits) are generated. Moreover, the pair-profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions, as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs, we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification

  16. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun

    2016-02-02

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  17. Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d

    Directory of Open Access Journals (Sweden)

    Moffatt Barbara A

    2010-08-01

    Full Text Available Abstract Background Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB for coplanar aromatic motifs similar to those found in known glycan-binding proteins. Results The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192 in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Conclusions Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

  18. Investigating the Host Binding Signature on the Plasmodium falciparum PfEMP1 Protein Family

    OpenAIRE

    Janes, Joel H.; Wang, Christopher P.; Emily Levin-Edens; Inès Vigan-Womas; Micheline Guillotte; Martin Melcher; Odile Mercereau-Puijalon; Smith, Joseph D

    2011-01-01

    The Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) family plays a central role in antigenic variation and cytoadhesion of P. falciparum infected erythrocytes. PfEMP1 proteins/var genes are classified into three main subfamilies (UpsA, UpsB, and UpsC) that are hypothesized to have different roles in binding and disease. To investigate whether these subfamilies have diverged in binding specificity and test if binding could be predicted by adhesion domain classification, we genera...

  19. Position specific variation in the rate of evolution intranscription factor binding sites

    Energy Technology Data Exchange (ETDEWEB)

    Moses, Alan M.; Chiang, Derek Y.; Kellis, Manolis; Lander, EricS.; Eisen, Michael B.

    2003-08-28

    The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. Here we analyze the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikataeto study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artifacts of computational motif finding algorithms. As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative

  20. Structural analysis of heme proteins: implications for design and prediction

    OpenAIRE

    Bonkovsky Herbert L; Li Ting; Guo Jun-tao

    2011-01-01

    Abstract Background Heme is an essential molecule and plays vital roles in many biological processes. The structural determination of a large number of heme proteins has made it possible to study the detailed chemical and structural properties of heme binding environment. Knowledge of these characteristics can provide valuable guidelines in the design of novel heme proteins and help us predict unknown heme binding proteins. Results In this paper, we constructed a non-redundant dataset of 125 ...

  1. Binding-site assessment by virtual fragment screening.

    Directory of Open Access Journals (Sweden)

    Niu Huang

    Full Text Available The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock approximately 11,000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.

  2. Erythropoietin binding protein from mammalian serum

    Energy Technology Data Exchange (ETDEWEB)

    Clemons, G.K.

    1997-04-29

    Purified mammalian erythropoietin binding-protein is disclosed, and its isolation, identification, characterization, purification, and immunoassay are described. The erythropoietin binding protein can be used for regulation of erythropoiesis by regulating levels and half-life of erythropoietin. A diagnostic kit for determination of level of erythropoietin binding protein is also described. 11 figs.

  3. Erythropoietin binding protein from mammalian serum

    Energy Technology Data Exchange (ETDEWEB)

    Clemons, Gisela K. (Berkeley, CA)

    1997-01-01

    Purified mammalian erythropoietin binding-protein is disclosed, and its isolation, identification, characterization, purification, and immunoassay are described. The erythropoietin binding protein can be used for regulation of erythropoiesis by regulating levels and half-life of erythropoietin. A diagnostic kit for determination of level of erythropoietin binding protein is also described.

  4. Identifying intrinsically disordered protein regions likely to undergo binding-induced helical transitions.

    Science.gov (United States)

    Glover, Karen; Mei, Yang; Sinha, Sangita C

    2016-10-01

    Many proteins contain intrinsically disordered regions (IDRs) lacking stable secondary and ordered tertiary structure. IDRs are often implicated in macromolecular interactions, and may undergo structural transitions upon binding to interaction partners. However, as binding partners of many protein IDRs are unknown, these structural transitions are difficult to verify and often are poorly understood. In this study we describe a method to identify IDRs that are likely to undergo helical transitions upon binding. This method combines bioinformatics analyses followed by circular dichroism spectroscopy to monitor 2,2,2-trifluoroethanol (TFE)-induced changes in secondary structure content of these IDRs. Our results demonstrate that there is no significant change in the helicity of IDRs that are not predicted to fold upon binding. IDRs that are predicted to fold fall into two groups: one group does not become helical in the presence of TFE and includes examples of IDRs that form β-strands upon binding, while the other group becomes more helical and includes examples that are known to fold into helices upon binding. Therefore, we propose that bioinformatics analyses combined with experimental evaluation using TFE may provide a general method to identify IDRs that undergo binding-induced disorder-to-helix transitions. PMID:27179590

  5. State of the art and challenges in sequence based T-cell epitope prediction

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Hoof, Ilka; Lund, Ole;

    2010-01-01

    field has evolved significantly. Methods have now been developed that produce highly accurate binding predictions for many alleles and integrate both proteasomal cleavage and transport events. Moreover have so-called pan-specific methods been developed, which allow for prediction of peptide binding to......Sequence based T-cell epitope predictions have improved immensely in the last decade. From predictions of peptide binding to major histocompatibility complex molecules with moderate accuracy, limited allele coverage, and no good estimates of the other events in the antigen-processing pathway, the...... MHC alleles characterized by limited or no peptide binding data. Most of the developed methods are publicly available, and have proven to be very useful as a shortcut in epitope discovery. Here, we will go through some of the history of sequence-based predictions of helper as well as cytotoxic T cell...

  6. SH3 domain-peptide binding energy calculations based on structural ensemble and multiple peptide templates.

    Directory of Open Access Journals (Sweden)

    Seungpyo Hong

    Full Text Available SH3 domains mediate signal transduction by recognizing short peptides. Understanding of the driving forces in peptide recognitions will help us to predict the binding specificity of the domain-peptide recognition and to understand the molecular interaction networks of cells. However, accurate calculation of the binding energy is a tough challenge. In this study, we propose three ideas for improving our ability to predict the binding energy between SH3 domains and peptides: (1 utilizing the structural ensembles sampled from a molecular dynamics simulation trajectory, (2 utilizing multiple peptide templates, and (3 optimizing the sequence-structure mapping. We tested these three ideas on ten previously studied SH3 domains for which SPOT analysis data were available. The results indicate that calculating binding energy using the structural ensemble was most effective, clearly increasing the prediction accuracy, while the second and third ideas tended to give better binding energy predictions. We applied our method to the five SH3 targets in DREAM4 Challenge and selected the best performing method.

  7. Binding of transcription factor GabR to DNA requires recognition of DNA shape at a location distinct from its cognate binding site

    Science.gov (United States)

    Al-Zyoud, Walid A.; Hynson, Robert MG.; Ganuelas, Lorraine A.; Coster, Adelle CF.; Duff, Anthony P.; Baker, Matthew AB.; Stewart, Alastair G.; Giannoulatou, Eleni; Ho, Joshua WK.; Gaus, Katharina; Liu, Dali; Lee, Lawrence K.; Böcking, Till

    2016-01-01

    Mechanisms for transcription factor recognition of specific DNA base sequences are well characterized and recent studies demonstrate that the shape of these cognate binding sites is also important. Here, we uncover a new mechanism where the transcription factor GabR simultaneously recognizes two cognate binding sites and the shape of a 29 bp DNA sequence that bridges these sites. Small-angle X-ray scattering and multi-angle laser light scattering are consistent with a model where the DNA undergoes a conformational change to bend around GabR during binding. In silico predictions suggest that the bridging DNA sequence is likely to be bendable in one direction and kinetic analysis of mutant DNA sequences with biolayer interferometry, allowed the independent quantification of the relative contribution of DNA base and shape recognition in the GabR–DNA interaction. These indicate that the two cognate binding sites as well as the bendability of the DNA sequence in between these sites are required to form a stable complex. The mechanism of GabR–DNA interaction provides an example where the correct shape of DNA, at a clearly distinct location from the cognate binding site, is required for transcription factor binding and has implications for bioinformatics searches for novel binding sites. PMID:26681693

  8. Synthetic heparin-binding factor analogs

    Science.gov (United States)

    Pena, Louis A.; Zamora, Paul O.; Lin, Xinhua; Glass, John D.

    2010-04-20

    The invention provides synthetic heparin-binding growth factor analogs having at least one peptide chain, and preferably two peptide chains branched from a dipeptide branch moiety composed of two trifunctional amino acid residues, which peptide chain or chains bind a heparin-binding growth factor receptor and are covalently bound to a non-signaling peptide that includes a heparin-binding domain, preferably by a linker, which may be a hydrophobic linker. The synthetic heparin-binding growth factor analogs are useful as pharmaceutical agents, soluble biologics or as surface coatings for medical devices.

  9. Drug binding properties of neonatal albumin

    DEFF Research Database (Denmark)

    Brodersen, R; Honoré, B

    1989-01-01

    Neonatal and adult albumin was isolated by gel chromatography on Sephacryl S-300, from adult and umbilical cord serum, respectively. Binding of monoacetyl-diamino-diphenyl sulfone, warfarin, sulfamethizole, and diazepam was studied by means of equilibrium dialysis and the binding data were analyzed...... by the method of several acceptable fitted curves. It was found that the binding affinity to neonatal albumin is less than to adult albumin for monoacetyl-diamino-diphenyl sulfone and warfarin. Sulfamethizole binding to the neonatal protein is similarly reduced when more than one molecule of the drug...... is bound per albumin molecule, and binding of the first sulfamethizole molecule is possibly reduced as well. Diazepam binds with equal affinity to the fetal and adult proteins. Among the two main albumin drug-binding functions, for warfarin and diazepam, the former is thus compromised in the newborn...

  10. Computational Design of DNA-Binding Proteins.

    Science.gov (United States)

    Thyme, Summer; Song, Yifan

    2016-01-01

    Predicting the outcome of engineered and naturally occurring sequence perturbations to protein-DNA interfaces requires accurate computational modeling technologies. It has been well established that computational design to accommodate small numbers of DNA target site substitutions is possible. This chapter details the basic method of design used in the Rosetta macromolecular modeling program that has been successfully used to modulate the specificity of DNA-binding proteins. More recently, combining computational design and directed evolution has become a common approach for increasing the success rate of protein engineering projects. The power of such high-throughput screening depends on computational methods producing multiple potential solutions. Therefore, this chapter describes several protocols for increasing the diversity of designed output. Lastly, we describe an approach for building comparative models of protein-DNA complexes in order to utilize information from homologous sequences. These models can be used to explore how nature modulates specificity of protein-DNA interfaces and potentially can even be used as starting templates for further engineering. PMID:27094297

  11. Probing the minimal determinants of zinc binding with computational protein design.

    Science.gov (United States)

    Guffy, Sharon L; Der, Bryan S; Kuhlman, Brian

    2016-08-01

    Structure-based protein design tests our understanding of the minimal determinants of protein structure and function. Previous studies have demonstrated that placing zinc binding amino acids (His, Glu, Asp or Cys) near each other in a folded protein in an arrangement predicted to be tetrahedral is often sufficient to achieve binding to zinc. However, few designs have been characterized with high-resolution structures. Here, we use X-ray crystallography, binding studies and mutation analysis to evaluate three alternative strategies for designing zinc binding sites with the molecular modeling program Rosetta. While several of the designs were observed to bind zinc, crystal structures of two designs reveal binding configurations that differ from the design model. In both cases, the modeling did not accurately capture the presence or absence of second-shell hydrogen bonds critical in determining binding-site structure. Efforts to more explicitly design second-shell hydrogen bonds were largely unsuccessful as evidenced by mutation analysis and low expression of proteins engineered with extensive primary and secondary networks. Our results suggest that improved methods for designing interaction networks will be needed for creating metal binding sites with high accuracy. PMID:27358168

  12. Aminoglycosylation can enhance the G-quadruplex binding activity of epigallocatechin.

    Directory of Open Access Journals (Sweden)

    Li-Ping Bai

    Full Text Available With the aim of enhancing G-quadruplex binding activity, two new glucosaminosides (16, 18 of penta-methylated epigallocatechin were synthesized by chemical glycosylation. Subsequent ESI-TOF-MS analysis demonstrated that these two glucosaminoside derivatives exhibit much stronger binding activity to human telomeric DNA and RNA G-quadruplexes than their parent structure (i.e., methylated EGC (14 as well as natural epigallocatechin (EGC, 6. The DNA G-quadruplex binding activity of 16 and 18 is even more potent than strong G-quadruplex binder quercetin, which has a more planar structure. These two synthetic compounds also showed a higher binding strength to human telomeric RNA G-quadruplex than its DNA counterpart. Analysis of the structure-activity relationship revealed that the more basic compound, 16, has a higher binding capacity with DNA and RNA G-quadruplexes than its N-acetyl derivative, 18, suggesting the importance of the basicity of the aminoglycoside for G-quadruplex binding activity. Molecular docking simulation predicted that the aromatic ring of 16 π-stacks with the aromatic ring of guanine nucleotides, with the glucosamine moiety residing in the groove of G-quadruplex. This research indicates that glycosylation of natural products with aminosugar can significantly enhance their G-quadruplex binding activities, thus is an effective way to generate small molecules targeting G-quadruplexes in nucleic acids. In addition, this is the first report that green tea catechin can bind to nucleic acid G-quadruplex structures.

  13. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun

    2015-06-11

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  14. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray.

    Science.gov (United States)

    Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

    2016-01-01

    Transcription factor binding sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k = 8∼10). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build TFBS (also known as DNA motif) models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement if choosing di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  15. Effect of positional dependence and alignment strategy on modeling transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Quader Saad

    2012-07-01

    Full Text Available Abstract Background Many consensus-based and Position Weight Matrix-based methods for recognizing transcription factor binding sites (TFBS are not well suited to the variability in the lengths of binding sites. Besides, many methods discard known binding sites while building the model. Moreover, the impact of Information Content (IC and the positional dependence of nucleotides within an aligned set of TFBS has not been well researched for modeling variable-length binding sites. In this paper, we propose ML-Consensus (Mixed-Length Consensus: a consensus model for variable-length TFBS which does not exclude any reported binding sites. Methods We consider Pairwise Score (PS as a measure of positional dependence of nucleotides within an alignment of TFBS. We investigate how the prediction accuracy of ML-Consensus is affected by the incorporation of IC and PS with a particular binding site alignment strategy. We perform cross-validations for datasets of six species from the TRANSFAC public database, and analyze the results using ROC curves and the Wilcoxon matched-pair signed-ranks test. Results We observe that the incorporation of IC and PS in ML-Consensus results in statistically significant improvement in the prediction accuracy of the model. Moreover, the existence of a core region among the known binding sites (of any length is witnessed by the pairwise coexistence of nucleotides within the core length. Conclusions These observations suggest the possibility of an efficient multiple sequence alignment algorithm for aligning TFBS, accommodating known binding sites of any length, for optimal (or near-optimal TFBS prediction. However, designing such an algorithm is a matter of further investigation.

  16. Infinite sets and double binds.

    Science.gov (United States)

    Arden, M

    1984-01-01

    There have been many attempts to bring psychoanalytical theory up to date. This paper approaches the problem by discussing the work of Gregory Bateson and Ignacio Matte-Blanco, with particular reference to the use made by these authors of Russell's theory of logical types. Bateson's theory of the double bind and Matte-Blanco's bilogic are both based on concepts of logical typing. It is argued that the two theories can be linked by the idea that neurotic symptoms are based on category errors in thinking. Clinical material is presented from the analysis of a middle-aged woman. The intention is to demonstrate that the process of making interpretations can be thought of as revealing errors in thinking. Changes in the patient's inner world are then seen to be the result of clarifying childhood experiences based on category errors. Matte-Blanco's theory of bilogic and infinite experiences is a re-evaluation of the place of the primary process in mental life. It is suggested that a combination of bilogic and double bind theory provides a possibility of reformulating psychoanalytical theory.

  17. Trends for isolated amino acids and dipeptides: Conformation, divalent ion binding, and remarkable similarity of binding to calcium and lead

    CERN Document Server

    Ropo, Matti; Baldauf, Carsten

    2016-01-01

    We derive structural and binding energy trends for twenty amino acids, their dipeptides, and their interactions with the divalent cations Ca$^{2+}$, Ba$^{2+}$, Sr$^{2+}$, Cd$^{2+}$, Pb$^{2+}$, and Hg$^{2+}$. The underlying data set consists of 45,892 first-principles predicted conformers with relative energies up to about 4 eV (about 400kJ/mol). We show that only very few distinct backbone structures of isolated amino acids and their dipeptides emerge as lowest-energy conformers. The isolated amino acids predominantly adopt structures that involve an acidic proton shared between the carboxy and amino function. Dipeptides adopt one of two intramolecular-hydrogen bonded conformations C$_5$ or equatorial C$_7$. Upon complexation with a divalent cation, the accessible conformational space shrinks and intramolecular hydrogen bonding is prevented due to strong electrostatic interaction of backbone and side chain functional groups with cations. Clear correlations emerge from the binding energies of the six divalent ...

  18. Consensus of sample-balanced classifiers for identifying ligand-binding residue by co-evolutionary physicochemical characteristics of amino acids

    KAUST Repository

    Chen, Peng

    2013-01-01

    Protein-ligand binding is an important mechanism for some proteins to perform their functions, and those binding sites are the residues of proteins that physically bind to ligands. So far, the state-of-the-art methods search for similar, known structures of the query and predict the binding sites based on the solved structures. However, such structural information is not commonly available. In this paper, we propose a sequence-based approach to identify protein-ligand binding residues. Due to the highly imbalanced samples between the ligand-binding sites and non ligand-binding sites, we constructed several balanced data sets, for each of which a random forest (RF)-based classifier was trained. The ensemble of these RF classifiers formed a sequence-based protein-ligand binding site predictor. Experimental results on CASP9 targets demonstrated that our method compared favorably with the state-of-the-art. © Springer-Verlag Berlin Heidelberg 2013.

  19. Text mining improves prediction of protein functional sites.

    Directory of Open Access Journals (Sweden)

    Karin M Verspoor

    Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

  20. Erythropoietin binding sites in human foetal tissues

    Energy Technology Data Exchange (ETDEWEB)

    Pekonen, F.; Rosenloef, K.; Rutanen, E.-M.

    1987-01-01

    Using /sup 125/I labelled recombinant DNA human erythropoietin (EP), we have explored the presence and properties of EP binding sites in foetal human tissues. The EP binding site is present in the foetal liver already during the first trimester of pregnancy. The binding site has a equilibrium association constant of 4.1-6.2 x 10/sup 9/l/mol and is specific for EP. The cross-reactivities of FSH, TSH, hCG, insulin and renin substrate were less than 0.01%. The EP binding capacity of foetal liver was 5.4-16 fmol/mg membrane protein. In foetal lung tissue, a slight EP binding activity was observed, whereas foetal spleen, muscle, brain, thyroid and placental tissues were virtually devoid of EP binding capacity. The same level of binding was reached at 37 deg. C in 1 h and at 4 deg. C in 24 h. The binding was pH-dependent with maximal specific binding at pH 7.7. SDS-PAGE gel electrophoresis analysis of covalently cross-linked /sup 125/I-EP to foetal liver membranes suggested that the EP binding site was composed of two subunits with an apparent mol wt of 41000 and 86000 dalton, respectively.

  1. Binding characteristics of swine erythrocyte insulin receptors

    International Nuclear Information System (INIS)

    Crossbred gilts had 8.8 +/- 1.1% maximum binding of [125I]insulin to insulin receptors on erythrocytes. The number of insulin-binding sites per cell was 137 +/- 19, with a binding affinity ranging from 7.4 X 10(7)M-1 to 11.2 X 10(7)M-1 and mean of 8.8 X 10(7)M-1. Pregnant sows had a significant increase in maximum binding due to an increase in number of receptor sites per cell. Lactating sows fed a high-fiber diet and a low-fiber diet did not develop a significant difference in maximum binding of insulin. Sows fed the low-fiber diet had a significantly higher number of binding sites and a significantly lower binding affinity than did sows fed a high-fiber diet. Receptor-binding affinity was lower in the low-fiber diet group than in cycling gilts, whereas data from sows fed the high-fiber diet did not differ from data for cycling gilts. Data from this study indicated that insulin receptors of swine erythrocytes have binding characteristics similar to those in other species. Pregnancy and diet will alter insulin receptor binding in swine

  2. Erythropoietin binding sites in human foetal tissues

    International Nuclear Information System (INIS)

    Using 125I labelled recombinant DNA human erythropoietin (EP), we have explored the presence and properties of EP binding sites in foetal human tissues. The EP binding site is present in the foetal liver already during the first trimester of pregnancy. The binding site has a equilibrium association constant of 4.1-6.2 x 109l/mol and is specific for EP. The cross-reactivities of FSH, TSH, hCG, insulin and renin substrate were less than 0.01%. The EP binding capacity of foetal liver was 5.4-16 fmol/mg membrane protein. In foetal lung tissue, a slight EP binding activity was observed, whereas foetal spleen, muscle, brain, thyroid and placental tissues were virtually devoid of EP binding capacity. The same level of binding was reached at 37 deg. C in 1 h and at 4 deg. C in 24 h. The binding was pH-dependent with maximal specific binding at pH 7.7. SDS-PAGE gel electrophoresis analysis of covalently cross-linked 125I-EP to foetal liver membranes suggested that the EP binding site was composed of two subunits with an apparent mol wt of 41000 and 86000 dalton, respectively. (author)

  3. Adaptive evolution of transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Berg Johannes

    2004-10-01

    Full Text Available Abstract Background The regulation of a gene depends on the binding of transcription factors to specific sites located in the regulatory region of the gene. The generation of these binding sites and of cooperativity between them are essential building blocks in the evolution of complex regulatory networks. We study a theoretical model for the sequence evolution of binding sites by point mutations. The approach is based on biophysical models for the binding of transcription factors to DNA. Hence we derive empirically grounded fitness landscapes, which enter a population genetics model including mutations, genetic drift, and selection. Results We show that the selection for factor binding generically leads to specific correlations between nucleotide frequencies at different positions of a binding site. We demonstrate the possibility of rapid adaptive evolution generating a new binding site for a given transcription factor by point mutations. The evolutionary time required is estimated in terms of the neutral (background mutation rate, the selection coefficient, and the effective population size. Conclusions The efficiency of binding site formation is seen to depend on two joint conditions: the binding site motif must be short enough and the promoter region must be long enough. These constraints on promoter architecture are indeed seen in eukaryotic systems. Furthermore, we analyse the adaptive evolution of genetic switches and of signal integration through binding cooperativity between different sites. Experimental tests of this picture involving the statistics of polymorphisms and phylogenies of sites are discussed.

  4. Cloning, sequence analysis and expression of a cDNA encoding a novel insulin-like growth factor binding protein (IGFBP-2).

    OpenAIRE

    Binkert, C; Landwehr, J; Mary, J L; J. Schwander; Heinrich, G

    1989-01-01

    Insulin-like growth factors bind with high affinity to specific binding proteins in extracellular fluids. To identify structural characteristics of IGF-binding proteins that might define their physiological roles, we determined the complete primary structure of a novel human IGF-binding protein (IGFBP-2) from a cloned cDNA. The cDNA encodes a 328 amino acid IGF-binding protein precursor which contains a 39-residue signal peptide. The mature 289 amino acid IGFBP-2 has a predicted Mr of 31,325....

  5. Robust Array-Based Coregulator Binding Assay Predicting ERa-Agonist Potency and Generating Binding Profiles Reflecting Ligand Structure

    NARCIS (Netherlands)

    Aarts, J.M.M.J.G.; Wang, S.; Houtman, R.; Beuningen, van R.M.G.J.; Westerink, W.M.A.; Waart, van de B.J.; Rietjens, I.M.C.M.; Bovee, T.F.H.

    2013-01-01

    Testing chemicals for their endocrine-disrupting potential, including interference with estrogen receptor (ER) signaling, is an important aspect of chemical safety testing. Because of the practical drawbacks of animal testing, the development of in vitro alternatives for the uterotrophic assay and o

  6. Nonparametric bootstrap prediction

    OpenAIRE

    Fushiki, Tadayoshi; Komaki, Fumiyasu; Aihara, Kazuyuki

    2005-01-01

    Ensemble learning has recently been intensively studied in the field of machine learning. `Bagging' is a method of ensemble learning and uses bootstrap data to construct various predictors. The required prediction is then obtained by averaging the predictors. Harris proposed using this technique with the parametric bootstrap predictive distribution to construct predictive distributions, and showed that the parametric bootstrap predictive distribution gives asymptotically better prediction tha...

  7. Chondroitin sulphate A (CSA)-binding of single recombinant Duffy-binding-like domains is not restricted to Plasmodium falciparum Erythrocyte Membrane Protein 1 expressed by CSA-binding parasites

    DEFF Research Database (Denmark)

    Resende, Mafalda; Ditlev, Sisse B; Nielsen, Morten A;

    2009-01-01

    Individuals living in areas with high Plasmodium falciparum transmission acquire immunity to malaria over time and adults have a markedly reduced risk of contracting severe disease. However, pregnant women constitute an important exception. Pregnancy-associated malaria is a major cause of mother...... heparan sulphate. These data explain a number of publications describing CSA-binding domains derived from PfEMP1 antigens not involved in placental adhesion. The data suggest that the ability of single domains to bind CSA does not predict the functional capacity of the whole PfEMP1 and raises doubt...

  8. Variable structure motifs for transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Wernisch Lorenz

    2010-01-01

    Full Text Available Abstract Background Classically, models of DNA-transcription factor binding sites (TFBSs have been based on relatively few known instances and have treated them as sites of fixed length using position weight matrices (PWMs. Various extensions to this model have been proposed, most of which take account of dependencies between the bases in the binding sites. However, some transcription factors are known to exhibit some flexibility and bind to DNA in more than one possible physical configuration. In some cases this variation is known to affect the function of binding sites. With the increasing volume of ChIP-seq data available it is now possible to investigate models that incorporate this flexibility. Previous work on variable length models has been constrained by: a focus on specific zinc finger proteins in yeast using restrictive models; a reliance on hand-crafted models for just one transcription factor at a time; and a lack of evaluation on realistically sized data sets. Results We re-analysed binding sites from the TRANSFAC database and found motivating examples where our new variable length model provides a better fit. We analysed several ChIP-seq data sets with a novel motif search algorithm and compared the results to one of the best standard PWM finders and a recently developed alternative method for finding motifs of variable structure. All the methods performed comparably in held-out cross validation tests. Known motifs of variable structure were recovered for p53, Stat5a and Stat5b. In addition our method recovered a novel generalised version of an existing PWM for Sp1 that allows for variable length binding. This motif improved classification performance. Conclusions We have presented a new gapped PWM model for variable length DNA binding sites that is not too restrictive nor over-parameterised. Our comparison with existing tools shows that on average it does not have better predictive accuracy than existing methods. However, it does

  9. Synthetic LPS-Binding Polymer Nanoparticles

    Science.gov (United States)

    Jiang, Tian

    Lipopolysaccharide (LPS), one of the principal components of most gram-negative bacteria's outer membrane, is a type of contaminant that can be frequently found in recombinant DNA products. Because of its strong and even lethal biological effects, selective LPS removal from bioproducts solution is of particular importance in the pharmaceutical and health care industries. In this thesis, for the first time, a proof-of-concept study on preparing LPS-binding hydrogel-like NPs through facile one-step free-radical polymerization was presented. With the incorporation of various hydrophobic (TBAm), cationic (APM, GUA) monomers and cross-linkers (BIS, PEG), a small library of NPs was constructed. Their FITC-LPS binding behaviors were investigated and compared with those of commercially available LPS-binding products. Moreover, the LPS binding selectivity of the NPs was also explored by studying the NPs-BSA interactions. The results showed that all NPs obtained generally presented higher FITC-LPS binding capacity in lower ionic strength buffer than higher ionic strength. However, unlike commercial poly-lysine cellulose and polymyxin B agarose beads' nearly linear increase of FITC-LPS binding with particle concentration, NPs exhibited serious aggregation and the binding quickly saturated or even decreased at high particle concentration. Among various types of NPs, higher FITC-LPS binding capacity was observed for those containing more hydrophobic monomers (TBAm). However, surprisingly, more cationic NPs with higher content of APM exhibited decreased FITC-LPS binding in high ionic strength conditions. Additionally, when new cationic monomer and cross-linker, GUA and PEG, were applied to replace APM and BIS, the obtained NPs showed improved FITC-LPS binding capacity at low NP concentration. But compared with APM- and BIS-containing NPs, the FITC-LPS binding capacity of GUA- and PEG-containing NPs saturated earlier. To investigate the NPs' binding to proteins, we tested the NPs

  10. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

    Directory of Open Access Journals (Sweden)

    Xin Deng

    2015-07-01

    Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

  11. Why tight-binding theory?

    Science.gov (United States)

    Harrison, Walter A.

    2002-12-01

    In the context of computational physics other methods are more accurate, but tight-binding theory allows very direct physical interpretation and is simple enough to allow much more realistic treatments beyond the local density approximation. We address several important questions of this last category: How does the gap enhancement from Coulomb correlations vary from material to material? Should the enhanced gap be used for calculating the dielectric constant? For calculating the effective mass in k-dot-p theory? How valid is the scissors approximation? How does one line up bands at an interface? How should we match the envelope function at interfaces in effective-mass theory? Why can the resulting quantum-well states seem to violate the uncertainty principle? How should f-shell electrons be treated when they are intermediate between band-like and core-like? The answers to all of these questions are given and discussed.

  12. DNA binding hydroxyl radical probes

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Vicky J.; Konigsfeld, Katie M.; Aguilera, Joe A. [Department of Radiology, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0610 (United States); Milligan, Jamie R., E-mail: jmilligan@ucsd.edu [Department of Radiology, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0610 (United States)

    2012-01-15

    The hydroxyl radical is the primary mediator of DNA damage by the indirect effect of ionizing radiation. It is a powerful oxidizing agent produced by the radiolysis of water and is responsible for a significant fraction of the DNA damage associated with ionizing radiation. There is therefore an interest in the development of sensitive assays for its detection. The hydroxylation of aromatic groups to produce fluorescent products has been used for this purpose. We have examined four different chromophores, which produce fluorescent products when hydroxylated. Of these, the coumarin system suffers from the fewest disadvantages. We have therefore examined its behavior when linked to a cationic peptide ligand designed to bind strongly to DNA. - Highlights: > Examined four aromatic groups as a means to detect hydroxyl radicals by fluorescence. > Coumarin system suffers from the fewest disadvantages. > Characterized its reactivity when linked to a hexa-arginine peptide.

  13. Structural basis for the evolutionary inactivation of Ca[superscript 2+] binding to synaptotagmin 4

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Han; Shin, Ok-Ho; Machius, Mischa; Tomchick, Diana R.; Südhof, Thomas C.; Rizo, Josep (U. of Texas-SMED)

    2010-11-16

    The neuronal protein synaptotagmin 1 functions as a Ca{sup 2+} sensor in exocytosis via two Ca{sup 2+}-binding C{sub 2} domains. The very similar synaptotagmin 4, which includes all the predicted Ca{sup 2+}-binding residues in the C{sub 2}B domain but not in the C{sub 2}A domain, is also thought to function as a neuronal Ca{sup 2+} sensor. Here we show that, unexpectedly, both C{sub 2} domains of fly synaptotagmin 4 exhibit Ca{sup 2+}-dependent phospholipid binding, whereas neither C{sub 2} domain of rat synaptotagmin 4 binds Ca{sup 2+} or phospholipids efficiently. Crystallography reveals that changes in the orientations of critical Ca{sup 2+} ligands, and perhaps their flexibility, render the rat synaptotagmin 4 C{sub 2}B domain unable to form full Ca{sup 2+}-binding sites. These results indicate that synaptotagmin 4 is a Ca{sup 2+} sensor in the fly but not in the rat, that the Ca{sup 2+}-binding properties of C{sub 2} domains cannot be reliably predicted from sequence analyses, and that proteins clearly identified as orthologs may nevertheless have markedly different functional properties.

  14. Putative hAPN receptor binding sites in SARS_CoV spike protein

    Institute of Scientific and Technical Information of China (English)

    YUXiao-Jing; LUOCheng; LinJian-Cheng; HAOPei; HEYou-Yu; GUOZong-Ming; QINLei; SUJiong; LIUBo-Shu; HUANGYin; NANPeng; LIChuan-Song; XIONGBin; LUOXiao-Min; ZHAOGuo-Ping; PEIGang; CHENKai-Xian; SHENXu; SHENJian-Hua; ZOUJian-Ping; HEWei-Zhong; SHITie-Liu; ZHONGYang; JIANGHua-Liang; LIYi-Xue

    2003-01-01

    AIM:To obtain the information of ligand-receptor binding between thd S protein of SARS_CoV and CD13, identify the possible interacting domains or motifs related to binding sites, and provide clues for studying the functions of SARS proteins and designing anti-SARS drugs and vaccines. METHODS: On the basis of comparative genomics, the homology search, phylogenetic analyses, and multi-sequence alignment were used to predict CD13 related interacting domains and binding sites sites in the S protein of SARS_CoV. Molecular modeling and docking simulation methods were employed to address the interaction feature between CD13 and S protein of SARS_CoV in validating the bioinformatics predictions. RESULTS:Possible binding sites in the SARS_CoV S protein to CD13 have been mapped out by using bioinformatics analysis tools. The binding for one protein-protein interaction pair (D757-R761 motif of the SARS_CoV S protein to P585-A653 domain of CD13) has been simulated by molecular modeling and docking simulation methods. CONCLUSION:CD13 may be a possible receptor of the SARS_CoV S protein which may be associated with the SARS infection. This study also provides a possible strategy for mapping the possible binding receptors of the proteins in a genome.

  15. The helical structure of DNA facilitates binding

    Science.gov (United States)

    Berg, Otto G.; Mahmutovic, Anel; Marklund, Emil; Elf, Johan

    2016-09-01

    The helical structure of DNA imposes constraints on the rate of diffusion-limited protein binding. Here we solve the reaction-diffusion equations for DNA-like geometries and extend with simulations when necessary. We find that the helical structure can make binding to the DNA more than twice as fast compared to a case where DNA would be reactive only along one side. We also find that this rate advantage remains when the contributions from steric constraints and rotational diffusion of the DNA-binding protein are included. Furthermore, we find that the association rate is insensitive to changes in the steric constraints on the DNA in the helix geometry, while it is much more dependent on the steric constraints on the DNA-binding protein. We conclude that the helical structure of DNA facilitates the nonspecific binding of transcription factors and structural DNA-binding proteins in general.

  16. Scrutinizing MHC-I binding peptides and their limits of variation.

    Directory of Open Access Journals (Sweden)

    Christian P Koch

    Full Text Available Designed peptides that bind to major histocompatibility protein I (MHC-I allomorphs bear the promise of representing epitopes that stimulate a desired immune response. A rigorous bioinformatical exploration of sequence patterns hidden in peptides that bind to the mouse MHC-I allomorph H-2K(b is presented. We exemplify and validate these motif findings by systematically dissecting the epitope SIINFEKL and analyzing the resulting fragments for their binding potential to H-2K(b in a thermal denaturation assay. The results demonstrate that only fragments exclusively retaining the carboxy- or amino-terminus of the reference peptide exhibit significant binding potential, with the N-terminal pentapeptide SIINF as shortest ligand. This study demonstrates that sophisticated machine-learning algorithms excel at extracting fine-grained patterns from peptide sequence data and predicting MHC-I binding peptides, thereby considerably extending existing linear prediction models and providing a fresh view on the computer-based molecular design of future synthetic vaccines. The server for prediction is available at http://modlab-cadd.ethz.ch (SLiDER tool, MHC-I version 2012.

  17. Inferring PDZ domain multi-mutant binding preferences from single-mutant data.

    Directory of Open Access Journals (Sweden)

    Elena Zaslavsky

    Full Text Available Many important cellular protein interactions are mediated by peptide recognition domains. The ability to predict a domain's binding specificity directly from its primary sequence is essential to understanding the complexity of protein-protein interaction networks. One such recognition domain is the PDZ domain, functioning in scaffold proteins that facilitate formation of signaling networks. Predicting the PDZ domain's binding specificity was a part of the DREAM4 Peptide Recognition Domain challenge, the goal of which was to describe, as position weight matrices, the specificity profiles of five multi-mutant ERBB2IP-1 domains. We developed a method that derives multi-mutant binding preferences by generalizing the effects of single point mutations on the wild type domain's binding specificities. Our approach, trained on publicly available ERBB2IP-1 single-mutant phage display data, combined linear regression-based prediction for ligand positions whose specificity is determined by few PDZ positions, and single-mutant position weight matrix averaging for all other ligand columns. The success of our method as the winning entry of the DREAM4 competition, as well as its superior performance over a general PDZ-ligand binding model, demonstrates the advantages of training a model on a well-selected domain-specific data set.

  18. Identification of Covalent Binding Sites Targeting Cysteines Based on Computational Approaches.

    Science.gov (United States)

    Zhang, Yanmin; Zhang, Danfeng; Tian, Haozhong; Jiao, Yu; Shi, Zhihao; Ran, Ting; Liu, Haichun; Lu, Shuai; Xu, Anyang; Qiao, Xin; Pan, Jing; Yin, Lingfeng; Zhou, Weineng; Lu, Tao; Chen, Yadong

    2016-09-01

    Covalent drugs have attracted increasing attention in recent years due to good inhibitory activity and selectivity. Targeting noncatalytic cysteines with irreversible inhibitors is a powerful approach for enhancing pharmacological potency and selectivity because cysteines can form covalent bonds with inhibitors through their nucleophilic thiol groups. However, most human kinases have multiple noncatalytic cysteines within the active site; to accurately predict which cysteine is most likely to form covalent bonds is of great importance but remains a challenge when designing irreversible inhibitors. In this work, FTMap was first applied to check its ability in predicting covalent binding site defined as the region where covalent bonds are formed between cysteines and irreversible inhibitors. Results show that it has excellent performance in detecting the hot spots within the binding pocket, and its hydrogen bond interaction frequency analysis could give us some interesting instructions for identification of covalent binding cysteines. Furthermore, we proposed a simple but useful covalent fragment probing approach and showed that it successfully predicted the covalent binding site of seven targets. By adopting a distance-based method, we observed that the closer the nucleophiles of covalent warheads are to the thiol group of a cysteine, the higher the possibility that a cysteine is prone to form a covalent bond. We believe that the combination of FTMap and our distance-based covalent fragment probing method can become a useful tool in detecting the covalent binding site of these targets. PMID:27483186

  19. Predictions of the bond length and vibrational frequency of Ge/sub 2/

    Energy Technology Data Exchange (ETDEWEB)

    Northrup, J.E.; Cohen, M.L.

    1983-12-02

    A pseudopotential local spin density calculation of the bond length, vibrational frequency, and binding energy for the ..sigma../sub g//sup -/ state of the germanium dimer is presented. Predictions for the equilibrium bond length and vibrational frequency are given. An overestimate of the binding energy is obtained; this is consistent with other local density calculations for sp bonded diatomic molecules.

  20. Predictions of the bond length and vibrational frequency of Ge 2

    Science.gov (United States)

    Northrup, John E.; Cohen, Marvin L.

    1983-12-01

    We present a pseudopotential local spin density calculation of the bond length, vibrational frequency, and binding energy for the 3Σ g- state of the germanium dimer. Predictions for the equilibrium bond length and vibrational frequency are given. An overestimate of the binding energy is obtained; this is consistent with other local spin density calculations for sp bonded diatomic molecules.

  1. Entamoeba histolytica Lectins Contain Unique 6-Cys or 8-Cys Chitin-Binding Domains

    OpenAIRE

    Van Dellen, Katrina; Ghosh, Sudip K.; Robbins, Phillips W.; Loftus, Brendan; Samuelson, John

    2002-01-01

    The Jacob lectin, the most abundant glycoprotein in the cyst wall of Entamoeba invadens, contains five unique 6-Cys chitin-binding domains (CBDs). We identified Entamoeba histolytica and Entamoeba dispar genes encoding Jacob homologues, each of which contains two predicted 6-Cys CBDs. A unique 8-Cys CBD was found at the N termini of the E. histolytica chitinase and three other predicted lectins, called Jessie 1 to Jessie 3. The CBDs of four E. histolytica lectins (Jacob, chitinase, and Jessie...

  2. Preoperative mannan-binding lectin pathway and prognosis in colorectal cancer

    DEFF Research Database (Denmark)

    Ytting, Henriette; Christensen, Ib Jarle; Jensenius, Jens Christian;

    2005-01-01

    PURPOSE: Deficiency of the mannan-binding lectin (MBL) pathway of innate immunity is associated with increased susceptibility to infections. In patients with colorectal cancer (CRC), postoperative infection is associated with poor prognosis. The aim of the present study was to evaluate (1) the...... predictive of pneumonia, which is associated with poorer survival. MBL concentration and MBL/MASP activity was not predictive of other postoperative infections or long-term prognosis, and showed no correlation with CRP....

  3. A cellular protein specifically binds to the 3'-terminal sequences of hepatitis C virus intermediate negative-strand RNA

    Institute of Scientific and Technical Information of China (English)

    王巍; 邓庆丽; 黄开红; 段朝晖; 邵静; 黄志清; 黄志明

    2003-01-01

    ObjectiveTo study the mechanism of the cellular proteins involved in the process of replication of hepatitis C virus (HCV) negative-strand RNA.MethodsUltraviolet (UV) cross-linking was used to identify the cellular proteins that would bind to the 3'-end of HCV negative-strand RNA. Competition experimentwas used to confirm the specificity of this binding, in which excess nonhomologous protein and RNA transcripts were used as competitors. The required binding sequence was determined by mapping, then the binding site was predicted through secondary structure analysis.ResultsA cellular protein of 45 kD (p45) was found to bind specifically to the 3'-endof HCV negative-strand RNA by UV cross-linking. nhomologous proteins and RNA transcripts could not compete out this binding, whereas the unlabeled 3'-endof HCV negative-strand RNA could. Mapping of the protein-binding site suggested that the 3'-end 131-278nt of HCV negative-strand RNA was the possible protein-binding region. Analysis of RNA secondary structure presumed that the potential binding site was located at 194-GAAAGAAC-201. ConclusionThe cellular protein p45 could specifically bind to the secondary structure of the 3'-end of HCV intermediate negative-strand RNA, and may play an important role in HCV RNA replication.

  4. Human Leukocyte Antigen (HLA) Class I Restricted Epitope Discovery in Yellow Fewer and Dengue Viruses: Importance of HLA Binding Strength

    DEFF Research Database (Denmark)

    Lund, Ole; Nascimento, Eduardo J. M.; Maciel, Milton, Jr;

    2011-01-01

    Epitopes from all available full-length sequences of yellow fever virus (YFV) and dengue fever virus (DENV) restricted by Human Leukocyte Antigen class I (HLA-I) alleles covering 12 HLA-I supertypes were predicted using the NetCTL algorithm. A subset of 179 predicted YFV and 158 predicted DENV...... inoculated twice with the 17DD YFV vaccine strain. Three of the YFV A*02:01 restricted peptides activated T-cells from the infected mice in vitro. All three peptides that elicited responses had an HLA binding affinity of 2 nM or less. The results indicate the importance of the strength of HLA binding...

  5. Methods for Improving Aptamer Binding Affinity

    OpenAIRE

    Hijiri Hasegawa; Nasa Savory; Koichi Abe; Kazunori Ikebukuro

    2016-01-01

    Aptamers are single stranded oligonucleotides that bind a wide range of biological targets. Although aptamers can be isolated from pools of random sequence oligonucleotides using affinity-based selection, aptamers with high affinities are not always obtained. Therefore, further refinement of aptamers is required to achieve desired binding affinities. The optimization of primary sequences and stabilization of aptamer conformations are the main approaches to refining the binding properties of a...

  6. Collective bargaining under non-binding contracts

    OpenAIRE

    Dobbelaere, S.; Luttens, R.I.

    2011-01-01

    We introduce collective bargaining in a static framework where the firm and its risk-neutral employees negotiate over wages in a non-binding contract setting. Our main result is the equivalence between the non-binding collective equilibrium wage-employment contract and the equilibrium contract under binding risk-neutral efficient bargaining. We also demonstrate that our non-cooperative equilibrium wages and profits coincide with the Owen values of the corresponding cooperative game with the c...

  7. A computational model for feature binding

    Institute of Scientific and Technical Information of China (English)

    SHI ZhiWei; SHI ZhongZhi; LIU Xi; SHI ZhiPing

    2008-01-01

    The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism.Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.

  8. A computational model for feature binding

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.

  9. RNA Binding Specificity of Drosophila Muscleblind†

    OpenAIRE

    Goers, Emily S.; Voelker, Rodger B.; Gates, Devika P.; Berglund, J. Andrew

    2008-01-01

    Members of the muscleblind family of RNA binding proteins found in Drosophila and mammals are key players in both the human disease myotonic dystrophy and the regulation of alternative splicing. Recently, the mammalian muscleblind-like protein, MBNL1, has been shown to have interesting RNA binding properties with both endogenous and disease-related RNA targets. Here we report the characterization of RNA binding properties of the Drosophila muscleblind protein Mbl. Mutagenesis of double-strand...

  10. Great interactions: How binding incorrect partners can teach us about protein recognition and function.

    Science.gov (United States)

    Vamparys, Lydie; Laurent, Benoist; Carbone, Alessandra; Sacquin-Mora, Sophie

    2016-10-01

    Protein-protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding-site predictions resulting from the cross-docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408-1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

  11. Altered SPECT (123)I-iomazenil Binding in the Cingulate Cortex of Children with Anorexia Nervosa.

    Science.gov (United States)

    Nagamitsu, Shinichiro; Sakurai, Rieko; Matsuoka, Michiko; Chiba, Hiromi; Ozono, Shuichi; Tanigawa, Hitoshi; Yamashita, Yushiro; Kaida, Hayato; Ishibashi, Masatoshi; Kakuma, Tatsuki; Croarkin, Paul E; Matsuishi, Toyojiro

    2016-01-01

    Several lines of evidence suggest that anxiety plays a key role in the development and maintenance of anorexia nervosa (AN) in children. The purpose of this study was to examine cortical GABA(A)-benzodiazepine receptor binding before and after treatment in children beginning intensive AN treatment. Brain single-photon emission computed tomography (SPECT) measurements using (123)I-iomazenil, which binds to GABA(A)-benzodiazepine receptors, was performed in 26 participants with AN who were enrolled in a multimodal treatment program. Sixteen of the 26 participants underwent a repeat SPECT scan immediately before discharge at conclusion of the intensive treatment program. Eating behavior and mood disturbances were assessed using Eating Attitudes Test with 26 items (EAT-26) and the short form of the Profile of Mood States (POMS). Clinical outcome scores were evaluated after a 1-year period. We examined association between relative iomazenil-binding activity in cortical regions of interest and psychometric profiles and determined which psychometric profiles show interaction effects with brain regions. Further, we determined if binding activity could predict clinical outcome and treatment changes. Higher EAT-26 scores were significantly associated with lower iomazenil-binding activity in the anterior and posterior cingulate cortex. Higher POMS subscale scores were significantly associated with lower iomazenil-binding activity in the left frontal, parietal cortex, and posterior cingulate cortex (PCC). "Depression-Dejection" and "Confusion" POMS subscale scores, and total POMS score showed interaction effects with brain regions in iomazenil-binding activity. Decreased binding in the anterior cingulate cortex and left parietal cortex was associated with poor clinical outcomes. Relative binding increases throughout the PCC and occipital gyrus were observed after weight gain in children with AN. These findings suggest that cortical GABAergic receptor binding is altered in

  12. Altered SPECT 123I iomazenil Binding in the Cingulate Cortex of Children with Anorexia Nervosa

    Directory of Open Access Journals (Sweden)

    Shinichiro eNagamitsu

    2016-02-01

    Full Text Available Several lines of evidence suggest that anxiety plays a key role in the development and maintenance of anorexia nervosa (AN in children. The purpose of this study was to examine cortical GABA(A-benzodiazepine receptor binding before and after treatment in children beginning intensive AN treatment. Brain single photon emission computed tomography (SPECT measurements using 123I iomazenil, which binds to GABA(A-benzodiazepine receptors, was performed in 26 participants with AN who were enrolled in a multimodal treatment program. Sixteen of the 26 participants underwent a repeat SPECT scan immediately before discharge at conclusion of the intensive treatment program. Eating behavior and mood disturbances were assessed using Eating Attitudes Test with 26 items (EAT-26 and the short form of the Profile of Mood States (POMS. Clinical outcome scores were evaluated after a 1-year period. We examined association between relative iomazenil binding activity in cortical regions of interest (ROIs and psychometric profiles, and determined which psychometric profiles show interaction effects with brain regions. Further, we determined if binding activity could predict clinical outcome and treatment changes. Higher EAT-26 scores were significantly associated with lower iomazenil binding activity in the anterior posterior cingulate cortex (ACC. Higher POMS subscale scores were significantly associated with lower iomazenil binding activity in the left frontal, parietal cortex, and posterior cingulate cortex (PCC. Depression-Dejection, and Confusion POMS subscale scores, and total POMS score, showed interaction effects with brain regions in iomazenil binding activity. Decreased binding in the ACC and left parietal cortex was associated with poor clinical outcomes. Relative binding increases throughout the PCC and occipital gyrus were observed after weight gain in children with AN. These findings suggest that cortical GABAergic receptor binding is altered in children

  13. Exploring the composition of protein-ligand binding sites on a large scale.

    Directory of Open Access Journals (Sweden)

    Nickolay A Khazanov

    Full Text Available The residue composition of a ligand binding site determines the interactions available for diffusion-mediated ligand binding, and understanding general composition of these sites is of great importance if we are to gain insight into the functional diversity of the proteome. Many structure-based drug design methods utilize such heuristic information for improving prediction or characterization of ligand-binding sites in proteins of unknown function. The Binding MOAD database if one of the largest curated sets of protein-ligand complexes, and provides a source of diverse, high-quality data for establishing general trends of residue composition from currently available protein structures. We present an analysis of 3,295 non-redundant proteins with 9,114 non-redundant binding sites to identify residues over-represented in binding regions versus the rest of the protein surface. The Binding MOAD database delineates biologically-relevant "valid" ligands from "invalid" small-molecule ligands bound to the protein. Invalids are present in the crystallization medium and serve no known biological function. Contacts are found to differ between these classes of ligands, indicating that residue composition of biologically relevant binding sites is distinct not only from the rest of the protein surface, but also from surface regions capable of opportunistic binding of non-functional small molecules. To confirm these trends, we perform a rigorous analysis of the variation of residue propensity with respect to the size of the dataset and the content bias inherent in structure sets obtained from a large protein structure database. The optimal size of the dataset for establishing general trends of residue propensities, as well as strategies for assessing the significance of such trends, are suggested for future studies of binding-site composition.

  14. Altered SPECT 123I-iomazenil Binding in the Cingulate Cortex of Children with Anorexia Nervosa

    Science.gov (United States)

    Nagamitsu, Shinichiro; Sakurai, Rieko; Matsuoka, Michiko; Chiba, Hiromi; Ozono, Shuichi; Tanigawa, Hitoshi; Yamashita, Yushiro; Kaida, Hayato; Ishibashi, Masatoshi; Kakuma, Tatsuki; Croarkin, Paul E.; Matsuishi, Toyojiro

    2016-01-01

    Several lines of evidence suggest that anxiety plays a key role in the development and maintenance of anorexia nervosa (AN) in children. The purpose of this study was to examine cortical GABA(A)-benzodiazepine receptor binding before and after treatment in children beginning intensive AN treatment. Brain single-photon emission computed tomography (SPECT) measurements using 123I-iomazenil, which binds to GABA(A)-benzodiazepine receptors, was performed in 26 participants with AN who were enrolled in a multimodal treatment program. Sixteen of the 26 participants underwent a repeat SPECT scan immediately before discharge at conclusion of the intensive treatment program. Eating behavior and mood disturbances were assessed using Eating Attitudes Test with 26 items (EAT-26) and the short form of the Profile of Mood States (POMS). Clinical outcome scores were evaluated after a 1-year period. We examined association between relative iomazenil-binding activity in cortical regions of interest and psychometric profiles and determined which psychometric profiles show interaction effects with brain regions. Further, we determined if binding activity could predict clinical outcome and treatment changes. Higher EAT-26 scores were significantly associated with lower iomazenil-binding activity in the anterior and posterior cingulate cortex. Higher POMS subscale scores were significantly associated with lower iomazenil-binding activity in the left frontal, parietal cortex, and posterior cingulate cortex (PCC). “Depression–Dejection” and “Confusion” POMS subscale scores, and total POMS score showed interaction effects with brain regions in iomazenil-binding activity. Decreased binding in the anterior cingulate cortex and left parietal cortex was associated with poor clinical outcomes. Relative binding increases throughout the PCC and occipital gyrus were observed after weight gain in children with AN. These findings suggest that cortical GABAergic receptor binding is altered

  15. Copper(II) binding properties of hepcidin

    OpenAIRE

    Kulprachakarn, Kanokwan; Chen, Yu-Lin; Kong, Xiaole; Arno, Maria Chiara; Hider, Robert Charles; Srichairatanakool, Somdet; Bansal, Sukhvinder

    2016-01-01

    Hepcidin is a peptide hormone that regulates the homeostasis of iron metabolism. The N-terminal domain of hepcidin is conserved amongst a range of species and is capable of binding CuII and NiII through the amino terminal copper–nickel binding motif (ATCUN). It has been suggested that the binding of copper to hepcidin may have biological relevance. In this study we have investigated the binding of CuII with model peptides containing the ATCUN motif, fluorescently labelled hepcidin and hepcidi...

  16. Advances on Plant Pathogenic Mycotoxin Binding Proteins

    Institute of Scientific and Technical Information of China (English)

    WANG Chao-hua; DONG Jin-gao

    2002-01-01

    Toxin-binding protein is one of the key subjects in plant pathogenic mycotoxin research. In this paper, new advances in toxin-binding proteins of 10 kinds of plant pathogenic mycotoxins belonging to Helminthosporium ,Alternaria ,Fusicoccum ,Verticillium were reviewed, especially the techniques and methods of toxin-binding proteins of HS-toxin, HV-toxin, HMT-toxin, HC-toxin. It was proposed that the isotope-labeling technique and immunological chemistry technique should be combined together in research of toxin-binding protein, which will be significant to study the molecular recognition mechanism between host and pathogenic fungus.

  17. Retinoid-binding proteins: similar protein architectures bind similar ligands via completely different ways.

    Directory of Open Access Journals (Sweden)

    Yu-Ru Zhang

    Full Text Available BACKGROUND: Retinoids are a class of compounds that are chemically related to vitamin A, which is an essential nutrient that plays a key role in vision, cell growth and differentiation. In vivo, retinoids must bind with specific proteins to perform their necessary functions. Plasma retinol-binding protein (RBP and epididymal retinoic acid binding protein (ERABP carry retinoids in bodily fluids, while cellular retinol-binding proteins (CRBPs and cellular retinoic acid-binding proteins (CRABPs carry retinoids within cells. Interestingly, although all of these transport proteins possess similar structures, the modes of binding for the different retinoid ligands with their carrier proteins are different. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we analyzed the various retinoid transport mechanisms using structure and sequence comparisons, binding site analyses and molecular dynamics simulations. Our results show that in the same family of proteins and subcellular location, the orientation of a retinoid molecule within a binding protein is same, whereas when different families of proteins are considered, the orientation of the bound retinoid is completely different. In addition, none of the amino acid residues involved in ligand binding is conserved between the transport proteins. However, for each specific binding protein, the amino acids involved in the ligand binding are conserved. The results of this study allow us to propose a possible transport model for retinoids. CONCLUSIONS/SIGNIFICANCE: Our results reveal the differences in the binding modes between the different retinoid-binding proteins.

  18. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683

  19. Function of the PEX19-binding site of human adrenoleukodystrophy protein as targeting motif in man and yeast. PMP targeting is evolutionarily conserved.

    Science.gov (United States)

    Halbach, André; Lorenzen, Stephan; Landgraf, Christiane; Volkmer-Engert, Rudolf; Erdmann, Ralf; Rottensteiner, Hanspeter

    2005-06-01

    We predicted in human peroxisomal membrane proteins (PMPs) the binding sites for PEX19, a key player in the topogenesis of PMPs, by virtue of an algorithm developed for yeast PMPs. The best scoring PEX19-binding site was found in the adrenoleukodystrophy protein (ALDP). The identified site was indeed bound by human PEX19 and was also recognized by the orthologous yeast PEX19 protein. Likewise, both human and yeast PEX19 bound with comparable affinities to the PEX19-binding site of the yeast PMP Pex13p. Interestingly, the identified PEX19-binding site of ALDP coincided with its previously determined targeting motif. We corroborated the requirement of the ALDP PEX19-binding site for peroxisomal targeting in human fibroblasts and showed that the minimal ALDP fragment targets correctly also in yeast, again in a PEX19-binding site-dependent manner. Furthermore, the human PEX19-binding site of ALDP proved interchangeable with that of yeast Pex13p in an in vivo targeting assay. Finally, we showed in vitro that most of the predicted binding sequences of human PMPs represent true binding sites for human PEX19, indicating that human PMPs harbor common PEX19-binding sites that do resemble those of yeast. Our data clearly revealed a role for PEX19-binding sites as PMP-targeting motifs across species, thereby demonstrating the evolutionary conservation of PMP signal sequences from yeast to man.

  20. 混合微粒群神经网络系统的构建及其在HLA-A*0201限制性T细胞表位活性预测中的应用%Design and construction of hybrid particle swarm optimizer-artificial neural network and its application in predicting the binding affinity of T-cell epitope to HLA-A*0201

    Institute of Scientific and Technical Information of China (English)

    任彦荣

    2011-01-01

    A novel modeling method that we named hybrid particle swarm optimizer-artificial neural network (HPSO-ANN) is developed by introducing "reproduction", "hybrid", "mutation" operator and "Metropolis" sampling into exploration of particle swarm optimizer and then applies to optimize the weighted values of feed-forward multilayer perceptron. By performing this newly proposed method to quantitatively predict the binding affinity of 152 CTL epitopes to their common receptor of HLA-A*0201 protein, it is suggested that the developed method enormously increases abilities of global searching for such algorithms in their former periods and/or earlier stages and local convergence in their latter periods and/or final stages except for little time-consuming of CPU. By comparing with QSAR modeling results obtained from reports in references, this proposed method is effective in solving practical problems, especially in cases of optimizations with non-linear, high-dimensional, etc.%尝试将“复制”、“杂交”、“变异”算子和“Metropolis”采样策略引入到微粒群算法(PSO)搜索进程,并将其用于前馈型多层神经网络(FMANN)连接权值优化当中,形成了1种新的非线性统计建模方法:混合微粒群神经网络系统(hybrid particle Swarmoptimizer-artificial neural network,HPSO-ANN)。通过仿真对比及对152个HLA-A*0201限制性T细胞表位活性预测表明:HPSO-ANN仅在少量增加CPU耗时的同时大大提高了算法前期全局搜索能力及后期局部收敛性,特别是对于非线性、高维数等复杂问题该法往往能够取得优于传统QSAR建模方法的实际效果。

  1. Methods and systems for identifying ligand-protein binding sites

    KAUST Repository

    Gao, Xin

    2016-05-06

    The invention provides a novel integrated structure and system-based approach for drug target prediction that enables the large-scale discovery of new targets for existing drugs Novel computer-readable storage media and computer systems are also provided. Methods and systems of the invention use novel sequence order-independent structure alignment, hierarchical clustering, and probabilistic sequence similarity techniques to construct a probabilistic pocket ensemble (PPE) that captures even promiscuous structural features of different binding sites for a drug on known targets. The drug\\'s PPE is combined with an approximation of the drug delivery profile to facilitate large-scale prediction of novel drug- protein interactions with several applications to biological research and drug development.

  2. Describing the Peptide Binding Specificity of HLA-C

    DEFF Research Database (Denmark)

    Rasmussen, Michael; Harndahl, Mikkel Nors; Nielsen, Morten;

    for 5 HLA-C molecules and for all, but one, molecule we find a high frequency of binders, >70%, among these peptides. To extend the examined peptide space, we use bioinformatic prediction tools to search for additional binders. Finally, we update our prediction tool, NetMHCpan, with the HLA-C affinity......Human leukocyte antigen (HLA) presents peptides to T-cells for immune scrutiny. Whereas HLA-A and -B have been described in great detail, HLA-C has received much less attention. Here, to increase the coverage of HLA-C and the accuracy of the corresponding tools, we have generated HLA-C molecules......; peptide-binding assays, data and predictors; and tetramers; representing the most prevalent HLA-C molecules. We have combined positional scanning combinatorial peptide library (PSCPL) with a homogenous high-throughput dissociation assay and generated specificity matrices for 11 different HLA-C molecules...

  3. Improving the scoring of protein-ligand binding affinity by including the effects of structural water and electronic polarization.

    Science.gov (United States)

    Liu, Jinfeng; He, Xiao; Zhang, John Z H

    2013-06-24

    Docking programs that use scoring functions to estimate binding affinities of small molecules to biological targets are widely applied in drug design and drug screening with partial success. But accurate and efficient scoring functions for protein-ligand binding affinity still present a grand challenge to computational chemists. In this study, the polarized protein-specific charge model (PPC) is incorporated into the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method to rescore the binding poses of some protein-ligand complexes, for which docking programs, such as Autodock, could not predict their binding modes correctly. Different sampling techniques (single minimized conformation and multiple molecular dynamics (MD) snapshots) are used to test the performance of MM/PBSA combined with the PPC model. Our results show the availability and effectiveness of this approach in correctly ranking the binding poses. More importantly, the bridging water molecules are found to play an important role in correctly determining the protein-ligand binding modes. Explicitly including these bridging water molecules in MM/PBSA calculations improves the prediction accuracy significantly. Our study sheds light on the importance of both bridging water molecules and the electronic polarization in the development of more reliable scoring functions for predicting molecular docking and protein-ligand binding affinity. PMID:23651068

  4. Toward Improved Force-Field Accuracy through Sensitivity Analysis of Host-Guest Binding Thermodynamics.

    Science.gov (United States)

    Yin, Jian; Fenley, Andrew T; Henriksen, Niel M; Gilson, Michael K

    2015-08-13

    Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by nonoptimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery.

  5. Decreased Transcription Factor Binding Levels Nearby Primate Pseudogenes Suggest Regulatory Degeneration.

    Science.gov (United States)

    Douglas, Gavin M; Wilson, Michael D; Moses, Alan M

    2016-06-01

    Characteristics of pseudogene degeneration at the coding level are well-known, such as a shift toward neutral rates of nonsynonymous substitutions and gain of frameshift mutations. In contrast, degeneration of pseudogene transcriptional regulation is not well understood. Here, we test two predictions of regulatory degeneration along a pseudogenized lineage: 1) Decreased transcription factor (TF) binding and 2) accelerated evolution in putative cis-regulatory regions.We find evidence for decreased TF binding levels nearby two primate pseudogenes compared with functional liver genes. However, the majority of TF-bound sequences nearby pseudogenes do not show evidence for lineage-specific accelerated rates of evolution. We conclude that decreases in TF binding level could be a marker for regulatory degeneration, while sequence degeneration in primate cis-regulatory modules may be obscured by background rates of TF binding site turnover. PMID:26882985

  6. Fragmentation cross sections and binding energies of neutron-rich nuclei

    Science.gov (United States)

    Tsang, M. B.; Lynch, W. G.; Friedman, W. A.; Mocko, M.; Sun, Z. Y.; Aoi, N.; Cook, J. M.; Delaunay, F.; Famiano, M. A.; Hui, H.; Imai, N.; Iwasaki, H.; Motobayashi, T.; Niikura, M.; Onishi, T.; Rogers, A. M.; Sakurai, H.; Suzuki, H.; Takeshita, E.; Takeuchi, S.; Wallace, M. S.

    2007-10-01

    An exponential dependence of the fragmentation cross section on the average binding energy is observed and reproduced with a statistical model. The observed functional dependence is robust and allows the extraction of binding energies from measured cross sections. From the systematics of Cu isotope cross sections, the binding energies of Cu76,77,78,79 have been extracted. They are 636.94±0.4,647.1±0.4,651.6±0.4, and 657.8±0.5 MeV, respectively. Specifically, the uncertainty of the binding energy of Cu75 is reduced from 980 keV, as listed in the 2003 mass table of Audi, Wapstra, and Thibault to 400 keV. The predicted cross sections of two near drip-line nuclei, Na39 and Mg40 from the fragmentation of Ca48 are discussed.

  7. Structural and binding properties of two paralogous fatty acid binding proteins of Taenia solium metacestode.

    Directory of Open Access Journals (Sweden)

    Seon-Hee Kim

    Full Text Available BACKGROUND: Fatty acid (FA binding proteins (FABPs of helminths are implicated in acquisition and utilization of host-derived hydrophobic substances, as well as in signaling and cellular interactions. We previously demonstrated that secretory hydrophobic ligand binding proteins (HLBPs of Taenia solium metacestode (TsM, a causative agent of neurocysticercosis (NC, shuttle FAs in the surrounding host tissues and inwardly transport the FAs across the parasite syncytial membrane. However, the protein molecules responsible for the intracellular trafficking and assimilation of FAs have remained elusive. METHODOLOGY/PRINCIPAL FINDINGS: We isolated two novel TsMFABP genes (TsMFABP1 and TsMFABP2, which encoded 133- and 136-amino acid polypeptides with predicted molecular masses of 14.3 and 14.8 kDa, respectively. They shared 45% sequence identity with each other and 15-95% with other related-members. Homology modeling demonstrated a characteristic β-barrel composed of 10 anti-parallel β-strands and two α-helices. TsMFABP2 harbored two additional loops between β-strands two and three, and β-strands six and seven, respectively. TsMFABP1 was secreted into cyst fluid and surrounding environments, whereas TsMFABP2 was intracellularly confined. Partially purified native proteins migrated to 15 kDa with different isoelectric points of 9.2 (TsMFABP1 and 8.4 (TsMFABP2. Both native and recombinant proteins bound to 11-([5-dimethylaminonaphthalene-1-sulfonyl]aminoundecannoic acid, dansyl-DL-α-amino-caprylic acid, cis-parinaric acid and retinol, which were competitively inhibited by oleic acid. TsMFABP1 exhibited high affinity toward FA analogs. TsMFABPs showed weak binding activity to retinol, but TsMFABP2 showed relatively high affinity. Isolation of two distinct genes from an individual genome strongly suggested their paralogous nature. Abundant expression of TsMFABP1 and TsMFABP2 in the canal region of worm matched well with the histological distributions

  8. Ivermectin binding sites in human and invertebrate Cys-loop receptors

    DEFF Research Database (Denmark)

    Lynagh, Timothy Peter; Lynch, Joseph W

    2012-01-01

    modelling now explain how ivermectin binds to these receptors and reveal why it is selective for invertebrate members of the Cys-loop receptor family. Combining this with emerging genomic information, we are now in a position to predict species sensitivity to ivermectin and better understand the molecular...

  9. Mannan-binding lectin and MBL-associated serine protease-2

    DEFF Research Database (Denmark)

    Jorgensen, J.; Ytting, H.; Steffensen, R.M.;

    2008-01-01

    used for detection, evaluation of prognosis, therapy selection and monitoring. The serum proteins of the innate immune system mannan-binding lectin (MBL) and MBL-associated serine protease-2 (MASP-2) are novel biomarkers under validation in CRC. Low preoperative MBL levels are predictive of pneumonia...

  10. Identification of candidate transcription factor binding sites in the cattle genome

    Science.gov (United States)

    A resource that provides candidate transcription factor binding sites does not currently exist for cattle. Such data is necessary, as predicted sites may serve as excellent starting locations for future 'omics studies to develop transcriptional regulation hypotheses. In order to generate this resour...

  11. Cloud computing for protein-ligand binding site comparison.

    Science.gov (United States)

    Hung, Che-Lun; Hua, Guan-Jie

    2013-01-01

    The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

  12. Cloud computing for protein-ligand binding site comparison.

    Science.gov (United States)

    Hung, Che-Lun; Hua, Guan-Jie

    2013-01-01

    The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery. PMID:23762824

  13. MicroRNA binding sites in C. elegans 3' UTRs.

    Science.gov (United States)

    Liu, Chaochun; Rennie, William A; Mallick, Bibekanand; Kanoria, Shaveta; Long, Dang; Wolenc, Adam; Carmack, C Steven; Ding, Ye

    2014-01-01

    MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Since the discovery of lin-4, the founding member of the miRNA family, over 360 miRNAs have been identified for Caenorhabditis elegans (C. elegans). Prediction and validation of targets are essential for elucidation of regulatory functions of these miRNAs. For C. elegans, crosslinking immunoprecipitation (CLIP) has been successfully performed for the identification of target mRNA sequences bound by Argonaute protein ALG-1. In addition, reliable annotation of the 3' untranslated regions (3' UTRs) as well as developmental stage-specific expression profiles for both miRNAs and 3' UTR isoforms are available. By utilizing these data, we developed statistical models and bioinformatics tools for both transcriptome-scale and developmental stage-specific predictions of miRNA binding sites in C. elegans 3' UTRs. In performance evaluation via cross validation on the ALG-1 CLIP data, the models were found to offer major improvements over established algorithms for predicting both seed sites and seedless sites. In particular, our top-ranked predictions have a substantially higher true positive rate, suggesting a much higher likelihood of positive experimental validation. A gene ontology analysis of stage-specific predictions suggests that miRNAs are involved in dynamic regulation of biological functions during C. elegans development. In particular, miRNAs preferentially target genes related to development, cell cycle, trafficking, and cell signaling processes. A database for both transcriptome-scale and stage-specific predictions and software for implementing the prediction models are available through the Sfold web server at http://sfold.wadsworth.org. PMID:24827614

  14. Genome-wide analysis of PDZ domain binding reveals inherent functional overlap within the PDZ interaction network.

    Directory of Open Access Journals (Sweden)

    Aartjan J W te Velthuis

    Full Text Available Binding selectivity and cross-reactivity within one of the largest and most abundant interaction domain families, the PDZ family, has long been enigmatic. The complete human PDZ domain complement (the PDZome consists of 267 domains and we applied here a Bayesian selectivity model to predict hundreds of human PDZ domain interactions, using target sequences of 22,997 non-redundant proteins. Subsequent analysis of these binding scores shows that PDZs can be divided into two genome-wide clusters that coincide well with the division between canonical class 1 and 2 PDZs. Within the class 1 PDZs we observed binding overlap at unprecedented levels, mediated by two residues at positions 1 and 5 of the second α-helix of the binding pocket. Eight PDZ domains were subsequently selected for experimental binding studies and to verify the basics of our predictions. Overall, the PDZ domain class 1 cross-reactivity identified here implies that auxiliary mechanisms must be in place to overcome this inherent functional overlap and to minimize cross-selectivity within the living cell. Indeed, when we superimpose PDZ domain binding affinities with gene ontologies, network topology data and the domain position within a PDZ superfamily protein, functional overlap is minimized and PDZ domains position optimally in the binding space. We therefore propose that PDZ domain selectivity is achieved through cellular context rather than inherent binding specificity.

  15. Major histocompatibility complex linked databases and prediction tools for designing vaccines.

    Science.gov (United States)

    Singh, Satarudra Prakash; Mishra, Bhartendu Nath

    2016-03-01

    Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide-MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics.

  16. Using Deep Learning for Compound Selectivity Prediction.

    Science.gov (United States)

    Zhang, Ruisheng; Li, Juan; Lu, Jingjing; Hu, Rongjing; Yuan, Yongna; Zhao, Zhili

    2016-01-01

    Compound selectivity prediction plays an important role in identifying potential compounds that bind to the target of interest with high affinity. However, there is still short of efficient and accurate computational approaches to analyze and predict compound selectivity. In this paper, we propose two methods to improve the compound selectivity prediction. We employ an improved multitask learning method in Neural Networks (NNs), which not only incorporates both activity and selectivity for other targets, but also uses a probabilistic classifier with a logistic regression. We further improve the compound selectivity prediction by using the multitask learning method in Deep Belief Networks (DBNs) which can build a distributed representation model and improve the generalization of the shared tasks. In addition, we assign different weights to the auxiliary tasks that are related to the primary selectivity prediction task. In contrast to other related work, our methods greatly improve the accuracy of the compound selectivity prediction, in particular, using the multitask learning in DBNs with modified weights obtains the best performance. PMID:26892071

  17. Predicting Nanocrystal Shape through Consideration of Surface-Ligand Interactions

    KAUST Repository

    Bealing, Clive R.

    2012-03-27

    Density functional calculations for the binding energy of oleic acid-based ligands on Pb-rich {100} and {111} facets of PbSe nanocrystals determine the surface energies as a function of ligand coverage. Oleic acid is expected to bind to the nanocrystal surface in the form of lead oleate. The Wulff construction predicts the thermodynamic equilibrium shape of the PbSe nanocrystals. The equilibrium shape is a function of the ligand surface coverage, which can be controlled by changing the concentration of oleic acid during synthesis. The different binding energy of the ligand on the {100} and {111} facets results in different equilibrium ligand coverages on the facets, and a transition in the equilibrium shape from octahedral to cubic is predicted when increasing the ligand concentration during synthesis. © 2012 American Chemical Society.

  18. Nonlinear Combustion Instability Prediction

    Science.gov (United States)

    Flandro, Gary

    2010-01-01

    The liquid rocket engine stability prediction software (LCI) predicts combustion stability of systems using LOX-LH2 propellants. Both longitudinal and transverse mode stability characteristics are calculated. This software has the unique feature of being able to predict system limit amplitude.

  19. Thermodynamics of ligand binding to acyl-coenzyme A binding protein studied by titration calorimetry

    DEFF Research Database (Denmark)

    Færgeman, Nils J.; Sigurskjold, B W; Kragelund, B B;

    1996-01-01

    Ligand binding to recombinant bovine acyl-CoA binding protein (ACBP) was examined using isothermal microcalorimetry. Microcalorimetric measurements confirm that the binding affinity of acyl-CoA esters for ACBP is strongly dependent on the length of the acyl chain with a clear preference for acyl-...

  20. Biodiscovery of aluminum binding peptides

    Science.gov (United States)

    Adams, Bryn L.; Sarkes, Deborah A.; Finch, Amethist S.; Hurley, Margaret M.; Stratis-Cullum, Dimitra

    2013-05-01

    Cell surface peptide display systems are large and diverse libraries of peptides (7-15 amino acids) which are presented by a display scaffold hosted by a phage (virus), bacteria, or yeast cell. This allows the selfsustaining peptide libraries to be rapidly screened for high affinity binders to a given target of interest, and those binders quickly identified. Peptide display systems have traditionally been utilized in conjunction with organic-based targets, such as protein toxins or carbon nanotubes. However, this technology has been expanded for use with inorganic targets, such as metals, for biofabrication, hybrid material assembly and corrosion prevention. While most current peptide display systems employ viruses to host the display scaffold, we have recently shown that a bacterial host, Escherichia coli, displaying peptides in the ubiquitous, membrane protein scaffold eCPX can also provide specific peptide binders to an organic target. We have, for the first time, extended the use of this bacterial peptide display system for the biodiscovery of aluminum binding 15mer peptides. We will present the process of biopanning with macroscopic inorganic targets, binder enrichment, and binder isolation and discovery.

  1. CTCF Binding Polarity Determines Chromatin Looping

    NARCIS (Netherlands)

    de Wit, Elzo; Vos, Erica S M; Holwerda, Sjoerd J B; Valdes-Quezada, Christian; Verstegen, Marjon J A M; Teunissen, Hans; Splinter, Erik; Wijchers, Patrick J; Krijger, Peter H L; de Laat, Wouter

    2015-01-01

    CCCTC-binding factor (CTCF) is an architectural protein involved in the three-dimensional (3D) organization of chromatin. In this study, we assayed the 3D genomic contact profiles of a large number of CTCF binding sites with high-resolution 4C-seq. As recently reported, our data also suggest that ch

  2. Localization-enhanced biexciton binding in semiconductors

    DEFF Research Database (Denmark)

    Langbein, Wolfgang Werner; Hvam, Jørn Märcher

    1999-01-01

    The influence of excitonic localization on the binding energy of biexcitons is investigated for quasi-three-dimensional and quasi-two-dimensional AlxGa1-xAs structures. An increase of the biexciton binding energy is observed for localization energies comparable to or larger than the free biexcito...

  3. Gravitational Binding Energy in Charged Cylindrical Symmetry

    CERN Document Server

    Sharif, M

    2014-01-01

    We consider static cylindrically symmetric charged gravitating object with perfect fluid and investigate the gravitational binding energy. It is found that only the localized part of the mass function provides the gravitational binding energy, whereas the non-localized part generated by the electric coupling does not contribute for such energy.

  4. Triazatriangulene as binding group for molecular electronics

    DEFF Research Database (Denmark)

    Wei, Zhongming; Wang, Xintai; Borges, Anders;

    2014-01-01

    The triazatriangulene (TATA) ring system was investigated as a binding group for tunnel junctions of molecular wires on gold surfaces. Self-assembled monolayers (SAMs) of TATA platforms with three different lengths of phenylene wires were fabricated, and their electrical conductance was recorded ...... with its high stability and directionality make this binding group very attractive for molecular electronic measurements and devices. (Figure Presented)....

  5. Binding of Quasi-Two-Dimensional Biexcitons

    DEFF Research Database (Denmark)

    Birkedal, Dan; Singh, Jai; Vadim, Lyssenko;

    1996-01-01

    Biexciton binding in GaAs quantum wells has been investigated for a range of well thicknesses (80-160 Angstrom) with spectrally resolved photoluminescence and transient degenerate four-wave mixing. Both light and heavy hole biexcitons are observed. The ratio of the binding energy of the heavy hole...

  6. (TH) diazepam binding to human granulocytes

    Energy Technology Data Exchange (ETDEWEB)

    Bond, P.A.; Cundall, R.L.; Rolfe, B.

    1985-07-08

    (TH)-diazepam binds to sites on human granulocyte membranes, with little or no binding to platelets or lymphocytes. These (TH)-diazepam binding sites are of the peripheral type, being strongly inhibited by R05-4864 (Ki=6.23nM) but only weakly by clonazepam (Ki=14 M). Binding of (TH) diazepam at 0 is saturable, specific and stereoselective. Scatchard analysis indicates a single class of sites with Bmax of 109 +/- 17f moles per mg of protein and K/sub D/ of 3.07 +/- 0.53nM. Hill plots of saturation experiments gave straight lines with a mean Hill coefficient of 1.03 +/- 0.014. Binding is time dependent and reversible and it varies linearly with granulocyte protein concentration over the range 0.025-0.300 mg of protein. 11 references, 3 figures, 1 table.

  7. [3H] diazepam binding to human granulocytes

    International Nuclear Information System (INIS)

    [3H]-diazepam binds to sites on human granulocyte membranes, with little or no binding to platelets or lymphocytes. These [3H]-diazepam binding sites are of the peripheral type, being strongly inhibited by R05-4864 (Ki=6.23nM) but only weakly by clonazepam (Ki=14μM). Binding of [3H] diazepam at 00 is saturable, specific and stereoselective. Scatchard analysis indicates a single class of sites with Bmax of 109 +/- 17f moles per mg of protein and K/sub D/ of 3.07 +/- 0.53nM. Hill plots of saturation experiments gave straight lines with a mean Hill coefficient of 1.03 +/- 0.014. Binding is time dependent and reversible and it varies linearly with granulocyte protein concentration over the range 0.025-0.300 mg of protein. 11 references, 3 figures, 1 table

  8. Testing earthquake predictions

    Science.gov (United States)

    Luen, Brad; Stark, Philip B.

    2008-01-01

    Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify 'chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as random. The null distribution of the number of successful predictions - or any other test statistic - is taken to be its distribution when the fixed set of predictions is applied to random seismicity. Such tests tacitly assume that the predictions do not depend on the observed seismicity. Conditioning on the predictions in this way sets a low hurdle for statistical significance. Consider this scheme: When an earthquake of magnitude 5.5 or greater occurs anywhere in the world, predict that an earthquake at least as large will occur within 21 days and within an epicentral distance of 50 km. We apply this rule to the Harvard centroid-moment-tensor (CMT) catalog for 2000-2004 to generate a set of predictions. The null hypothesis is that earthquake times are exchangeable conditional on their magnitudes and locations and on the predictions - a common "nonparametric" assumption in the literature. We generate random seismicity by permuting the times of events in the CMT catalog. We consider an event successfully predicted only if (i) it is predicted and (ii) there is no larger event within 50 km in the previous 21 days. The P-value for the observed success rate is <0.001: The method successfully predicts about 5% of earthquakes, far better than 'chance' because the predictor exploits the clustering of earthquakes - occasional foreshocks - which the null hypothesis lacks. Rather than condition on the predictions and use a stochastic model for seismicity, it is preferable to treat the observed seismicity as fixed, and to compare the success rate of the predictions to the success rate of simple-minded predictions like those just described. If the proffered predictions do no better than a simple scheme, they have little value.

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

    Science.gov (United States)

    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

  10. Bacterial periplasmic sialic acid-binding proteins exhibit a conserved binding site

    Energy Technology Data Exchange (ETDEWEB)

    Gangi Setty, Thanuja [Institute for Stem Cell Biology and Regenerative Medicine, NCBS Campus, GKVK Post, Bangalore, Karnataka 560 065 (India); Cho, Christine [Carver College of Medicine, University of Iowa, Iowa City, IA 52242-1109 (United States); Govindappa, Sowmya [Institute for Stem Cell Biology and Regenerative Medicine, NCBS Campus, GKVK Post, Bangalore, Karnataka 560 065 (India); Apicella, Michael A. [Carver College of Medicine, University of Iowa, Iowa City, IA 52242-1109 (United States); Ramaswamy, S., E-mail: ramas@instem.res.in [Institute for Stem Cell Biology and Regenerative Medicine, NCBS Campus, GKVK Post, Bangalore, Karnataka 560 065 (India)

    2014-07-01

    Structure–function studies of sialic acid-binding proteins from F. nucleatum, P. multocida, V. cholerae and H. influenzae reveal a conserved network of hydrogen bonds involved in conformational change on ligand binding. Sialic acids are a family of related nine-carbon sugar acids that play important roles in both eukaryotes and prokaryotes. These sialic acids are incorporated/decorated onto lipooligosaccharides as terminal sugars in multiple bacteria to evade the host immune system. Many pathogenic bacteria scavenge sialic acids from their host and use them for molecular mimicry. The first step of this process is the transport of sialic acid to the cytoplasm, which often takes place using a tripartite ATP-independent transport system consisting of a periplasmic binding protein and a membrane transporter. In this paper, the structural characterization of periplasmic binding proteins from the pathogenic bacteria Fusobacterium nucleatum, Pasteurella multocida and Vibrio cholerae and their thermodynamic characterization are reported. The binding affinities of several mutations in the Neu5Ac binding site of the Haemophilus influenzae protein are also reported. The structure and the thermodynamics of the binding of sugars suggest that all of these proteins have a very well conserved binding pocket and similar binding affinities. A significant conformational change occurs when these proteins bind the sugar. While the C1 carboxylate has been identified as the primary binding site, a second conserved hydrogen-bonding network is involved in the initiation and stabilization of the conformational states.

  11. Bacterial periplasmic sialic acid-binding proteins exhibit a conserved binding site

    International Nuclear Information System (INIS)

    Structure–function studies of sialic acid-binding proteins from F. nucleatum, P. multocida, V. cholerae and H. influenzae reveal a conserved network of hydrogen bonds involved in conformational change on ligand binding. Sialic acids are a family of related nine-carbon sugar acids that play important roles in both eukaryotes and prokaryotes. These sialic acids are incorporated/decorated onto lipooligosaccharides as terminal sugars in multiple bacteria to evade the host immune system. Many pathogenic bacteria scavenge sialic acids from their host and use them for molecular mimicry. The first step of this process is the transport of sialic acid to the cytoplasm, which often takes place using a tripartite ATP-independent transport system consisting of a periplasmic binding protein and a membrane transporter. In this paper, the structural characterization of periplasmic binding proteins from the pathogenic bacteria Fusobacterium nucleatum, Pasteurella multocida and Vibrio cholerae and their thermodynamic characterization are reported. The binding affinities of several mutations in the Neu5Ac binding site of the Haemophilus influenzae protein are also reported. The structure and the thermodynamics of the binding of sugars suggest that all of these proteins have a very well conserved binding pocket and similar binding affinities. A significant conformational change occurs when these proteins bind the sugar. While the C1 carboxylate has been identified as the primary binding site, a second conserved hydrogen-bonding network is involved in the initiation and stabilization of the conformational states

  12. Specific insulin binding in bovine chromaffin cells; demonstration of preferential binding to adrenalin-storing cells

    Energy Technology Data Exchange (ETDEWEB)

    Serck-Hanssen, G.; Soevik, O.

    1987-12-28

    Insulin binding was studied in subpopulations of bovine chromaffin cells enriched in adrenalin-producing cells (A-cells) or noradrenalin-producing cells (NA-cells). Binding of /sup 125/I-insulin was carried out at 15/sup 0/C for 3 hrs in the absence or presence of excess unlabeled hormone. Four fractions of cells were obtained by centrifugation on a stepwise bovine serum albumin gradient. The four fractions were all shown to bind insulin in a specific manner and the highest binding was measured in the cell layers of higher densities, containing mainly A-cells. The difference in binding of insulin to the four subpopulations of chromaffin cells seemed to be related to differences in numbers of receptors as opposed to receptor affinities. The authors conclude that bovine chromaffin cells possess high affinity binding sites for insulin and that these binding sites are mainly confined to A-cells. 24 references, 2 figures, 1 table.

  13. Calmodulin Binding Proteins and Alzheimer's Disease.

    Science.gov (United States)

    O'Day, Danton H; Eshak, Kristeen; Myre, Michael A

    2015-01-01

    The small, calcium-sensor protein, calmodulin, is ubiquitously expressed and central to cell function in all cell types. Here the literature linking calmodulin to Alzheimer's disease is reviewed. Several experimentally-verified calmodulin-binding proteins are involved in the formation of amyloid-β plaques including amyloid-β protein precursor, β-secretase, presenilin-1, and ADAM10. Many others possess potential calmodulin-binding domains that remain to be verified. Three calmodulin binding proteins are associated with the formation of neurofibrillary tangles: two kinases (CaMKII, CDK5) and one protein phosphatase (PP2B or calcineurin). Many of the genes recently identified by genome wide association studies and other studies encode proteins that contain putative calmodulin-binding domains but only a couple (e.g., APOE, BIN1) have been experimentally confirmed as calmodulin binding proteins. At least two receptors involved in calcium metabolism and linked to Alzheimer's disease (mAchR; NMDAR) have also been identified as calmodulin-binding proteins. In addition to this, many proteins that are involved in other cellular events intimately associated with Alzheimer's disease including calcium channel function, cholesterol metabolism, neuroinflammation, endocytosis, cell cycle events, and apoptosis have been tentatively or experimentally verified as calmodulin binding proteins. The use of calmodulin as a potential biomarker and as a therapeutic target is discussed. PMID:25812852

  14. DNA Triplexes That Bind Several Cofactor Molecules.

    Science.gov (United States)

    Vollmer, Sven; Richert, Clemens

    2015-12-14

    Cofactors are critical for energy-consuming processes in the cell. Harnessing such processes for practical applications requires control over the concentration of cofactors. We have recently shown that DNA triplex motifs with a designed binding site can be used to capture and release nucleotides with low micromolar dissociation constants. In order to increase the storage capacity of such triplex motifs, we have explored the limits of ligand binding through designed cavities in the oligopurine tract. Oligonucleotides with up to six non-nucleotide bridges between purines were synthesized and their ability to bind ATP, cAMP or FAD was measured. Triplex motifs with several single-nucleotide binding sites were found to bind purines more tightly than triplexes with one large binding site. The optimized triplex consists of 59 residues and four C3-bridges. It can bind up to four equivalents of ligand with apparent Kd values of 52 µM for ATP, 9 µM for FAD, and 2 µM for cAMP. An immobilized version fuels bioluminescence via release of ATP at body temperature. These results show that motifs for high-density capture, storage and release of energy-rich biomolecules can be constructed from synthetic DNA. PMID:26561335

  15. Copper(II) binding properties of hepcidin.

    Science.gov (United States)

    Kulprachakarn, Kanokwan; Chen, Yu-Lin; Kong, Xiaole; Arno, Maria C; Hider, Robert C; Srichairatanakool, Somdet; Bansal, Sukhvinder S

    2016-06-01

    Hepcidin is a peptide hormone that regulates the homeostasis of iron metabolism. The N-terminal domain of hepcidin is conserved amongst a range of species and is capable of binding Cu(II) and Ni(II) through the amino terminal copper-nickel binding motif (ATCUN). It has been suggested that the binding of copper to hepcidin may have biological relevance. In this study we have investigated the binding of Cu(II) with model peptides containing the ATCUN motif, fluorescently labelled hepcidin and hepcidin using MALDI-TOF mass spectrometry. As with albumin, it was found that tetrapeptide models of hepcidin possessed a higher affinity for Cu(II) than that of native hepcidin. The log K 1 value of hepcidin for Cu(II) was determined as 7.7. Cu(II) binds to albumin more tightly than hepcidin (log K 1 = 12) and in view of the serum concentration difference of albumin and hepcidin, the bulk of kinetically labile Cu(II) present in blood will be bound to albumin. It is estimated that the concentration of Cu(II)-hepcidin will be less than one femtomolar in normal serum and thus the binding of copper to hepcidin is unlikely to play a role in iron homeostasis. As with albumin, small tri and tetra peptides are poor models for the metal binding properties of hepcidin. PMID:26883683

  16. [Binding to chicken liver lactatedehydrogenase (author's transl)].

    Science.gov (United States)

    Lluís, C; Bozal, J

    1976-06-01

    Some information about the lactate dehydrogenase NAD binding site has been obtained by working with coenzymes analogs of incomplete molecules. 5'AMP, 5'-ADP, ATP, 5'-c-AMP and 3'(2)-AMP inhibit chicken liver LDH activity competitively with NADH. 5"-AMP and 5'-ADP show a stronger inhibition power than ATP, suggesting that the presence of one or two phosphate groups at the 5' position of adenosine, is essential for the binding of the coenzyme analogs at the enzyme binding site. Ribose and ribose-5'-P do not appear to inhibit the LDH activity, proving that purine base lacking mononucleotides do not bind to the enzyme. 5"-ADPG inhibits LDH activity in the exactly as 5'-ADP, showing that ribose moiety may be replaced by glucose, without considerable effects on the coenzyme analog binding. 2'-desoxidenosin-5'-phosphate proves to be a poorer inhibitor of the LDH activity than 5'-AMP, indicating that an interaction between the--OH groups and the amino-acids of the LDH active center takes place. Nicotinamide does not produce any inhibition effect, while NMN and CMP induce a much weaker inhibition than the adenine analogues, thus indicating a lesser binding capacity to the enzyme. Therefore, the LDH binding site seems to show some definite specificity towards the adenina groups of the coenzyme.

  17. Structural Analysis of the Ligand-Binding Domain of the Aspartate Receptor Tar from Escherichia coli.

    Science.gov (United States)

    Mise, Takeshi

    2016-07-01

    The Escherichia coli cell-surface aspartate receptor Tar mediates bacterial chemotaxis toward an attractant, aspartate (Asp), and away from a repellent, Ni(2+). These signals are transmitted from the extracellular region of Tar to the cytoplasmic region via the transmembrane domain. The mechanism by which extracellular signals are transmitted into the cell through conformational changes in Tar is predicted to involve a piston displacement of one of the α4 helices of the homodimer. To understand the molecular mechanisms underlying the induction of Tar activity by an attractant, the three-dimensional structures of the E. coli Tar periplasmic domain with and without bound aspartate, Asp-Tar and apo-Tar, respectively, were determined. Of the two ligand-binding sites, only one site was occupied, and it clearly showed the electron density of an aspartate. The slight changes in conformation and the electrostatic surface potential around the aspartate-binding site were observed. In addition, the presence of an aspartate stabilized residues Phe-150' and Arg-73. A pistonlike displacement of helix α4b' was also induced by aspartate binding as predicted by the piston model. Taken together, these small changes might be related to the induction of Tar activity and might disturb binding of the second aspartate to the second binding site in E. coli. PMID:27292793

  18. Differential Nucleosome Occupancies across Oct4-Sox2 Binding Sites in Murine Embryonic Stem Cells.

    Directory of Open Access Journals (Sweden)

    Amy Sebeson

    Full Text Available The binding sequence for any transcription factor can be found millions of times within a genome, yet only a small fraction of these sequences encode functional transcription factor binding sites. One of the reasons for this dichotomy is that many other factors, such as nucleosomes, compete for binding. To study how the competition between nucleosomes and transcription factors helps determine a functional transcription factor site from a predicted transcription factor site, we compared experimentally-generated in vitro nucleosome occupancy with in vivo nucleosome occupancy and transcription factor binding in murine embryonic stem cells. Using a solution hybridization enrichment technique, we generated a high-resolution nucleosome map from targeted regions of the genome containing predicted sites and functional sites of Oct4/Sox2 regulation. We found that at Pax6 and Nes, which are bivalently poised in stem cells, functional Oct4 and Sox2 sites show high amounts of in vivo nucleosome displacement compared to in vitro. Oct4 and Sox2, which are active, show no significant displacement of in vivo nucleosomes at functional sites, similar to nonfunctional Oct4/Sox2 binding. This study highlights a complex interplay between Oct4 and Sox2 transcription factors and nucleosomes among different target genes, which may result in distinct patterns of stem cell gene regulation.

  19. Differential Nucleosome Occupancies across Oct4-Sox2 Binding Sites in Murine Embryonic Stem Cells.

    Science.gov (United States)

    Sebeson, Amy; Xi, Liqun; Zhang, Quanwei; Sigmund, Audrey; Wang, Ji-Ping; Widom, Jonathan; Wang, Xiaozhong

    2015-01-01

    The binding sequence for any transcription factor can be found millions of times within a genome, yet only a small fraction of these sequences encode functional transcription factor binding sites. One of the reasons for this dichotomy is that many other factors, such as nucleosomes, compete for binding. To study how the competition between nucleosomes and transcription factors helps determine a functional transcription factor site from a predicted transcription factor site, we compared experimentally-generated in vitro nucleosome occupancy with in vivo nucleosome occupancy and transcription factor binding in murine embryonic stem cells. Using a solution hybridization enrichment technique, we generated a high-resolution nucleosome map from targeted regions of the genome containing predicted sites and functional sites of Oct4/Sox2 regulation. We found that at Pax6 and Nes, which are bivalently poised in stem cells, functional Oct4 and Sox2 sites show high amounts of in vivo nucleosome displacement compared to in vitro. Oct4 and Sox2, which are active, show no significant displacement of in vivo nucleosomes at functional sites, similar to nonfunctional Oct4/Sox2 binding. This study highlights a complex interplay between Oct4 and Sox2 transcription factors and nucleosomes among different target genes, which may result in distinct patterns of stem cell gene regulation.

  20. Increased Hyaluronan Acid Binding Ability of Spermatozoa Indicating a Better Maturity, Morphology, and Higher DNA Integrity After Micronutrient Supplementation

    OpenAIRE

    Markus Lipovac; Florian Bodner; Alexander Schütz; Harald Kurz; Claus Riedl; Julia Mair; Martin Imhof

    2014-01-01

    Measuring the hyaluronan-binding ability of spermatozoa is useful in predicting the ability of spermatozoa to fertilise oocytes during in vitro fertilisation (IVF). Recent publications discuss an influence of micronutrients on sperm quality. The objective of this paper was to evaluate the effect of a non-prescription nutraceutical containing eight micronutrients on sperm-hyaluronan binding assay (SHBA) values among males with idiopathic sub-/infertility, using an open comparative pilot study....