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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 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.

  4. 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...

  5. Knowledge-based fragment binding prediction.

    Science.gov (United States)

    Tang, Grace W; Altman, Russ B

    2014-04-01

    Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

  6. Predicted metal binding sites for phytoremediation

    OpenAIRE

    Sharma, Ashok; Roy, Sudeep; Tripathi, Kumar Parijat; Roy, Pratibha; Mishra, Manoj; Khan, Feroz; Meena, Abha

    2009-01-01

    Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. The objective of the study is to design and analyze metal binding motifs against the genes involved in phytoremediation. This is being done on the basis of certain pre-requisite amino-acid residues known to bind metal ions/metal complexes in medicinal and aromatic plants (MAP's). Earlier work on MAP's have shown that heavy metals accumulated by aromatic and medicinal plants do no...

  7. A structure-based model for predicting serum albumin binding.

    Directory of Open Access Journals (Sweden)

    Katrina W Lexa

    Full Text Available One of the many factors involved in determining the distribution and metabolism of a compound is the strength of its binding to human serum albumin. While experimental and QSAR approaches for determining binding to albumin exist, various factors limit their ability to provide accurate binding affinity for novel compounds. Thus, to complement the existing tools, we have developed a structure-based model of serum albumin binding. Our approach for predicting binding incorporated the inherent flexibility and promiscuity known to exist for albumin. We found that a weighted combination of the predicted logP and docking score most accurately distinguished between binders and nonbinders. This model was successfully used to predict serum albumin binding in a large test set of therapeutics that had experimental binding data.

  8. Does antibody binding to diverse antigens predict future infection?

    Science.gov (United States)

    Owen, J P; Waite, J L; Holden, K Z; Clayton, D H

    2014-11-01

    We studied diverse antigen binding in hosts and the outcome of parasitism. We used captive-bred F1 descendants of feral rock pigeons (Columba livia) challenged with blood-feeding flies (Hippoboscidae) and a protozoan parasite (Haemoproteus). Enzyme-linked immunosorbent assays (ELISAs) and immunoblots were used to test (i) whether pre-infection IgY antigen binding predicts parasite fitness and (ii) whether antigen binding changes after infection. Assays used extracts from three pigeon parasites (northern fowl mite, Salmonella bacteria and avian pox virus), as well as nonparasitic molecules from cattle, chicken and keyhole limpet. Binding to hippoboscid and S. enterica extracts were predictive of hippoboscid fly fitness. Binding to extracts from hippoboscids, pox virus and nonparasitic organisms was predictive of Haemoproteus infection levels. Antigen binding to all extracts increased after parasite challenge, despite the fact that birds were only exposed to flies and Haemoproteus. Immunoblots suggested innate Ig binding to parasite-associated molecular markers and revealed that new antigens were bound in extracts after infection. These data suggest that host antibody binding to diverse antigens predicts parasite fitness even when the antigens are not related to the infecting parasite. We discuss the implications of these data for the study of host-parasite immunological interaction. PMID:25313676

  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. DNA-binding residues and binding mode prediction with binding-mechanism concerned models

    OpenAIRE

    Oyang Yen-Jen; Liu Yu-Cheng; Huang Chun-Chin; Huang Yu-Feng; Huang Chien-Kang

    2009-01-01

    Abstract Background Protein-DNA interactions are essential for fundamental biological activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two categories of binding mechanisms - sequence-specific and non-specific binding. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs for sequence-specific identification. Protein-DNA non-specific binding shows sequence indepe...

  11. 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.

  12. Reliable prediction of transcription factor binding sites by phylogenetic verification

    OpenAIRE

    Li, Xiaoman; Zhong, Sheng; Wong, Wing H.

    2005-01-01

    We present a statistical methodology that largely improves the accuracy in computational predictions of transcription factor (TF) binding sites in eukaryote genomes. This method models the cross-species conservation of binding sites without relying on accurate sequence alignment. It can be coupled with any motif-finding algorithm that searches for overrepresented sequence motifs in individual species and can increase the accuracy of the coupled motif-finding algorithm. Because this method is ...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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 a...... significant gap in knowledge as HLA DP and DQ molecules are presumably equally important, and have only been studied less because they are more difficult to handle experimentally. RESULTS: In this study, we aimed to narrow this gap by providing a large scale dataset of over 17,000 HLA-peptide binding...... affinities for a set of 11 HLA DP and DQ alleles. We also expanded our dataset for HLA DR alleles resulting in a total of 40,000 MHC class II binding affinities covering 26 allelic variants. Utilizing this dataset, we generated prediction tools utilizing several machine learning algorithms and evaluated...

  14. 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

  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. Reliable prediction of transcription factor binding sites by phylogenetic verification.

    Science.gov (United States)

    Li, Xiaoman; Zhong, Sheng; Wong, Wing H

    2005-11-22

    We present a statistical methodology that largely improves the accuracy in computational predictions of transcription factor (TF) binding sites in eukaryote genomes. This method models the cross-species conservation of binding sites without relying on accurate sequence alignment. It can be coupled with any motif-finding algorithm that searches for overrepresented sequence motifs in individual species and can increase the accuracy of the coupled motif-finding algorithm. Because this method is capable of accurately detecting TF binding sites, it also enhances our ability to predict the cis-regulatory modules. We applied this method on the published chromatin immunoprecipitation (ChIP)-chip data in Saccharomyces cerevisiae and found that its sensitivity and specificity are 9% and 14% higher than those of two recent methods. We also recovered almost all of the previously verified TF binding sites and made predictions on the cis-regulatory elements that govern the tight regulation of ribosomal protein genes in 13 eukaryote species (2 plants, 4 yeasts, 2 worms, 2 insects, and 3 mammals). These results give insights to the transcriptional regulation in eukaryotic organisms. PMID:16286651

  18. The next generation of transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Anthony Mathelier

    Full Text Available Finding where transcription factors (TFs bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs is based on basic position weight matrices (PWMs which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make the strong assumption that each nucleotide participates independently in the corresponding DNA-protein interaction and do not account for flexible length motifs. We introduce transcription factor flexible models (TFFMs to represent TF binding properties. Based on hidden Markov models, TFFMs are flexible, and can model both position interdependence within TFBSs and variable length motifs within a single dedicated framework. The availability of thousands of experimentally validated DNA-TF interaction sequences from ChIP-seq allows for the generation of models that perform as well as PWMs for stereotypical TFs and can improve performance for TFs with flexible binding characteristics. We present a new graphical representation of the motifs that convey properties of position interdependence. TFFMs have been assessed on ChIP-seq data sets coming from the ENCODE project, revealing that they can perform better than both PWMs and the dinucleotide weight matrix extension in discriminating ChIP-seq from background sequences. Under the assumption that ChIP-seq signal values are correlated with the affinity of the TF-DNA binding, we find that TFFM scores correlate with ChIP-seq peak signals. Moreover, using available TF-DNA affinity measurements for the Max TF, we demonstrate that TFFMs constructed from ChIP-seq data correlate with published experimentally measured DNA-binding affinities. Finally, TFFMs allow for the straightforward computation of an integrated TF occupancy score across a sequence. These results demonstrate the capacity of TFFMs to accurately model DNA

  19. 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 giv......-user to make 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...... 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...

  20. 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

  1. Late pregnancy thyroid-binding globulin predicts perinatal depression.

    Science.gov (United States)

    Pedersen, Cort; Leserman, Jane; Garcia, Nacire; Stansbury, Melissa; Meltzer-Brody, Samantha; Johnson, Jacqueline

    2016-03-01

    Previously we found that late pregnancy total and free thyroxine (TT4, FT4) concentrations were negatively related to greater pre and/or postpartum depressive symptoms. In a much larger cohort, the current study examined whether these thyroid indices measured earlier in the third trimester (31-33 weeks) predict subsequent perinatal depression and anxiety ratings as well as syndromal depression. Thyroid-binding globulin (TBG) concentrations increase markedly during pregnancy and may be an index of sensitivity to elevated estrogen levels. TBG was examined in this study because prior findings suggest that postpartum depression is related to sensitivity to mood destabilization by elevated sex hormone concentrations during pregnancy. Our cohort was 199 euthyroid women recruited from a public health obstetrics clinic (63.8% Hispanic, 21.6% Black). After screening and blood draws for hormone measures at pregnancy weeks 31-33, subjects were evaluated during home visits at pregnancy weeks 35-36 as well as postpartum weeks 6 and 12. Evaluations included psychiatric interviews for current and life-time DSM-IV psychiatric history (M.I.N.I.-Plus), subject self-ratings and interviewer ratings for depression and anxiety (Edinburgh Postnatal Depression Scale, Montgomery-Ǻsberg Depression Rating Scale; Spielberger State-Trait Anxiety Inventory, Hamilton Anxiety Inventory), as well as a standardized interview to obtain life-time trauma history. Numerous covariates were included in all regression analyses. Trauma and major depression history were robustly significant predictors of depression and anxiety ratings over the study period when these variables were analyzed individually or in a combined model including FT4 or TBG (pdepression and anxiety ratings (pdepression history, were significant individual predictors of syndromal depression during the study period (pdepression history, FT4 and TBG generally were not significantly predictive of depression or anxiety ratings, and FT4

  2. 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 ...

  3. 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

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

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Nielsen, Morten; Lamberth, K.; Worning, Peder; Sylvester-Hvid, C.; Buus, S.; Brunak, Søren; Lund, Ole

    predicting peptides binding to specific MHC class I alleles. The method combines advanced automatic scoring matrix generation with empirical position specific differential anchor weighting. The method leads to predictions with a comparable or higher accuracy than other established prediction servers, even in...... situations where only very limited data are available for training....

  5. 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.

  6. 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...

  7. 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...

  8. 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...

  9. PREDICTION OF ANTIGENIC AND BINDING SITES OF NEUROTOXIN 23 OF SCORPION (LYCHASMUCRONACTUS SP.)

    OpenAIRE

    Bharati K Thosare; Ingale, Arun G

    2015-01-01

    Identification of antigenic and binding site of protein is highly desirable for the design of vaccines and immunodiagnostics. The present exercise deals with a prediction of antigenic as well as binding sites of neurotoxin 23 of Lychasmucronactus. This species of scorpion having diverse molecules of toxic peptide, the peptide neurotoxin 23 is 96 amino acids long of which 23 to 96 specifically code for neurotoxin. The total of 27 such different ligand binding residue were identifie...

  10. Binding Mode Prediction of Evodiamine within Vanilloid Receptor TRPV1

    OpenAIRE

    Huaping Liang; Liangren Zhang; Wuzhuang Gong; Yanhui Zhang; Zhanli Wang; Lidan Sun; Hui Yu; Hongwei Jin

    2012-01-01

    Accurate assessment of the potential binding mode of drugs is crucial to computer-aided drug design paradigms. It has been reported that evodiamine acts as an agonist of the vanilloid receptor Transient receptor potential vanilloid-1 (TRPV1). However, the precise interaction between evodiamine and TRPV1 was still not fully understood. In this perspective, the homology models of TRPV1 were generated using the crystal structure of the voltage-dependent shaker family K

  11. 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...

  12. Prediction of peptides binding to MHC class I alleles by partial periodic pattern mining

    OpenAIRE

    Meydan, Cem; Sezerman, Uğur; Sezerman, Ugur; Otu, Hasan

    2009-01-01

    MHC (Major Histocompatibility Complex) is a key player in the immune response of an organism. It is important to be able to predict which antigenic peptides will bind to a spe-cific MHC allele and which will not, creating possibilities for controlling immune response and for the applications of immunotherapy. However a problem encountered in the computational binding prediction methods for MHC class I is the presence of bulges and loops in the peptides, changing the total length. Most machine...

  13. Binding Energy Distribution Analysis Method: Hamiltonian Replica Exchange with Torsional Flattening for Binding Mode Prediction and Binding Free Energy Estimation.

    Science.gov (United States)

    Mentes, Ahmet; Deng, Nan-Jie; Vijayan, R S K; Xia, Junchao; Gallicchio, Emilio; Levy, Ronald M

    2016-05-10

    Molecular dynamics modeling of complex biological systems is limited by finite simulation time. The simulations are often trapped close to local energy minima separated by high energy barriers. Here, we introduce Hamiltonian replica exchange (H-REMD) with torsional flattening in the Binding Energy Distribution Analysis Method (BEDAM), to reduce energy barriers along torsional degrees of freedom and accelerate sampling of intramolecular degrees of freedom relevant to protein-ligand binding. The method is tested on a standard benchmark (T4 Lysozyme/L99A/p-xylene complex) and on a library of HIV-1 integrase complexes derived from the SAMPL4 blind challenge. We applied the torsional flattening strategy to 26 of the 53 known binders to the HIV Integrase LEDGF site found to have a binding energy landscape funneled toward the crystal structure. We show that our approach samples the conformational space more efficiently than the original method without flattening when starting from a poorly docked pose with incorrect ligand dihedral angle conformations. In these unfavorable cases convergence to a binding pose within 2-3 Å from the crystallographic pose is obtained within a few nanoseconds of the Hamiltonian replica exchange simulation. We found that torsional flattening is insufficient in cases where trapping is due to factors other than torsional energy, such as the formation of incorrect intramolecular hydrogen bonds and stacking. Work is in progress to generalize the approach to handle these cases and thereby make it more widely applicable. PMID:27070865

  14. Prediction of transcription factor binding to DNA using rule induction methods

    OpenAIRE

    Huss, Mikael; Nordström, Karin

    2005-01-01

    The transcription of DNA into mRNA is initiated and aided by a number of transcription factors (TFs), proteins with DNA-binding regions that attach themselves to binding sites in the DNA (transcription factor binding sites, TFBSs). As it has become apparent that both TFs and TFBSs are highly variable, tools are needed to quantify the strength of the interaction resulting from a certain TF variant binding to a certain TFBS. We used a simple way to predict interactions between protein and DNA: ...

  15. 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 ...

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

    DEFF Research Database (Denmark)

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

    2009-01-01

    Binding of peptides to major histocompatibility complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC genomic region (called HLA) is extremely polymorphic comprising several thousand alleles, each encoding a distinct...... method that generates quantitative predictions of the affinity of any peptide-MHC class I interaction. NetMHCpan-2.0 has been trained on the hitherto largest set of quantitative MHC binding data available, covering HLA-A and HLA-B, as well as chimpanzee, rhesus macaque, gorilla, and mouse MHC class I...... molecules. We show that the NetMHCpan-2.0 method can accurately predict binding to uncharacterized HLA molecules, including HLA-C and HLA-G. Moreover, NetMHCpan-2.0 is demonstrated to accurately predict peptide binding to chimpanzee and macaque MHC class I molecules. The power of NetMHCpan-2.0 to guide...

  17. 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

  18. Prediction of chloride ingress and binding in cement paste

    DEFF Research Database (Denmark)

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

    2007-01-01

    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...... 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...... steady state diffusion however. It simply implies that incremental increases in the concentration of diffusing ions in the pore solution will rapidly re-equilibrate with the hydrates present locally, where, the greater the ratio of bound to free ions, the greater the buffering effect which slows down the...

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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

    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...

  4. 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

  5. FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions.

    Directory of Open Access Journals (Sweden)

    Daniel B Roche

    Full Text Available The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP experiment, utilizing the Matthews Correlation Coefficient (MCC and Binding-site Distance Test (BDT metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall's τ, Spearman's ρ and Pearson's r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC when Receiver Operator Characteristic (ROC analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%, and one of the top manual groups (FN293 tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site

  6. 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...

  7. 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.

  8. 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/.

  9. Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction

    Science.gov (United States)

    Gao, Jun; Liu, Qi; Kang, Hong; Cao, Zhiwei; Zhu, Ruixin

    2012-01-01

    In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the protein-ligand binding site prediction method presented in our former study, a comparison of different binding site ranking lists was studied. Four kinds of properties, i.e., pocket size, distance from the protein centroid, sequence conservation and the number of hydrophobic residues, have been chosen as the corresponding ranking criterion respectively. Our studies show that the sequence conservation information helps to rank the real pockets with the most successful accuracy compared to others. At the same time, the pocket size and the distance of binding site from the protein centroid are also found to be helpful. In addition, a multi-view ranking aggregation method, which combines the information among those four properties, was further applied in our study. The results show that a better performance can be achieved by the aggregation of the complementary properties in the prediction of ligand-binding sites. PMID:22942732

  10. 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

    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...

  11. 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

  12. Prediction of heme binding residues from protein sequences with integrative sequence profiles

    OpenAIRE

    2012-01-01

    Background The heme-protein interactions are essential for various biological processes such as electron transfer, catalysis, signal transduction and the control of gene expression. The knowledge of heme binding residues can provide crucial clues to understand these activities and aid in functional annotation, however, insufficient work has been done on the research of heme binding residues from protein sequence information. Methods We propose a sequence-based approach for accurate prediction...

  13. 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

  14. 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

  15. 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.

  16. A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity

    OpenAIRE

    Hayik, Seth A.; Dunbrack, Roland; Merz, Kenneth M.

    2010-01-01

    Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaini...

  17. PREDICTION OF ANTIGENIC AND BINDING SITES OF NEUROTOXIN 23 OF SCORPION (LYCHASMUCRONACTUS SP.

    Directory of Open Access Journals (Sweden)

    Bharati K Thosare

    2015-07-01

    Full Text Available Identification of antigenic and binding site of protein is highly desirable for the design of vaccines and immunodiagnostics. The present exercise deals with a prediction of antigenic as well as binding sites of neurotoxin 23 of Lychasmucronactus. This species of scorpion having diverse molecules of toxic peptide, the peptide neurotoxin 23 is 96 amino acids long of which 23 to 96 specifically code for neurotoxin. The total of 27 such different ligand binding residue were identified by ConSurf and Raptor X server. The web tool Ellipro which implements Modeller and Jmol viewer, predicted and visualized the linear and discontinuous antibody epitopes ofneurotoxin 23 protein sequence.Thus the information discussed here provides a clue for understanding antigenic site and molecular function of neurotoxin 23.

  18. How well do lipophilicity parameters, MEEKC microemulsion capacity factor, and plasma protein binding predict CNS tissue binding?

    Science.gov (United States)

    Zamek-Gliszczynski, Maciej J; Sprague, Karen E; Espada, Alfonso; Raub, Thomas J; Morton, Stuart M; Manro, Jason R; Molina-Martin, Manuel

    2012-05-01

    Brain fraction unbound (Fu) is critical to understanding the pharmacokinetics/dynamics of central nervous system (CNS) drugs, thus several surrogate predictors have been proposed. At present, correlations between brain Fu, microemulsion electrokinetic chromatography capacity factor (MEEKC k'), plasma Fu, octanol-water partition coefficient (clogP), and LogP at pH 7.4 (clogD(7.4) ) were compared for 94 diverse molecules, and additionally for 587 compounds. MEEKC k' was a better predictor of brain Fu (r(2) = 0.74) than calculated lipophilicity parameters (clogP r(2) = 0.51-0.54, clogD(7.4) r(2) = 0.41-0.44), but it was not superior to plasma Fu (r(2) = 0.74-0.85) as a predictor of brain Fu. MEEKC k' did not predict plasma Fu(r(2) = 0.58) as well as brain Fu, and the extent of improvement over clogP or clogD(7.4) (r(2) = 0.41-0.49) was less pronounced. Although log-log-correlation analysis supported seemingly strong prediction of brain Fu both by MEEKC k' and by plasma Fu (r(2) ≥ 0.74), analysis of prediction error estimated a 10-fold and 6.9-8.6-fold prediction interval for brain Fu estimated using MEEKC k' and plasma Fu, respectively. Therefore, MEEKC k' and plasma Fu can predict the log order of CNS tissue binding, but they cannot provide truly quantitative brain Fu predictions necessary to support in-vitro-to-in-vivo extrapolations and pharmacokinetic/dynamic data interpretation. PMID:22344827

  19. 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.

  20. 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.

  1. 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

  2. Sequence-based prediction of protein-peptide binding sites using support vector machine.

    Science.gov (United States)

    Taherzadeh, Ghazaleh; Yang, Yuedong; Zhang, Tuo; Liew, Alan Wee-Chung; Zhou, Yaoqi

    2016-05-15

    Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computationally as the first step. All existing approaches for predicting protein-peptide binding sites, however, are based on protein structures despite the fact that the structures for most proteins are not yet solved. This article proposes the first machine-learning method called SPRINT to make Sequence-based prediction of Protein-peptide Residue-level Interactions. SPRINT yields a robust and consistent performance for 10-fold cross validations and independent test. The most important feature is evolution-generated sequence profiles. For the test set (1056 binding and non-binding residues), it yields a Matthews' Correlation Coefficient of 0.326 with a sensitivity of 64% and a specificity of 68%. This sequence-based technique shows comparable or more accurate than structure-based methods for peptide-binding site prediction. SPRINT is available as an online server at: http://sparks-lab.org/. © 2016 Wiley Periodicals, Inc. PMID:26833816

  3. 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

  4. 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...

  5. 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

    ., 2008] and [Larsen et al., 2010]). HTMS involves HLA typing, immunoaffinity chromatography of HLA molecules, HLA extraction, and chromatography combined with tandem mass spectrometry, followed by the application of computational algorithms for peptide characterization (Bassani-Sternberg et al., 2010......). Hundreds of naturally processed HLA class I associated peptides have been identified in individual studies using HTMS in normal (Escobar et al., 2008), cancer ( [Antwi et al., 2009] and [Bassani-Sternberg et al., 2010]), autoimmunity-related (Ben Dror et al., 2010), and infected samples (Wahl et al, 2010...... 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...

  6. 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

  7. 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

  8. 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

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

    Science.gov (United States)

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

    2015-01-01

    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. PMID:25608737

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

    OpenAIRE

    Marharyta Petukh; Luogeng Dai; Emil Alexov

    2016-01-01

    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,...

  11. 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...

  12. 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.

  13. Binding affinity prediction of novel estrogen receptor ligands using receptor-based 3-D QSAR methods.

    Science.gov (United States)

    Sippl, Wolfgang

    2002-12-01

    We have recently reported the development of a 3-D QSAR model for estrogen receptor ligands showing a significant correlation between calculated molecular interaction fields and experimentally measured binding affinity. The ligand alignment obtained from docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection procedure, a significant and robust model was obtained (q(2)(LOO)=0.921, SDEP=0.345). To further analyze the robustness and the predictivity of the established model several recently developed estrogen receptor ligands were selected as external test set. An excellent agreement between predicted and experimental binding data was obtained indicated by an external SDEP of 0.531. Two other traditionally used prediction techniques were applied in order to check the performance of the receptor-based 3-D QSAR procedure. The interaction energies calculated on the basis of receptor-ligand complexes were correlated with experimentally observed affinities. Also ligand-based 3-D QSAR models were generated using program FlexS. The interaction energy-based model, as well as the ligand-based 3-D QSAR models yielded models with lower predictivity. The comparison with the interaction energy-based model and with the ligand-based 3-D QSAR models, respectively, indicates that the combination of receptor-based and 3-D QSAR methods is able to improve the quality of prediction. PMID:12413831

  14. Quantitative prediction of peptide binding to HLA-DP1 protein.

    Science.gov (United States)

    Ivanov, Stefan; Dimitrov, Ivan; Doytchinova, Irini

    2013-01-01

    The exogenous proteins are processed by the host antigen-processing cells. Peptidic fragments of them are presented on the cell surface bound to the major hystocompatibility complex (MHC) molecules class II and recognized by the CD4+ T lymphocytes. The MHC binding is considered as the crucial prerequisite for T-cell recognition. Only peptides able to form stable complexes with the MHC proteins are recognized by the T-cells. These peptides are known as T-cell epitopes. All T-cell epitopes are MHC binders, but not all MHC binders are T-cell epitopes. The T-cell epitope prediction is one of the main priorities of immunoinformatics. In the present study, three chemometric techniques are combined to derive a model for in silico prediction of peptide binding to the human MHC class II protein HLA-DP1. The structures of a set of known peptide binders are described by amino acid z-descriptors. Data are processed by an iterative self-consisted algorithm using the method of partial least squares, and a quantitative matrix (QM) for peptide binding prediction to HLA-DP1 is derived. The QM is validated by two sets of proteins and showed an average accuracy of 86 percent. PMID:24091413

  15. 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.

  16. 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 due to redundant binding core representation. Incorporation of information about the residues flanking the peptide-binding core is shown to significantly improve the prediction accuracy. The method is evaluated on a large-scale benchmark consisting of six independent data sets covering 14...

  17. Predicting DNA-binding sites of proteins from amino acid sequence

    Directory of Open Access Journals (Sweden)

    Wu Feihong

    2006-05-01

    Full Text Available Abstract Background Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach for the identification of amino acid residues involved in protein-DNA interactions. Results We start with a Naïve Bayes classifier trained to predict whether a given amino acid residue is a DNA-binding residue based on its identity and the identities of its sequence neighbors. The input to the classifier consists of the identities of the target residue and 4 sequence neighbors on each side of the target residue. The classifier is trained and evaluated (using leave-one-out cross-validation on a non-redundant set of 171 proteins. Our results indicate the feasibility of identifying interface residues based on local sequence information. The classifier achieves 71% overall accuracy with a correlation coefficient of 0.24, 35% specificity and 53% sensitivity in identifying interface residues as evaluated by leave-one-out cross-validation. We show that the performance of the classifier is improved by using sequence entropy of the target residue (the entropy of the corresponding column in multiple alignment obtained by aligning the target sequence with its sequence homologs as additional input. The classifier achieves 78% overall accuracy with a correlation coefficient of 0.28, 44% specificity and 41% sensitivity in identifying interface residues. Examination of the predictions in the context of 3-dimensional structures of proteins demonstrates the effectiveness of this method in identifying DNA-binding sites from sequence information. In 33% (56 out of 171 of the proteins, the classifier identifies the interaction sites by correctly recognizing at least half of the interface residues. In 87% (149 out of 171 of the proteins, the classifier correctly identifies at least 20% of the interface residues. This suggests the possibility of using such classifiers to identify

  18. 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.

  19. 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

  20. 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...

  1. Modification of a PAMPA model to predict passive gastrointestinal absorption and plasma protein binding.

    Science.gov (United States)

    Bujard, Alban; Voirol, Hervé; Carrupt, Pierre-Alain; Schappler, Julie

    2015-09-18

    The Parallel Artificial Membrane Permeability Assay (PAMPA) is a well-known high throughput screening (HTS) technique for predicting in vivo passive absorption. In this technique, two compartments are separated by an artificial membrane that mimics passive permeability through biological membranes such as the dermal layer, the gastrointestinal tract (GIT), and the blood brain barrier (BBB). In the present study, a hexadecane artificial membrane (HDM)-PAMPA was used to predict the binding of compounds towards the human plasma using a mixture of human serum albumin (HSA) and alpha-1-acid glycoprotein (AGP). The ratio of HSA and AGP was equivalent to that found in the human plasma for both proteins (∼20:1). A pH gradient (5.0-7.4) was performed to increase the screening capacity and overcome the issue of passive permeability for acidic and amphoteric compounds. With this assay, the prediction of passive GIT absorption was maintained and the compounds were discriminated according to their permeability (on a no-to-high scale). The plasma protein binding (PPB) was estimated via the correlation of the differences between the amount of compound crossing the artificial membrane in assays conducted with and without protein using only a two end-point measurement. The use of a mixture of HSA and AGP to modulate drug permeation was compared to the use of the same concentrations of HSA and AGP used separately. The addition of HSA alone in the acceptor compartment was sufficient for estimating PPB, while it was demonstrated that AGP alone could enable the estimation of AGP binding. PMID:26118348

  2. Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class I major histocompatibility proteins

    DEFF Research Database (Denmark)

    Rognan, D; Lauemoller, S L; Holm, A; Buus, S; Tschinke, V

    1999-01-01

    A simple and fast free energy scoring function (Fresno) has been developed to predict the binding free energy of peptides to class I major histocompatibility (MHC) proteins. It differs from existing scoring functions mainly by the explicit treatment of ligand desolvation and of unfavorable protein...... interactions were found to contribute the most to HLA-A0201-peptide interactions, whereas H-bonding predominates in H-2K(k) recognition. Both cross-validated models were afterward used to predict the binding affinity of a test set of 26 peptides to HLA-A0204 (an HLA allele closely related to HLA-A0201) and of...

  3. Exploiting structural and topological information to improve prediction of RNA-protein binding sites

    Directory of Open Access Journals (Sweden)

    Yuan Zheng

    2009-10-01

    Full Text Available Abstract Background RNA-protein interactions are important for a wide range of biological processes. Current computational methods to predict interacting residues in RNA-protein interfaces predominately rely on sequence data. It is, however, known that interface residue propensity is closely correlated with structural properties. In this paper we systematically study information obtained from sequences and structures and compare their contributions in this prediction problem. Particularly, different geometrical and network topological properties of protein structures are evaluated to improve interface residue prediction accuracy. Results We have quantified the impact of structural information on the prediction accuracy in comparison to the purely sequence based approach using two machine learning techniques: Naïve Bayes classifiers and Support Vector Machines. The highest AUC of 0.83 was achieved by a Support Vector Machine, exploiting PSI-BLAST profile, accessible surface area, betweenness-centrality and retention coefficient as input features. Taking into account that our results are based on a larger non-redundant data set, the prediction accuracy is considerably higher than reported in previous, comparable studies. A protein-RNA interface predictor (PRIP and the data set have been made available at http://www.qfab.org/PRIP. Conclusion Graph-theoretic properties of residue contact maps derived from protein structures such as betweenness-centrality can supplement sequence or structure features to improve the prediction accuracy for binding residues in RNA-protein interactions. While Support Vector Machines perform better on this task, Naïve Bayes classifiers also have been found to achieve good prediction accuracies but require much less training time and are an attractive choice for large scale predictions.

  4. Predicting DNA binding proteins using support vector machine with hybrid fractal features.

    Science.gov (United States)

    Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

    2014-02-21

    DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. PMID:24189096

  5. 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; Kesmir, C; Frimurer, T; Corbet, S; Fomsgaard, A; Hilden, J; Holm, A; Brunak, S

    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...... binding vs non-binding peptides. Furthermore, quantitative ANN allowed a straightforward application of a 'Query by Committee' (QBC) principle whereby particularly information-rich peptides could be identified and subsequently tested experimentally. Iterative training based on QBC-selected peptides...

  6. 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

  7. Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

    Science.gov (United States)

    Grebner, Christoph; Iegre, Jessica; Ulander, Johan; Edman, Karl; Hogner, Anders; Tyrchan, Christian

    2016-04-25

    Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein-ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD design cycles. PMID:26974351

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Lund Ole

    2009-09-01

    Full Text Available Abstract Background The major histocompatibility complex (MHC molecule plays a central role in controlling the adaptive immune response to infections. MHC class I molecules present peptides derived from intracellular proteins to cytotoxic T cells, whereas MHC class II molecules stimulate cellular and humoral immunity through presentation of extracellularly derived peptides to helper T cells. Identification of which peptides will bind a given MHC molecule is thus of great importance for the understanding of host-pathogen interactions, and large efforts have been placed in developing algorithms capable of predicting 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 due to redundant binding core representation. Incorporation of information about the residues flanking the peptide-binding core is shown to significantly improve the prediction accuracy. The method is evaluated on a large-scale benchmark consisting of six independent data sets covering 14 human MHC class II alleles, and is demonstrated to outperform other state-of-the-art MHC class II prediction methods. Conclusion The NN-align method is competitive with the state-of-the-art MHC class II peptide binding prediction algorithms. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCII-2.0.

  10. 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

  11. A general integrative genomic feature transcription factor binding site prediction method applied to analysis of USF1 binding in cardiovascular disease

    Directory of Open Access Journals (Sweden)

    Wang Tianyuan

    2009-04-01

    Full Text Available Abstract Transcription factors are key mediators of human complex disease processes. Identifying the target genes of transcription factors will increase our understanding of the biological network leading to disease risk. The prediction of transcription factor binding sites (TFBSs is one method to identify these target genes; however, current prediction methods need improvement. We chose the transcription factor upstream stimulatory factor l (USF1 to evaluate the performance of our novel TFBS prediction method because of its known genetic association with coronary artery disease (CAD and the recent availability of USF1 chromatin immunoprecipitation microarray (ChIP-chip results. The specific goals of our study were to develop a novel and accurate genome-scale method for predicting USF1 binding sites and associated target genes to aid in the study of CAD. Previously published USF1 ChIP-chip data for 1 per cent of the genome were used to develop and evaluate several kernel logistic regression prediction models. A combination of genomic features (phylogenetic conservation, regulatory potential, presence of a CpG island and DNaseI hypersensitivity, as well as position weight matrix (PWM scores, were used as variables for these models. Our most accurate predictor achieved an area under the receiver operator characteristic curve of 0.827 during cross-validation experiments, significantly outperforming standard PWM-based prediction methods. When applied to the whole human genome, we predicted 24,010 USF1 binding sites within 5 kilobases upstream of the transcription start site of 9,721 genes. These predictions included 16 of 20 genes with strong evidence of USF1 regulation. Finally, in the spirit of genomic convergence, we integrated independent experimental CAD data with these USF1 binding site prediction results to develop a prioritised set of candidate genes for future CAD studies. We have shown that our novel prediction method, which employs

  12. 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

  13. 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

  14. 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

  15. 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 ...

  16. A new protein binding pocket similarity measure based on comparison of 3D atom clouds: application to ligand prediction

    OpenAIRE

    Hoffmann, Brice; Zaslavskiy, Mikhail; Vert, Jean-Philippe; Stoven, Véronique

    2009-01-01

    Motivation: Prediction of ligands for proteins of known 3D structure is important to understand structure-function relationship, predict molecular function, or design new drugs.\\\\ Results: We explore a new approach for ligand prediction in which binding pockets are represented by atom clouds. Each target pocket is compared to an ensemble of pockets of known ligands. Pockets are aligned in 3D space with further use of convolution kernels between clouds of points. Performance of the new method ...

  17. 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.

  18. 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.

  19. A Novel Peptide Binding Prediction Approach for HLA-DR Molecule Based on Sequence and Structural Information

    Science.gov (United States)

    Li, Zhao; Zhao, Yilei; Pan, Gaofeng; Tang, Jijun; Guo, Fei

    2016-01-01

    MHC molecule plays a key role in immunology, and the molecule binding reaction with peptide is an important prerequisite for T cell immunity induced. MHC II molecules do not have conserved residues, so they appear as open grooves. As a consequence, this will increase the difficulty in predicting MHC II molecules binding peptides. In this paper, we aim to propose a novel prediction method for MHC II molecules binding peptides. First, we calculate sequence similarity and structural similarity between different MHC II molecules. Then, we reorder pseudosequences according to descending similarity values and use a weight calculation formula to calculate new pocket profiles. Finally, we use three scoring functions to predict binding cores and evaluate the accuracy of prediction to judge performance of each scoring function. In the experiment, we set a parameter α in the weight formula. By changing α value, we can observe different performances of each scoring function. We compare our method with the best function to some popular prediction methods and ultimately find that our method outperforms them in identifying binding cores of HLA-DR molecules. PMID:27340658

  20. 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...... 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...... but also by a refined definition of the MHC-binding environment including information from non-human species....

  1. 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

  2. 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.

  3. 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

  4. 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

  5. Algorithm for prediction of tumour suppressor p53 affinity for binding sites in DNA

    OpenAIRE

    Veprintsev, Dmitry B.; Fersht, Alan R.

    2008-01-01

    The tumour suppressor p53 is a transcription factor that binds DNA in the vicinity of the genes it controls. The affinity of p53 for specific binding sites relative to other DNA sequences is an inherent driving force for specificity, all other things being equal. We measured the binding affinities of systematically mutated consensus p53 DNA-binding sequences using automated fluorescence anisotropy titrations. Based on measurements of the effects of every possible single base-pair substitution...

  6. 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.

  7. MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence

    OpenAIRE

    Passerini, A.; Lippi, M.; P. Frasconi

    2011-01-01

    MetalDetector identifies CYS and HIS involved in transition metal protein binding sites, starting from sequence alone. A major new feature of release 2.0 is the ability to predict which residues are jointly involved in the coordination of the same metal ion. The server is available at http://metaldetector.dsi.unifi.it/v2.0/.

  8. 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.

  9. 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.

  10. 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.

  11. A computational method for the analysis and prediction of protein:phosphopeptide-binding sites

    OpenAIRE

    Joughin, Brian A.; Tidor, Bruce; Yaffe, Michael B.

    2005-01-01

    Phosphopeptide-binding domains, including the FHA, SH2, WW, WD40, MH2, and Polo-box domains, as well as the 14-3-3 proteins, exert control functions in important processes such as cell growth, division, differentiation, and apoptosis. Structures and mechanisms of phosphopeptide binding are generally diverse, revealing few general principles. A computational method for analysis of phosphopeptide-binding domains was therefore developed to elucidate the physical and chemical nature of phosphopep...

  12. Linear Interaction Energy Based Prediction of Cytochrome P450 1A2 Binding Affinities with Reliability Estimation.

    Directory of Open Access Journals (Sweden)

    Luigi Capoferri

    Full Text Available Prediction of human Cytochrome P450 (CYP binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD simulations and Linear Interaction Energy (LIE theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE of 4.1 kJ mol-1 and a standard error in prediction (SDEP in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units.

  13. 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.

  14. 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 k...

  15. 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...... situations where only very limited data are available for training....

  16. 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....

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

    Science.gov (United States)

    Zhang, Guang Lan; DeLuca, David S; Keskin, Derin B; Chitkushev, Lou; Zlateva, Tanya; Lund, Ole; Reinherz, Ellis L; Brusic, Vladimir

    2011-11-30

    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. NetMHCpan and NetMHCIIpan are used as prediction engines. The 13 HLA Class I supertypes are A1, A2, A3, A24, B7, B8, B27, B44, B58, B62, C1, and C4. The 13 HLA Class II DR supertypes are DR1, DR3, DR4, DR6, DR7, DR8, DR9, DR11, DR12, DR13, DR14, DR15, and DR16. In total, MULTIPRED2 enables prediction of peptide binding to 1077 variants representing 26 HLA supertypes. MULTIPRED2 has visualization modules for mapping promiscuous T-cell epitopes as well as those regions of high target concentration - referred to as T-cell epitope hotspots. Novel graphic representations are employed to display the predicted binding peptides and immunological hotspots in an intuitive manner and also to provide a global view of results as heat maps. Another function of MULTIPRED2, which has direct relevance to vaccine design, is the calculation of population coverage. Currently it calculates population coverage in five major 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/. PMID:21130094

  18. AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility.

    Science.gov (United States)

    Ravindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S; Olson, Arthur J; Sanner, Michel F

    2015-12-01

    Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR-AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 -a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down

  19. AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility.

    Directory of Open Access Journals (Sweden)

    Pradeep Anand Ravindranath

    2015-12-01

    Full Text Available Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1 exponential growth of the search space, demanding more efficient search methods; and 2 increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR-AutoDock for Flexible Receptors (ADFR, a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1 SEQ17 -a receptor diversity set containing 17 pairs of apo-holo structures; and 2 CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we

  20. Using metal-ligand binding characteristics to predict metal toxicity: quantitative ion character-activity relationships (QICARs).

    OpenAIRE

    Newman, M C; McCloskey, J T; Tatara, C P

    1998-01-01

    Ecological risk assessment can be enhanced with predictive models for metal toxicity. Modelings of published data were done under the simplifying assumption that intermetal trends in toxicity reflect relative metal-ligand complex stabilities. This idea has been invoked successfully since 1904 but has yet to be applied widely in quantitative ecotoxicology. Intermetal trends in toxicity were successfully modeled with ion characteristics reflecting metal binding to ligands for a wide range of ef...

  1. 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...

  2. 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...

  3. Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes.

    Directory of Open Access Journals (Sweden)

    Valerie A Walshe

    Full Text Available BACKGROUND: Predictive models of peptide-Major Histocompatibility Complex (MHC binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102. METHODOLOGY/FINDINGS: Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1. CONCLUSIONS/SIGNIFICANCE: A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology.

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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...

  9. Towards predictable transmembrane transport: QSAR analysis of anion binding and anion transport

    OpenAIRE

    Gale, Philip A.; Busschaert, Nathalie; Bradberry, Samuel J.; Wenzel, Marco; Haynes, Cally; Hiscock, Jennifer R.; Kirby, Isabelle; Karagiannidis, Louise E.; Moore, Stephen J.; Wells, Neil; Herniman, Julie; Langley, John; Horton, Peter; Mark E. Light; Marques, Igor

    2013-01-01

    The transport of anions across biological membranes by small molecules is a growing research field due to the potential therapeutic benefits of these compounds. However, little is known about the exact mechanism by which these drug-like molecules work and which molecular features make a good transporter. An extended series of 1-hexyl-3-phenylthioureas were synthesized, fully characterized (NMR, mass spectrometry, IR and single crystal diffraction) and their anion binding and anion transport p...

  10. 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 ...

  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

    cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...... presence of similar peptides in the cross-validation dataset. Rather, we found that small size and low sequence/affinity diversity of either training or blind datasets were associated with large differences in cross-validated vs. blind prediction performances. We use these findings to derive quantitative...

  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

    of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that...... the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions....

  13. 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

  14. 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

  15. Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction.

    Science.gov (United States)

    Yu, Dong-Jun; Hu, Jun; Li, Qian-Mu; Tang, Zhen-Min; Yang, Jing-Yu; Shen, Hong-Bin

    2015-01-01

    We are facing an era with annotated biological data rapidly and continuously generated. How to effectively incorporate new annotated data into the learning step is crucial for enhancing the performance of a bioinformatics prediction model. Although machine-learning-based methods have been extensively used for dealing with various biological problems, existing approaches usually train static prediction models based on fixed training datasets. The static approaches are found having several disadvantages such as low scalability and impractical when training dataset is huge. In view of this, we propose a dynamic learning framework for constructing query-driven prediction models. The key difference between the proposed framework and the existing approaches is that the training set for the machine learning algorithm of the proposed framework is dynamically generated according to the query input, as opposed to training a general model regardless of queries in traditional static methods. Accordingly, a query-driven predictor based on the smaller set of data specifically selected from the entire annotated base dataset will be applied on the query. The new way for constructing the dynamic model enables us capable of updating the annotated base dataset flexibly and using the most relevant core subset as the training set makes the constructed model having better generalization ability on the query, showing "part could be better than all" phenomenon. According to the new framework, we have implemented a dynamic protein-ligand binding sites predictor called OSML (On-site model for ligand binding sites prediction). Computer experiments on 10 different ligand types of three hierarchically organized levels show that OSML outperforms most existing predictors. The results indicate that the current dynamic framework is a promising future direction for bridging the gap between the rapidly accumulated annotated biological data and the effective machine-learning-based predictors. OSML

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities

    Science.gov (United States)

    Klus, Petr; Bolognesi, Benedetta; Agostini, Federico; Marchese, Domenica; Zanzoni, Andreas; Tartaglia, Gian Gaetano

    2014-01-01

    Motivation: The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups. Description: The central part of the cleverSuite is the cleverMachine (CM), an algorithm that performs statistics on protein sequences by comparing their physico-chemical propensities. The second element is called cleverClassifier and builds on top of the models generated by the CM to allow classification of new datasets. Results: We applied the cleverSuite to predict secondary structure properties, solubility, chaperone requirements and RNA-binding abilities. Using cross-validation and independent datasets, the cleverSuite reproduces experimental findings with great accuracy and provides models that can be used for future investigations. Availability: The intuitive interface for dataset exploration, analysis and prediction is available at http://s.tartaglialab.com/clever_suite. Contact: gian.tartaglia@crg.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24493033

  3. 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.

  4. 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...

  5. 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.

  6. 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

  7. 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

  8. Comparison of docking methods for carbohydrate binding in calcium-dependent lectins and prediction of the carbohydrate binding mode to sea cucumber lectin CEL-III

    OpenAIRE

    Nurisso, Alessandra; Kozmon, Stanislav; Imberty, Anne

    2008-01-01

    Abstract Lectins display a variety of strategies for specific recognition of carbohydrates. In several lectin families from different origin, one or two calcium ions are involved in the carbohydrate binding site with direct coordination of the sugar hydroxyl groups. Our work implied a molecular docking study involving a set of bacterial and animal calcium-dependant lectins in order to compare the ability of three docking programs to reproduce key carbohydrate-metal interactions. Fl...

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

    DEFF Research Database (Denmark)

    Buus, S.; Lauemoller, S.L.; Worning, Peder; Kesmir, Can; Frimurer, T.; Corbet, S.; Fomsgaard, A.; Hilden, J.; Holm, A.; Brunak, Søren

    2003-01-01

    binding vs non-binding peptides. Furthermore, quantitative ANN allowed a straightforward application of a 'Query by Committee' (QBC) principle whereby particularly information-rich peptides could be identified and subsequently tested experimentally. Iterative training based on QBC-selected peptides...

  10. Directed evolution reveals the binding motif preference of the LC8/DYNLL hub protein and predicts large numbers of novel binders in the human proteome.

    Science.gov (United States)

    Rapali, Péter; Radnai, László; Süveges, Dániel; Harmat, Veronika; Tölgyesi, Ferenc; Wahlgren, Weixiao Y; Katona, Gergely; Nyitray, László; Pál, Gábor

    2011-01-01

    LC8 dynein light chain (DYNLL) is a eukaryotic hub protein that is thought to function as a dimerization engine. Its interacting partners are involved in a wide range of cellular functions. In its dozens of hitherto identified binding partners DYNLL binds to a linear peptide segment. The known segments define a loosely characterized binding motif: [D/S](-4)K(-3)X(-2)[T/V/I](-1)Q(0)[T/V](1)[D/E](2). The motifs are localized in disordered segments of the DYNLL-binding proteins and are often flanked by coiled coil or other potential dimerization domains. Based on a directed evolution approach, here we provide the first quantitative characterization of the binding preference of the DYNLL binding site. We displayed on M13 phage a naïve peptide library with seven fully randomized positions around a fixed, naturally conserved glutamine. The peptides were presented in a bivalent manner fused to a leucine zipper mimicking the natural dimer to dimer binding stoichiometry of DYNLL-partner complexes. The phage-selected consensus sequence V(-5)S(-4)R(-3)G(-2)T(-1)Q(0)T(1)E(2) resembles the natural one, but is extended by an additional N-terminal valine, which increases the affinity of the monomeric peptide twentyfold. Leu-zipper dimerization increases the affinity into the subnanomolar range. By comparing crystal structures of an SRGTQTE-DYNLL and a dimeric VSRGTQTE-DYNLL complex we find that the affinity enhancing valine is accommodated in a binding pocket on DYNLL. Based on the in vitro evolved sequence pattern we predict a large number of novel DYNLL binding partners in the human proteome. Among these EML3, a microtubule-binding protein involved in mitosis contains an exact match of the phage-evolved consensus and binds to DYNLL with nanomolar affinity. These results significantly widen the scope of the human interactome around DYNLL and will certainly shed more light on the biological functions and organizing role of DYNLL in the human and other eukaryotic interactomes

  11. Directed evolution reveals the binding motif preference of the LC8/DYNLL hub protein and predicts large numbers of novel binders in the human proteome.

    Directory of Open Access Journals (Sweden)

    Péter Rapali

    Full Text Available LC8 dynein light chain (DYNLL is a eukaryotic hub protein that is thought to function as a dimerization engine. Its interacting partners are involved in a wide range of cellular functions. In its dozens of hitherto identified binding partners DYNLL binds to a linear peptide segment. The known segments define a loosely characterized binding motif: [D/S](-4K(-3X(-2[T/V/I](-1Q(0[T/V](1[D/E](2. The motifs are localized in disordered segments of the DYNLL-binding proteins and are often flanked by coiled coil or other potential dimerization domains. Based on a directed evolution approach, here we provide the first quantitative characterization of the binding preference of the DYNLL binding site. We displayed on M13 phage a naïve peptide library with seven fully randomized positions around a fixed, naturally conserved glutamine. The peptides were presented in a bivalent manner fused to a leucine zipper mimicking the natural dimer to dimer binding stoichiometry of DYNLL-partner complexes. The phage-selected consensus sequence V(-5S(-4R(-3G(-2T(-1Q(0T(1E(2 resembles the natural one, but is extended by an additional N-terminal valine, which increases the affinity of the monomeric peptide twentyfold. Leu-zipper dimerization increases the affinity into the subnanomolar range. By comparing crystal structures of an SRGTQTE-DYNLL and a dimeric VSRGTQTE-DYNLL complex we find that the affinity enhancing valine is accommodated in a binding pocket on DYNLL. Based on the in vitro evolved sequence pattern we predict a large number of novel DYNLL binding partners in the human proteome. Among these EML3, a microtubule-binding protein involved in mitosis contains an exact match of the phage-evolved consensus and binds to DYNLL with nanomolar affinity. These results significantly widen the scope of the human interactome around DYNLL and will certainly shed more light on the biological functions and organizing role of DYNLL in the human and other eukaryotic interactomes.

  12. RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.

    Science.gov (United States)

    Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

    2014-01-01

    Protein-RNA interactions are central to essential cellular processes such as protein synthesis and regulation of gene expression and play roles in human infectious and genetic diseases. Reliable identification of protein-RNA interfaces is critical for understanding the structural bases and functional implications of such interactions and for developing effective approaches to rational drug design. Sequence-based computational methods offer a viable, cost-effective way to identify putative RNA-binding residues in RNA-binding proteins. Here we report two novel approaches: (i) HomPRIP, a sequence homology-based method for predicting RNA-binding sites in proteins; (ii) RNABindRPlus, a new method that combines predictions from HomPRIP with those from an optimized Support Vector Machine (SVM) classifier trained on a benchmark dataset of 198 RNA-binding proteins. Although highly reliable, HomPRIP cannot make predictions for the unaligned parts of query proteins and its coverage is limited by the availability of close sequence homologs of the query protein with experimentally determined RNA-binding sites. RNABindRPlus overcomes these limitations. We compared the performance of HomPRIP and RNABindRPlus with that of several state-of-the-art predictors on two test sets, RB44 and RB111. On a subset of proteins for which homologs with experimentally determined interfaces could be reliably identified, HomPRIP outperformed all other methods achieving an MCC of 0.63 on RB44 and 0.83 on RB111. RNABindRPlus was able to predict RNA-binding residues of all proteins in both test sets, achieving an MCC of 0.55 and 0.37, respectively, and outperforming all other methods, including those that make use of structure-derived features of proteins. More importantly, RNABindRPlus outperforms all other methods for any choice of tradeoff between precision and recall. An important advantage of both HomPRIP and RNABindRPlus is that they rely on readily available sequence and sequence

  13. 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

  14. [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

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

    OpenAIRE

    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...

  16. 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

  17. 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....

  18. 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.

  19. 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......-based predictions (NetMHCpan). The updated NetMHCpan server was used to predict BoLA-I binding peptides within the P1 structural polyprotein sequence of FMDV (strain A24 Cruzeiro) for BoLA-1*01901, BoLA-2*00801, BoLA-2*01201, and BoLA-4*02401. Peptide binding affinity and stability were determined for these Bo....... The results of these analyses showed that BoLA alleles cluster into three distinct groups with the potential to define “BoLA supertypes.” This streamlined approach identifies potential T cell epitopes from pathogens, such as FMDV, and provides insight into T cell immunity following infection or vaccination....

  20. 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...

  1. 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

  2. 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...

  3. 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.

  4. 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; Nielsen, Morten; Wallin, Stefan; Paulsson, Kajsa Maria; Westerdahl, Helena

    2013-01-01

    The major histocompatibility complex (MHC) genes are the most polymorphic genes found in the vertebrate genome, and they encode proteins that play an essential role in the adaptive immune response. Many songbirds (passerines) have been shown to have a large number of transcribed MHC class I genes...... 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 their...... 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...

  5. Prediction of binding modes and affinities of 4-substituted-2,3,5,6-tetrafluorobenzenesulfonamide inhibitors to the carbonic anhydrase receptor by docking and ONIOM calculations.

    Science.gov (United States)

    Samanta, Pabitra Narayan; Das, Kalyan Kumar

    2016-01-01

    Inhibition activities of a series of 4-substituted-2,3,5,6-tetrafluorobenzenesulfonamides against the human carbonic anhydrase II (HCAII) enzyme have been explored by employing molecular docking and hybrid QM/MM methods. The docking protocol has been employed to assess the best pose of each ligand in the active site cavity of the enzyme, and probe the interactions with the amino acid residues. The docking calculations reveal that the inhibitor binds to the catalytic Zn(2+) site through the deprotonated sulfonamide nitrogen atom by making several hydrophobic and hydrogen bond interactions with the side chain residues depending on the substituted moiety. A cross-docking approach has been adopted prior to the hybrid QM/MM calculation to validate the docked poses. A correlation between the experimental dissociation constants and the docked free energies for the enzyme-inhibitor complexes has been established. Two-layered ONIOM calculations based on QM/MM approach have been performed to evaluate the binding efficacy of the inhibitors. The inhibitor potency has been predicted from the computed binding energies after taking into account of the electronic phenomena associated with enzyme-inhibitor interactions. Both the hybrid (B3LYP) and meta-hybrid (M06-2X) functionals are used for the description of the QM region. To improve the correlation between the experimental biological activity and the theoretical results, a three-layered ONIOM calculation has been carried out and verified for some of the selected inhibitors. The charge transfer stabilization energies are calculated via natural bond orbital analysis to recognize the donor-acceptor interaction in the binding pocket of the enzyme. The nature of binding between the inhibitors and HCAII active site is further analyzed from the electron density distribution maps. PMID:26619075

  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. MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence

    OpenAIRE

    Lippi, Marco; Passerini, Andrea; Punta, Marco; Rost, Burkhard; Frasconi, Paolo

    2008-01-01

    Summary: The web server MetalDetector classifies histidine residues in proteins into one of two states (free or metal bound) and cysteines into one of three states (free, metal bound or disulfide bridged). A decision tree integrates predictions from two previously developed methods (DISULFIND and Metal Ligand Predictor). Cross-validated performance assessment indicates that our server predicts disulfide bonding state at 88.6% precision and 85.1% recall, while it identifies cysteines and histi...

  10. Prediction

    OpenAIRE

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  11. MOLECULAR CHAPERONES DNAK AND DNAJ SHARE PREDICTED BINDING SITES ON MOST PROTEINS IN THE E. COLI PROTEOME

    OpenAIRE

    Srinivasan, Sharan R.; Gillies, Anne; Chang, Lyra; Thompson, Andrea D.; Gestwicki, Jason E.

    2012-01-01

    In Escherichia coli, the molecular chaperones DnaK and DnaJ cooperate to assist the folding of newly synthesized or unfolded polypeptides. DnaK and DnaJ bind to hydrophobic motifs in these proteins and also each other to promote folding. This system is thought to be sufficiently versatile to act on the entire proteome, which creates interesting challenges in understanding the large-scale, ternary interactions between DnaK, DnaJ and their thousands of potential substrates. To address this ques...

  12. 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...

  13. 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...

  14. MREdictor: a two-step dynamic interaction model that accounts for mRNA accessibility and Pumilio binding accurately predicts microRNA targets.

    Science.gov (United States)

    Incarnato, Danny; Neri, Francesco; Diamanti, Daniela; Oliviero, Salvatore

    2013-10-01

    The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation. Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3'-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility. On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures. Moreover, we implement the miRNA-MRE duplex pairing as a two-step model, which better fits the available structural data. This algorithm, called MREdictor, allows for the identification of miRNA targets in poorly accessible regions and is not restricted to a perfect seed-match; these features are not present in other computational prediction methods. PMID:23863844

  15. 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

  16. 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

  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. Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System

    DEFF Research Database (Denmark)

    Rapin, N.; Lund, Ole; Bernaschi, M.;

    2010-01-01

    proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives......We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-IMMSIM, such that it represents pathogens, as well...... for a better understanding of the immune system....

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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 ...

  5. Amino acid sequence of the ligand-binding domain of the aryl hydrocarbon receptor 1 predicts sensitivity of wild birds to effects of dioxin-like compounds.

    Science.gov (United States)

    Farmahin, Reza; Manning, Gillian E; Crump, Doug; Wu, Dongmei; Mundy, Lukas J; Jones, Stephanie P; Hahn, Mark E; Karchner, Sibel I; Giesy, John P; Bursian, Steven J; Zwiernik, Matthew J; Fredricks, Timothy B; Kennedy, Sean W

    2013-01-01

    The sensitivity of avian species to the toxic effects of dioxin-like compounds (DLCs) varies up to 1000-fold among species, and this variability has been associated with interspecies differences in aryl hydrocarbon receptor 1 ligand-binding domain (AHR1 LBD) sequence. We previously showed that LD(50) values, based on in ovo exposures to DLCs, were significantly correlated with in vitro EC(50) values obtained with a luciferase reporter gene (LRG) assay that measures AHR1-mediated induction of cytochrome P4501A in COS-7 cells transfected with avian AHR1 constructs. Those findings suggest that the AHR1 LBD sequence and the LRG assay can be used to predict avian species sensitivity to DLCs. In the present study, the AHR1 LBD sequences of 86 avian species were studied, and differences at amino acid sites 256, 257, 297, 324, 337, and 380 were identified. Site-directed mutagenesis, the LRG assay, and homology modeling highlighted the importance of each amino acid site in AHR1 sensitivity to 2,3,7,8-tetrachlorodibenzo-p-dioxin and other DLCs. The results of the study revealed that (1) only amino acids at sites 324 and 380 affect the sensitivity of AHR1 expression constructs of the 86 avian species to DLCs and (2) in vitro luciferase activity of AHR1 constructs containing only the LBD of the species of interest is significantly correlated (r (2) = 0.93, p toxicity data for those species. These results indicate promise for the use of AHR1 LBD amino acid sequences independently, or combined with the LRG assay, to predict avian species sensitivity to DLCs. PMID:22923492

  6. Computational prediction of structure, substrate binding mode, mechanism, and rate for a malaria protease with a novel type of active site.

    Science.gov (United States)

    Bjelic, Sinisa; Aqvist, Johan

    2004-11-23

    The histo-aspartic protease (HAP) from the malaria parasite P. falciparum is one of several new promising targets for drug intervention. The enzyme possesses a novel type of active site, but its 3D structure and mechanism of action are still unknown. Here we use a combination of homology modeling, automated docking searches, and molecular dynamics/reaction free energy profile simulations to predict the enzyme structure, conformation of bound substrate, catalytic mechanism, and rate of the peptide cleavage reaction. We find that the computational tools are sufficiently reliable both for identifying substrate binding modes and for distinguishing between different possible reaction mechanisms. It is found that the favored pathway only involves direct participation by the catalytic aspartate, with the neighboring histidine providing critical stabilization (by a factor of approximately 10000) along the reaction. The calculated catalytic rate constant of about 0.1 s(-1) for a hexapeptide substrate derived from the alpha chain of human hemoglobin is in excellent agreement with experimental kinetic data for a similar peptide fragment. PMID:15544322

  7. Directed Evolution Reveals the Binding Motif Preference of the LC8/DYNLL Hub Protein and Predicts Large Numbers of Novel Binders in the Human Proteome

    OpenAIRE

    Rapali, Péter; Radnai, László; Süveges, Dániel; Harmat, Veronika; Tölgyesi, Ferenc; Weixiao Y. Wahlgren; Katona, Gergely; Nyitray, László; Pál, Gábor

    2011-01-01

    LC8 dynein light chain (DYNLL) is a eukaryotic hub protein that is thought to function as a dimerization engine. Its interacting partners are involved in a wide range of cellular functions. In its dozens of hitherto identified binding partners DYNLL binds to a linear peptide segment. The known segments define a loosely characterized binding motif: [D/S]-4K-3X-2[T/V/I]-1Q0[T/V]1[D/E]2. The motifs are localized in disordered segments of the DYNLL-binding proteins and are often flanked by coiled...

  8. 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

  9. 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...

  10. 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

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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

  16. A highly predictive 3D-QSAR model for binding to the voltage-gated sodium channel: design of potent new ligands.

    Science.gov (United States)

    Zha, Congxiang; Brown, George B; Brouillette, Wayne J

    2014-01-01

    A comprehensive comparative molecular field analysis (CoMFA) model for the binding of ligands to the neuronal voltage-gated sodium channel was generated based on 67 diverse compounds. Earlier published CoMFA models for this target provided μM ligands, but the improved model described here provided structurally novel compounds with low nM IC₅₀. For example, new compounds 94 and 95 had IC₅₀ values of 129 and 119 nM, respectively. PMID:24332655

  17. 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.

  18. 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

  19. 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

  20. 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

    proteins, beta(2)m/SasaUBA*0301, were produced in Escherichia coli, in which the carboxyl terminus of beta(2)-microglobulin is joined together with a flexible (GGGGS)(3) linker to the amino terminus of the heavy chain. One hundred and seven individual phages bound to beta(2)m/SasaUBA*0301 were isolated...... after four rounds of panning from the 7mer random-peptide library. The peptide encoding sequences were determined and peptide alignment led to the prediction of position-specific anchor residue. A prominent proline at position 2 was observed and we predict that it might be one of the anchors at the N...

  1. 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).

  2. 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

  3. 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. PMID:14723617

  4. Regulation of ryanodine receptor RyR2 by protein-protein interactions: prediction of a PKA binding site on the N-terminal domain of RyR2 and its relation to disease causing mutations [v1; ref status: indexed, http://f1000r.es/4tw

    Directory of Open Access Journals (Sweden)

    Belinda Nazan Walpoth

    2015-01-01

    Full Text Available Protein-protein interactions are the key processes responsible for signaling and function in complex networks. Determining the correct binding partners and predicting the ligand binding sites in the absence of experimental data require predictive models. Hybrid models that combine quantitative atomistic calculations with statistical thermodynamics formulations are valuable tools for bioinformatics predictions. We present a hybrid prediction and analysis model for determining putative binding partners and interpreting the resulting correlations in the yet functionally uncharacterized interactions of the ryanodine RyR2 N-terminal domain. Using extensive docking calculations and libraries of hexameric peptides generated from regulator proteins of the RyR2 channel, we show that the residues 318-323 of protein kinase A, PKA, have a very high affinity for the N-terminal of RyR2. Using a coarse grained Elastic Net Model, we show that the binding site lies at the end of a pathway of evolutionarily conserved residues in RyR2. The two disease causing mutations are also on this path. The program for the prediction of the energetically responsive residues by the Elastic Net Model is freely available on request from the corresponding author.

  5. Prediction of a key role of motifs binding E2F and NR2F in down-regulation of numerous genes during the development of the mouse hippocampus

    Directory of Open Access Journals (Sweden)

    Kaminska Bozena

    2006-08-01

    Full Text Available Abstract Background We previously demonstrated that gene expression profiles during neuronal differentiation in vitro and hippocampal development in vivo were very similar, due to a conservation of the important second singular value decomposition (SVD mode (Mode 2 of expression. The conservation of Mode 2 suggests that it reflects a regulatory mechanism conserved between the two systems. In either dataset, the expression vectors of all the genes form two large clusters that differ in the sign of the contribution of Mode 2, which for the majority of them reflects the difference between down- or up-regulation. Results In the current work, we used a novel approach of analyzing cis-regulation of gene expression in a subspace of a single SVD mode of temporal expression profiles. In the putative upstream regulatory sequences identified by mouse-human homology for all the genes represented in either dataset, we searched for simple features (motifs and pairs of motifs associated with either sign of the loading of Mode 2. Using a cross-system training-test set approach, we identified E2F binding sites as predictors of down-regulation of gene expression during hippocampal development. NR2F binding sites, for the transcription factors Nr2f/COUP and Hnf4, and also NR2F_SP1 pairs of binding sites, were predictors of down-regulation of expression both during hippocampal development and neuronal differentiation. Analysis of another dataset, from gene profiling of myoblast differentiation in vitro, shows that the conservation of Mode 2 extends to the differentiation of mesenchymal cells. This permitted the identification of two more pairs of motifs, one of which included the CDE/CHR tandem element, as features associated with down-regulation both in the differentiating myoblasts and in the developing hippocampus. Of the features we identified, the E2F and CDE/CHR motifs may be associated with the cycling progenitor cell status, while NR2F may be related to the

  6. 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

  7. 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 ...

  8. 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.

  9. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    introduces the NetMHCIIpan-3.0 predictor based on artificial neural networks, which is capable of giving binding affinities to any human MHC class II molecule. Chapter 4 of this thesis gives an overview of bioinformatics tools developed by the Immunological Bioinformatics group at Center for Biological...... 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...... the MHC molecule in question, making it difficult for the non-expert end-user to choose the most suitable predictor. The first paper in this thesis presents a new, publicly available, consensus method for MHC class I predictions. The NetMHCcons predictor combines three state-of-the-art prediction...

  10. 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...

  11. 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 ...

  12. 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

  13. 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.

  14. Treponema pallidum Fibronectin-Binding Proteins

    OpenAIRE

    Cameron, Caroline E.; Brown, Elizabeth L.; Kuroiwa, Janelle M. Y.; Schnapp, Lynn M.; Brouwer, Nathan L.

    2004-01-01

    Putative adhesins were predicted by computer analysis of the Treponema pallidum genome. Two treponemal proteins, Tp0155 and Tp0483, demonstrated specific attachment to fibronectin, blocked bacterial adherence to fibronectin-coated slides, and supported attachment of fibronectin-producing mammalian cells. These results suggest Tp0155 and Tp0483 are fibronectin-binding proteins mediating T. pallidum-host interactions.

  15. Probabilistic Inference of Transcription Factor Binding from Multiple Data Sources

    OpenAIRE

    Lähdesmäki, Harri; Rust, Alistair G.; Shmulevich, Ilya

    2008-01-01

    An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for ...

  16. 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)

  17. Melanin-binding radiopharmaceuticals

    International Nuclear Information System (INIS)

    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

  18. 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.

  19. PoSSuM: a database of similar protein–ligand binding and putative pockets

    OpenAIRE

    Ito, Jun-ichi; Tabei, Yasuo; Shimizu, Kana; Tsuda, Koji; Tomii, Kentaro

    2011-01-01

    Numerous potential ligand-binding sites are available today, along with hundreds of thousands of known binding sites observed in the PDB. Exhaustive similarity search for such vastly numerous binding site pairs is useful to predict protein functions and to enable rapid screening of target proteins for drug design. Existing databases of ligand-binding sites offer databases of limited scale. For example, SitesBase covers only ∼33 000 known binding sites. Inferring protein function and drug disc...

  20. 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...

  1. 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 ...

  2. 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...

  3. Crystal structure and pharmacological characterization of a novel N-methyl-D-aspartate (NMDA) receptor antagonist at the GluN1 glycine binding site

    DEFF Research Database (Denmark)

    Kvist, Trine; Steffensen, Thomas Bielefeldt; Greenwood, Jeremy R;

    2013-01-01

    the competitive interaction and high potency. To delineate the binding mechanism, we have solved the crystal structure of the GluN1 ligand-binding domain in complex with TK40 and show that TK40 binds to the orthosteric binding site of the GluN1 subunit with a binding mode that was also predicted by virtual...

  4. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  5. Inhibition of selectin binding

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, Jon O. (Rodeo, CA); Spevak, Wayne R. (Albany, CA); Dasgupta, Falguni (New Delhi, IN); Bertozzi, Caroline (Albany, CA)

    2001-10-09

    This invention provides compositions for inhibiting the binding between two cells, one expressing P- or L-selectin on the surface and the other expressing the corresponding ligand. A covalently crosslinked lipid composition is prepared having saccharides and acidic group on separate lipids. The composition is then interposed between the cells so as to inhibit binding. Inhibition can be achieved at an effective oligosaccharide concentration as low as 10.sup.6 fold below that of the free saccharide. Since selectins are involved in recruiting cells to sites of injury, these composition scan be used to palliate certain inflammatory and immunological conditions.

  6. Inhibition of selectin binding

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, J.O.; Spevak, W.R.; Dasgupta, F.; Bertozzi, C.

    1999-10-05

    This invention provides a system for inhibiting the binding between two cells, one expressing P- or L-selectin on the surface and the other expressing the corresponding ligand. A covalently crosslinked lipid composition is prepared having saccharides and acidic group on separate lipids. The composition is then interposed between the cells so as to inhibit binding. Inhibition can be achieved at an effective oligosaccharide concentration as low as 10{sup 6} fold below that of the free saccharide. Since selectins are involved in recruiting cells to sites of injury, this system can be used to palliate certain inflammatory and immunological conditions.

  7. Inhibition of selectin binding

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, Jon O. (Rodeo, CA); Spevak, Wayne R. (Albany, CA); Dasgupta, Falguni (New Delhi, IN); Bertozzi, Caroline (Albany, CA)

    1999-01-01

    This invention provides compositions for inhibiting the binding between two cells, one expressing P- or L-selectin on the surface and the other expressing the corresponding ligand. A covalently crosslinked lipid composition is prepared having saccharides and acidic group on separate lipids. The composition is then interposed between the cells so as to inhibit binding. Inhibition can be achieved at an effective oligosaccharide concentration as low as 10.sup.6 fold below that of the free saccharide. Since selectins are involved in recruiting cells to sites of injury, these composition scan be used to palliate certain inflammatory and immunological conditions.

  8. Inhibition of selectin binding

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, J.O.; Spevak, W.R.; Dasgupta, F.; Bertozzi, C.

    1999-11-16

    This invention provides compositions for inhibiting the binding between two cells, one expressing P- or L-selectin on the surface and the other expressing the corresponding ligand. A covalently crosslinked lipid composition is prepared having saccharides and acidic group on separate lipids. The composition is then interposed between the cells so as to inhibit binding. Inhibition can be achieved at an effective oligosaccharide concentration as low as 10{sup 6} fold below that of the free saccharide. Since selectins are involved in recruiting cells to sites of injury, these composition scan be used to palliate certain inflammatory and immunological conditions.

  9. Inhibition of selectin binding

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, Jon O. (Rodeo, CA); Spevak, Wayne R. (Albany, CA); Dasgupta, Falguni (New Delhi, IN); Bertozzi, Carolyn (Albany, CA)

    1999-10-05

    This invention provides a system for inhibiting the binding between two cells, one expressing P- or L-selectin on the surface and the other expressing the corresponding ligand. A covalently crosslinked lipid composition is prepared having saccharides and acidic group on separate lipids. The composition is then interposed between the cells so as to inhibit binding. Inhibition can be achieved at an effective oligosaccharide concentration as low as 10.sup.6 fold below that of the free saccharide. Since selectins are involved in recruiting cells to sites of injury, this system can be used to palliate certain inflammatory and immunological conditions.

  10. 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.

  11. Probabilistic inference of transcription factor binding from multiple data sources.

    Science.gov (United States)

    Lähdesmäki, Harri; Rust, Alistair G; Shmulevich, Ilya

    2008-01-01

    An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for easy and systematic integration of our binding predictions into other probabilistic modeling methods, such as expression-based gene network inference. The method answers the question of whether the whole analyzed promoter has a binding site, but can also be extended to estimate the binding probability at each nucleotide position. Further, we introduce an extension to model combinatorial regulation by several TFs. Most importantly, the proposed methods can make principled probabilistic inference from multiple evidence sources, such as, multiple statistical models (motifs) of the TFs, evolutionary conservation, regulatory potential, CpG islands, nucleosome positioning, DNase hypersensitive sites, ChIP-chip binding segments and other (prior) sequence-based biological knowledge. We developed both a likelihood and a Bayesian method, where the latter is implemented with a Markov chain Monte Carlo algorithm. Results on a carefully constructed test set from the mouse genome demonstrate that principled data fusion can significantly improve the performance of TF binding prediction methods. We also applied the probabilistic modeling framework to all promoters in the mouse genome and the results indicate a sparse connectivity between transcriptional regulators and their target promoters. To facilitate analysis of other sequences and additional data, we have developed an on-line web tool, ProbTF, which implements our probabilistic TF binding prediction method using multiple data sources

  12. 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.

  13. MHC Class II epitope predictive algorithms

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lund, Ole; Buus, S; Lundegaard, Claus

    2010-01-01

    for this is that the MHC-II molecule is open at both ends allowing binding of peptides extending out of the groove. The binding core of MHC-II-bound peptides is therefore not known a priori and the binding motif is hence not readily discernible. Recent progress has been obtained by including the......-specific methods have been able to make reasonably accurate predictions for alleles that were not included in the training data. These methods can be used to define supertypes (clusters) of MHC-II alleles where alleles within each supertype have similar binding specificities. Furthermore, the pan-specific methods...

  14. 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.

  15. Basis for Half-Site Ligand Binding in Yeast NAD+-Specific Isocitrate Dehydrogenase†

    OpenAIRE

    Lin, An-Ping; McAlister-Henn, Lee

    2011-01-01

    Yeast NAD+-specific isocitrate dehydrogenase is an allosterically regulated octameric enzyme composed of four heterodimers of a catalytic IDH2 subunit and a regulatory IDH1 subunit. Despite structural predictions that the enzyme would contain eight isocitrate binding sites, four NAD+ binding sites, and four AMP binding sites, only half of the sites for each ligand are measurable in binding assays. Based on a potential interaction between side chains of Cys-150 residues in IDH2 subunits in eac...

  16. 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...

  17. 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

  18. 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.

  19. Predictive Computational Models of Substrate Binding by a Nucleoside Transporter*

    OpenAIRE

    Collar, Catharine J.; Al-Salabi, Mohammed I.; Stewart, Mhairi L.; Barrett, Michael P; Wilson, W. David; Koning, Harry P. de

    2009-01-01

    Transporters play a vital role in both the resistance mechanisms of existing drugs and effective targeting of their replacements. Melarsoprol and diamidine compounds similar to pentamidine and furamidine are primarily taken up by trypanosomes of the genus Trypanosoma brucei through the P2 aminopurine transporter. In standardized competition experiments with [3H]adenosine, P2 transporter inhibition constants (Ki) have been determined for a diverse dataset of adenosine analogs, diamidines, Food...

  20. 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

  1. 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

  2. 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

  3. 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...

  4. 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

  5. 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....

  6. Carboplatin binding to histidine

    International Nuclear Information System (INIS)

    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

  7. 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.

  8. 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.

  9. 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

  10. Collagen binding to Staphylococcus aureus

    International Nuclear Information System (INIS)

    Staphylococcus aureus can bind soluble collagen in a specific, saturable manner. We have previously shown that some variability exists in the degree of collagen binding between different strains of heat-killed, formaldehyde-fixed S. aureus which are commercially available as immunologic reagents. The present study demonstrates that live S. aureus of the Cowan 1 strain binds amounts of collagen per organism equivalent to those demonstrated previously in heat-killed, formaldehyde-fixed bacteria but has an affinity over 100 times greater, with Kd values of 9.7 X 10(-11) M and 4.3 X 10(-8) M for live and heat-killed organisms, respectively. Studies were also carried out with S. aureus killed by ionizing radiation, since this method of killing the organism seemed less likely to alter the binding moieties on the surface than did heat killing. Bacteria killed by exposure to gamma radiation bound collagen in a manner essentially indistinguishable from that of live organisms. Binding of collagen to irradiated cells of the Cowan 1 strain was rapid, with equilibrium reached by 30 min at 22 degrees C, and was fully reversible. The binding was not inhibited by fibronectin, fibrinogen, C1q, or immunoglobulin G, suggesting a binding site for collagen distinct from those for these proteins. Collagen binding was virtually eliminated in trypsin-treated organisms, indicating that the binding site has a protein component. Of four strains examined, Cowan 1 and S. aureus ATCC 25923 showed saturable, specific binding, while strains Woods and S4 showed a complete lack of binding. These results suggest that some strains of S. aureus contain high-affinity binding sites for collagen. While the number of binding sites per bacterium varied sixfold in the two collagen-binding strains, the apparent affinity was similar

  11. 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.

  12. Melanin binding radiopharmaceuticals

    International Nuclear Information System (INIS)

    We have determined the biodistribution an uptake by the Greene melanoma in the Syrian golden hamster with 21 radiopharmaceuticals. Maximum % uptake and the time at which this occurred are listed. It is essential to know maximum tumor to background ration and the time after injection that this occurs to determine suitability for tumor scanning. The importance of species variation deserves mention. Detection of eye melanoma in humans was quite variable whereas in hamsters it was quite easy to obtain a positive scan with a single pinhole. We then looked at brain uptake in man and found it (the brain scan) to be significant. In addition, we found a high uptake by the lung, something not found in hamsters but not entirely unsuspected of a amine, such as 123I-4,3DMQ. Finally, our clinical experience has shown us some of the vagaries of melanoma-seeking radiopharmaceuticals. This reflects the complexity of melanin and melanin-binding and points out the necessity for a more detailed analysis of the mechanisms involved in melanin binding radionuclides

  13. 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...

  14. 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.

  15. 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...... provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 316 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results are...

  16. Quantitative modeling of transcription factor binding specificities using DNA shape.

    Science.gov (United States)

    Zhou, Tianyin; Shen, Ning; Yang, Lin; Abe, Namiko; Horton, John; Mann, Richard S; Bussemaker, Harmen J; Gordân, Raluca; Rohs, Remo

    2015-04-14

    DNA binding specificities of transcription factors (TFs) are a key component of gene regulatory processes. Underlying mechanisms that explain the highly specific binding of TFs to their genomic target sites are poorly understood. A better understanding of TF-DNA binding requires the ability to quantitatively model TF binding to accessible DNA as its basic step, before additional in vivo components can be considered. Traditionally, these models were built based on nucleotide sequence. Here, we integrated 3D DNA shape information derived with a high-throughput approach into the modeling of TF binding specificities. Using support vector regression, we trained quantitative models of TF binding specificity based on protein binding microarray (PBM) data for 68 mammalian TFs. The evaluation of our models included cross-validation on specific PBM array designs, testing across different PBM array designs, and using PBM-trained models to predict relative binding affinities derived from in vitro selection combined with deep sequencing (SELEX-seq). Our results showed that shape-augmented models compared favorably to sequence-based models. Although both k-mer and DNA shape features can encode interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space. In addition, analyzing the feature weights of DNA shape-augmented models uncovered TF family-specific structural readout mechanisms that were not revealed by the DNA sequence. As such, this work combines knowledge from structural biology and genomics, and suggests a new path toward understanding TF binding and genome function. PMID:25775564

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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...

  3. Detecting and correcting the binding-affinity bias in ChIP-seq data using inter-species information

    OpenAIRE

    Nettling, Martin; Treutler, Hendrik; Cerquides, Jesus; Grosse, Ivo

    2016-01-01

    Background Transcriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. ChIP-seq has become the major technology to uncover genomic regions containing those binding sites, but motifs predicted by traditional computational approaches using these data are distorted by a ubiquitous binding-affinity bias. Here, we present an approach for detecti...

  4. Thermodynamic Characterization of New Positive Allosteric Modulators Binding to the Glutamate Receptor A2 Ligand-Binding Domain

    DEFF Research Database (Denmark)

    Nørholm, Ann-Beth; Francotte, Pierre; Goffin, Eric; Botez, Iuliana; Danober, Laurence; Lestage, Pierre; Pirotte, Bernard; Kastrup, Jette Sandholm Jensen; Olsen, Lars; Oostenbrink, Chris

    2014-01-01

    5a (5-F) and 5b (6-F) are entropy driven. For 5d (8-F), both quantities were equal in size. Thermodynamic integration (TI) and one-step perturbation (OSP) were used to calculate the relative binding affinity of the modulators. The OSP calculations had a higher predictive power than those from TI......Positive allosteric modulation of the ionotropic glutamate receptor GluA2 presents a potential treatment of cognitive disorders, for example, Alzheimer's disease. In the present study, we describe the synthesis, pharmacology, and thermodynamic studies of a series of monofluoro-substituted 3......,4-dihydro-2H-1,2,4-benzothiadiazine 1,1-dioxides. Measurements of ligand binding by isothermal titration calorimetry (ITC) showed similar binding affinities for the modulator series at the GluA2 LBD but differences in the thermodynamic driving forces. Binding of 5c (7-F) and 6 (no-F) is enthalpy driven, and...

  5. 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 ...

  6. Energy-dependent fitness: A quantitative model for the evolution of yeast transcription factor binding sites

    OpenAIRE

    Mustonen, Ville; Kinney, Justin; Callan, Curtis G.; Lässig, Michael

    2008-01-01

    We present a genomewide cross-species analysis of regulation for broad-acting transcription factors in yeast. Our model for binding site evolution is founded on biophysics: the binding energy between transcription factor and site is a quantitative phenotype of regulatory function, and selection is given by a fitness landscape that depends on this phenotype. The model quantifies conservation, as well as loss and gain, of functional binding sites in a coherent way. Its predictions are supported...

  7. 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...

  8. 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

  9. 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.

  10. Knowledge-based annotation of small molecule binding sites in proteins

    Directory of Open Access Journals (Sweden)

    Panchenko Anna R

    2010-07-01

    Full Text Available Abstract Background The study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapidly increasing structural data, it is essential to improve the tools that enable large scale binding site prediction with greater emphasis on their biological validity. Results We have developed a new method for the annotation of protein-small molecule binding sites, using inference by homology, which allows us to extend annotation onto protein sequences without experimental data available. To ensure biological relevance of binding sites, our method clusters similar binding sites found in homologous protein structures based on their sequence and structure conservation. Binding sites which appear evolutionarily conserved among non-redundant sets of homologous proteins are given higher priority. After binding sites are clustered, position specific score matrices (PSSMs are constructed from the corresponding binding site alignments. Together with other measures, the PSSMs are subsequently used to rank binding sites to assess how well they match the query and to better gauge their biological relevance. The method also facilitates a succinct and informative representation of observed and inferred binding sites from homologs with known three-dimensional structures, thereby providing the means to analyze conservation and diversity of binding modes. Furthermore, the chemical properties of small molecules bound to the inferred binding sites can be used as a starting point in small molecule virtual screening. The method was validated by comparison to other binding site prediction methods and to a collection of manually curated binding site annotations. We show that our method achieves a sensitivity of 72% at predicting biologically relevant binding sites and can accurately discriminate those sites that bind biological small molecules from non-biological ones. Conclusions

  11. 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。

  12. 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.

  13. [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

  14. 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.

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

    International Nuclear Information System (INIS)

    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 (R2=0.8521, RMS=0.2678) indicated satisfactory stability and predictive ability while the RBFNN predictive ability is somewhat superior (R2=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.

  16. 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.

  17. 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

  18. 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.

  19. Fast prediction of RNA-RNA interaction

    Directory of Open Access Journals (Sweden)

    Backofen Rolf

    2010-01-01

    Full Text Available Abstract Background Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s. There are a number of algorithms in the literature which can predict a variety of such interactions - unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site. Methods In this paper we present a novel algorithm to accurately predict the minimum free energy structure of RNA-RNA interaction under the most general type of interactions studied in the literature. Moreover, we introduce a fast heuristic method to predict the specific (multiple binding sites of two interacting RNAs. Results We verify the performance of our algorithms for joint structure and binding site prediction on a set of known interacting RNA pairs. Experimental results show our algorithms are highly accurate and outperform all competitive approaches.

  20. Windows Presentation Foundation & Data Binding

    OpenAIRE

    JANDA, Vilém

    2010-01-01

    The aim of this work is a course in the form of e-learning study materials for the interpretation of technology Data Binding in Windows Presentation Foundation (WPF). In the first, mostly theoretical part will be done a description and interpretation of the elements of technology, focusing on WPF Data Binding. In the second part, is available methodology and training course with their own interpretive audio-visual files for self-study. The lectures are supplemented by solved examples, and exa...

  1. Predictions of nuclear masses in different models

    International Nuclear Information System (INIS)

    The modern version of the liquid-drop model is compared to the macroscopic Thomas-Fermi (TF) energy and the macroscopic part of the binding energy evaluated within the Hartree-Fock-Bogoliubov theory with the Gogny force and the relativistic mean field theory. The limits of nuclear stability predicted by these models are discussed. (author)

  2. 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.

  3. 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

  4. 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.

  5. A Unified Model of the GABA(A) Receptor Comprising Agonist and Benzodiazepine Binding Sites

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning; Bergmann, Rikke; Sørensen, Pernille Louise; Sander, Tommy; Balle, Thomas

    2013-01-01

    -gated chloride channel (GluCl) from C. elegans and includes additional structural information from the prokaryotic ligand-gated ion channel ELIC in a few regions. Available mutational data of the binding sites are well explained by the model and the proposed ligand binding poses. We suggest a GABA binding mode...... similar to the binding mode of glutamate in the GluCl X-ray structure. Key interactions are predicted with residues a1R66, b2T202, a1T129, b2E155, b2Y205 and the backbone of b2S156. Muscimol is predicted to bind similarly, however, with minor differences rationalized with quantum mechanical energy...

  6. The propagation of binding interactions to remote sites in proteins: analysis of the binding of the monoclonal antibody D1.3 to lysozyme.

    Science.gov (United States)

    Freire, E

    1999-08-31

    The interaction of a ligand with a protein occurs at a local site (the binding site) and involves only a few residues; however, the effects of that interaction are often propagated to remote locations. The chain of events initiated by binding provides the basis for fundamental biological phenomena such as allosterism, signal transduction, and structural-stability modification. In this paper, a structure-based statistical thermodynamic approach is presented and used to predict the propagation of the stabilization effects triggered by the binding of the monoclonal antibody D1.3 to hen egg white lysozyme. Previously, Williams et al. [Williams, D. C., Benjamin, D. C., Poljak, R. J. & Rule, G. S. (1996) J. Mol. Biol. 257, 866-876] showed that the binding of this antibody affects the stability of hen egg white lysozyme and that the binding effects propagate to a selected number of residues at remote locations from the binding epitope. In this paper, we show that this phenomenon can be predicted from structure. The formalism presented here permits the identification of the structural path followed by cooperative interactions that originate at the binding site. It is shown that an important condition for the propagation of binding effects to distal regions is the presence of a significant fraction of residues with low structural stability in the uncomplexed binding site. A survey of protein structures indicates that many binding sites have a dual character and are defined by regions of high and low structural stabilities. The low-stability regions might be involved in the transmission of binding information to other regions in the protein. PMID:10468572

  7. Free-energy-based methods for binding profile determination in a congeneric series of CDK2 inhibitors.

    Science.gov (United States)

    Fidelak, Jérémy; Juraszek, Jarek; Branduardi, Davide; Bianciotto, Marc; Gervasio, Francesco Luigi

    2010-07-29

    Free-energy pathway methods show great promise in computing the mode of action and the free energy profile associated with the binding of small molecules with proteins, but are generally very computationally demanding. Here we apply a novel approach based on metadynamics and path collective variables. We show that this combination is able to find an optimal reaction coordinate and the free energy profile of binding with explicit solvent and full flexibility, while minimizing human intervention and computational costs. We apply it to predict the binding affinity of a congeneric series of 5 CDK2 inhibitors. The predicted binding free energy profiles are in accordance with experiment. PMID:20593892

  8. 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.

  9. 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.

  10. Xylanase inhibitors bind to nonstarch polysaccharides.

    Science.gov (United States)

    Fierens, Ellen; Gebruers, Kurt; Courtin, Christophe M; Delcour, Jan A

    2008-01-23

    This study is an in-depth investigation of the interaction between polysaccharides and the proteinaceous xylanase inhibitors, Triticum aestivum xylanase inhibitor (TAXI), xylanase inhibitor protein (XIP), and thaumatin-like xylanase inhibitor (TLXI). The binding affinities of all three known types of xylanase inhibitors from wheat are studied by measuring the residual xylanase inhibition activity after incubation of the inhibitors in the presence of different polysaccharides, such as beta-glucans and (arabino)xylans. The binding affinities of all three xylanase inhibitors for (arabino)xylans increased with a decreasing arabinose/xylose ratio (A/X ratio). This phenomenon was observed both with water-extractable and water-unextractable (arabino)xylans. The inhibitors also interacted with different soluble and insoluble beta-glucans. None of the inhibitors tested had the ability to hydrolyze the polysaccharides investigated. The present findings contribute to the unraveling of the function of xylanase inhibitors in nature and to the prediction of the effect of added xylanases in cereal-based biotechnological processes, such as bread making and gluten-starch separation. PMID:18092758

  11. 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.

  12. Preliminary study of the metal binding site of an anti-DTPA-indium antibody by equilibrium binding immunoassays and immobilized metal ion affinity chromatography.

    Science.gov (United States)

    Boden, V; Colin, C; Barbet, J; Le Doussal, J M; Vijayalakshmi, M

    1995-01-01

    Creating metal coordination sites by modifying an existing enzyme or by eliciting antibodies against metal chelate haptens is of great interest in biotechnology to create enzyme catalysts with novel specificities. Here, we investigate the metal binding potential of a monoclonal antibody raised against a DTPA-In(III) hapten (mAb 734). We study its relative binding efficiency to metals of biological relevance by equilibrium binding immunoassays and immobilized metal ion affinity chromatography, two approaches which can give complementary information regarding composition and/or structure of the metal binding site(s). Fe(III), Fe(II), Cu(II), Mg(II), Ca(II), and Zn(II) binding was compared to In(III). All of them were shown to displace indium, but their affinity for mAb 734 decreased by 100-fold compared to indium. Competitive metal binding immunoassays between Zn(II) and In(III) revealed an unusual behavior by Zn(II) which remains to be explained. Moreover, IMAC allowed us to predict the metal binding amino acids involved in the antibody paratope. The antibody metal binding site was shown to contain at least two histidine residues in a cluster, and the presence of aspartic and glutamic acid as well as cysteine residues could not be excluded. Thus, simple competition studies allows us to obtain some partial information on the metal binding structural features of this anti-metal chelate antibody and to guide our screening of its catalytic potential. PMID:7578356

  13. A DNA-binding-site landscape and regulatory network analysis for NAC transcription factors in Arabidopsis thaliana

    DEFF Research Database (Denmark)

    Lindemose, Søren; Jensen, Michael Krogh; de Velde, Jan Van; O'Shea, Charlotte; Heyndrickx, Ken S.; Workman, Christopher; Vandepoele, Klaas; Skriver, Karen; De Masi, Federico

    2014-01-01

    regulatory networks of 12 NAC transcription factors. Our data offer specific single-base resolution fingerprints for most TFs studied and indicate that NAC DNA-binding specificities might be predicted from their DNA-binding domain's sequence. The developed methodology, including the application of...... the DNA-binding preferences of individual members. Here, we present a TF-target gene identification workflow based on the integration of novel protein binding microarray data with gene expression and multi-species promoter sequence conservation to identify the DNA-binding specificities and the gene...

  14. Fast Prediction of RNA-RNA Interaction

    Science.gov (United States)

    Salari, Raheleh; Backofen, Rolf; Sahinalp, S. Cenk

    Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions - unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site.

  15. Cationic carbosilane dendrimers and oligonucleotide binding: an energetic affair

    Science.gov (United States)

    Marson, D.; Laurini, E.; Posocco, P.; Fermeglia, M.; Pricl, S.

    2015-02-01

    Generation 2 cationic carbosilane dendrimers hold great promise as internalizing agents for gene therapy as they present low toxicity and retain and internalize the genetic material as an oligonucleotide or siRNA. In this work we carried out complete in silico structural and energetical characterization of the interactions of a set of G2 carbosilane dendrimers, showing different affinity towards two single strand oligonucleotide (ODN) sequences in vitro. Our simulations predict that these four dendrimers and the relevant ODN complexes are characterized by similar size and shape, and that the molecule-specific ODN binding ability can be rationalized only by considering a critical molecular design parameter: the normalized effective binding energy ΔGbind,eff/Neff, i.e. the performance of each active individual dendrimer branch directly involved in a binding interaction.Generation 2 cationic carbosilane dendrimers hold great promise as internalizing agents for gene therapy as they present low toxicity and retain and internalize the genetic material as an oligonucleotide or siRNA. In this work we carried out complete in silico structural and energetical characterization of the interactions of a set of G2 carbosilane dendrimers, showing different affinity towards two single strand oligonucleotide (ODN) sequences in vitro. Our simulations predict that these four dendrimers and the relevant ODN complexes are characterized by similar size and shape, and that the molecule-specific ODN binding ability can be rationalized only by considering a critical molecular design parameter: the normalized effective binding energy ΔGbind,eff/Neff, i.e. the performance of each active individual dendrimer branch directly involved in a binding interaction. Electronic supplementary information (ESI) available: Additional figures and tables. See DOI: 10.1039/c4nr04510f

  16. 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

  17. 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

  18. 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.

  19. A probabilistic approach to microRNA-target binding

    International Nuclear Information System (INIS)

    Highlights: → A new probabilistic model is introduced for microRNA-target binding. → The new model significantly outperforms RNAHybrid and miRTif. → 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.

  20. 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.

  1. 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.

  2. Ligand Binding Pathways of Clozapine and Haloperidol in the Dopamine D2 and D3 Receptors.

    Science.gov (United States)

    Thomas, Trayder; Fang, Yu; Yuriev, Elizabeth; Chalmers, David K

    2016-02-22

    The binding of a small molecule ligand to its protein target is most often characterized by binding affinity and is typically viewed as an on/off switch. The more complex reality is that binding involves the ligand passing through a series of intermediate states between the solution phase and the fully bound pose. We have performed a set of 29 unbiased molecular dynamics simulations to model the binding pathways of the dopamine receptor antagonists clozapine and haloperidol binding to the D2 and D3 dopamine receptors. Through these simulations we have captured the binding pathways of clozapine and haloperidol from the extracellular vestibule to the orthosteric binding site and thereby, we also predict the bound pose of each ligand. These are the first long time scale simulations of haloperidol or clozapine binding to dopamine receptors. From these simulations, we have identified several important stages in the binding pathway, including the involvement of Tyr7.35 in a "handover" mechanism that transfers the ligand between the extracellular vestibule and Asp3.32. We have also performed interaction and cluster analyses to determine differences in binding pathways between the D2 and D3 receptors and identified metastable states that may be of use in drug design. PMID:26690887

  3. 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

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

    DEFF Research Database (Denmark)

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

    2005-01-01

    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...

  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. On the influence of reward on action-effect binding

    Directory of Open Access Journals (Sweden)

    PaulSimonMuhle-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.

  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. 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...

  10. Cholesterol-binding viral proteins in virus entry and morphogenesis.

    Science.gov (United States)

    Schroeder, Cornelia

    2010-01-01

    Up to now less than a handful of viral cholesterol-binding proteins have been characterized, in HIV, influenza virus and Semliki Forest virus. These are proteins with roles in virus entry or morphogenesis. In the case of the HIV fusion protein gp41 cholesterol binding is attributed to a cholesterol recognition consensus (CRAC) motif in a flexible domain of the ectodomain preceding the trans-membrane segment. This specific CRAC sequence mediates gp41 binding to a cholesterol affinity column. Mutations in this motif arrest virus fusion at the hemifusion stage and modify the ability of the isolated CRAC peptide to induce segregation of cholesterol in artificial membranes.Influenza A virus M2 protein co-purifies with cholesterol. Its proton translocation activity, responsible for virus uncoating, is not cholesterol-dependent, and the transmembrane channel appears too short for integral raft insertion. Cholesterol binding may be mediated by CRAC motifs in the flexible post-TM domain, which harbours three determinants of binding to membrane rafts. Mutation of the CRAC motif of the WSN strain attenuates virulence for mice. Its affinity to the raft-non-raft interface is predicted to target M2 protein to the periphery of lipid raft microdomains, the sites of virus assembly. Its influence on the morphology of budding virus implicates M2 as factor in virus fission at the raft boundary. Moreover, M2 is an essential factor in sorting the segmented genome into virus particles, indicating that M2 also has a role in priming the outgrowth of virus buds.SFV E1 protein is the first viral type-II fusion protein demonstrated to directly bind cholesterol when the fusion peptide loop locks into the target membrane. Cholesterol binding is modulated by another, proximal loop, which is also important during virus budding and as a host range determinant, as shown by mutational studies. PMID:20213541

  11. 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.

  12. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria

    Science.gov (United States)

    Wang, Harris H.

    2016-01-01

    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

  13. 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

  14. 1918 Influenza receptor binding domain variants bind and replicate in primary human airway cells regardless of receptor specificity.

    Science.gov (United States)

    Davis, A Sally; Chertow, Daniel S; Kindrachuk, Jason; Qi, Li; Schwartzman, Louis M; Suzich, Jon; Alsaaty, Sara; Logun, Carolea; Shelhamer, James H; Taubenberger, Jeffery K

    2016-06-01

    The 1918 influenza pandemic caused ~50 million deaths. Many questions remain regarding the origin, pathogenicity, and mechanisms of human adaptation of this virus. Avian-adapted influenza A viruses preferentially bind α2,3-linked sialic acids (Sia) while human-adapted viruses preferentially bind α2,6-linked Sia. A change in Sia preference from α2,3 to α2,6 is thought to be a requirement for human adaptation of avian influenza viruses. Autopsy data from 1918 cases, however, suggest that factors other than Sia preference played a role in viral binding and entry to human airway cells. Here, we evaluated binding and entry of five 1918 influenza receptor binding domain variants in a primary human airway cell model along with control avian and human influenza viruses. We observed that all five variants bound and entered cells efficiently and that Sia preference did not predict entry of influenza A virus to primary human airway cells evaluated in this model. PMID:27062579

  15. 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

  16. 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.

  17. 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, ...

  18. Positive Emotion Facilitates Audiovisual Binding.

    Science.gov (United States)

    Kitamura, Miho S; Watanabe, Katsumi; Kitagawa, Norimichi

    2015-01-01

    It has been shown that positive emotions can facilitate integrative and associative information processing in cognitive functions. The present study examined whether emotions in observers can also enhance perceptual integrative processes. We tested 125 participants in total for revealing the effects of emotional states and traits in observers on the multisensory binding between auditory and visual signals. Participants in Experiment 1 observed two identical visual disks moving toward each other, coinciding, and moving away, presented with a brief sound. We found that for participants with lower depressive tendency, induced happy moods increased the width of the temporal binding window of the sound-induced bounce percept in the stream/bounce display, while no effect was found for the participants with higher depressive tendency. In contrast, no effect of mood was observed for a simple audiovisual simultaneity discrimination task in Experiment 2. These results provide the first empirical evidence of a dependency of multisensory binding upon emotional states and traits, revealing that positive emotions can facilitate the multisensory binding processes at a perceptual level. PMID:26834585

  19. Radioligand Binding at Muscarinic Receptors

    Czech Academy of Sciences Publication Activity Database

    El-Fakahany, E. E.; Jakubík, Jan

    New York: Springer, 2016 - (Mysliveček, J.; Jakubík, J.), s. 37-68. (Neuromethods. 107). ISBN 978-1-4939-2857-6 R&D Projects: GA ČR(CZ) GBP304/12/G069 Institutional support: RVO:67985823 Keywords : muscarinic acetylcholine receptors * radioligand binding Subject RIV: ED - Physiology

  20. 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...

  1. 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.

  2. 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...

  3. 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

  4. In silico docking of forchlorfenuron (FCF to septins suggests that FCF interferes with GTP binding.

    Directory of Open Access Journals (Sweden)

    Dimitrios Angelis

    Full Text Available Septins are GTP-binding proteins that form cytoskeleton-like filaments, which are essential for many functions in eukaryotic organisms. Small molecule compounds that disrupt septin filament assembly are valuable tools for dissecting septin functions with high temporal control. To date, forchlorfenuron (FCF is the only compound known to affect septin assembly and functions. FCF dampens the dynamics of septin assembly inducing the formation of enlarged stable polymers, but the underlying mechanism of action is unknown. To investigate how FCF binds and affects septins, we performed in silico simulations of FCF docking to all available crystal structures of septins. Docking of FCF with SEPT2 and SEPT3 indicated that FCF interacts preferentially with the nucleotide-binding pockets of septins. Strikingly, FCF is predicted to form hydrogen bonds with residues involved in GDP-binding, mimicking nucleotide binding. FCF docking with the structure of SEPT2-GppNHp, a nonhydrolyzable GTP analog, and SEPT7 showed that FCF may assume two alternative non-overlapping conformations deeply into and on the outer side of the nucleotide-binding pocket. Surprisingly, FCF was predicted to interact with the P-loop Walker A motif GxxxxGKS/T, which binds the phosphates of GTP, and the GTP specificity motif AKAD, which interacts with the guanine base of GTP, and highly conserved amino acids including a threonine, which is critical for GTP hydrolysis. Thus, in silico FCF exhibits a conserved mechanism of binding, interacting with septin signature motifs and residues involved in GTP binding and hydrolysis. Taken together, our results suggest that FCF stabilizes septins by locking them into a conformation that mimics a nucleotide-bound state, preventing further GTP binding and hydrolysis. Overall, this study provides the first insight into how FCF may bind and stabilize septins, and offers a blueprint for the rational design of FCF derivatives that could target septins with

  5. 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...

  6. 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...

  7. 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 ...

  8. 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

  9. Probing protein phosphatase substrate binding

    DEFF Research Database (Denmark)

    Højlys-Larsen, Kim B.; Sørensen, Kasper Kildegaard; Jensen, Knud Jørgen; Gammeltoft, Steen

    2012-01-01

    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...... 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......, without the need for phosphopeptide mimics or phosphatase inhibitors. As no proven ILKAP substrates were available, we selected phosphopeptide substrates among known PP2Cδ substrates including the protein kinases: p38, ATM, Chk1, Chk2 and RSK2 and synthesized directly on PEGA solid supports through a BAL...

  10. Optical binding of unlike particles

    Czech Academy of Sciences Publication Activity Database

    Karásek, Vítězslav; Zemánek, Pavel

    Bellingham : SPIE, 2012, 86970T: 1-6. ISBN 978-0-8194-9481-8. [CPS 2012. Czech-Polish-Slovak Optical Conference on Wave and Quantum Aspects of Contemporary Optics /18./. Ostravice (CZ), 03.09.2012-07.09.2012] R&D Projects: GA ČR GPP205/12/P868 Institutional support: RVO:68081731 Keywords : Optical binding * Optical tweezers * self-arrangement * colloids Subject RIV: BH - Optics, Masers, Lasers

  11. 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)

  12. Positive Emotion Facilitates Audiovisual Binding

    OpenAIRE

    Kitamura, Miho S.; Watanabe, Katsumi; Kitagawa, Norimichi

    2016-01-01

    It has been shown that positive emotions can facilitate integrative and associative information processing in cognitive functions. The present study examined whether emotions in observers can also enhance perceptual integrative processes. We tested 125 participants in total for revealing the effects of emotional states and traits in observers on the multisensory binding between auditory and visual signals. Participants in Experiment 1 observed two identical visual disks moving toward each oth...

  13. 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.

  14. 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...

  15. 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...

  16. 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...

  17. 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

  18. 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

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

    DEFF Research Database (Denmark)

    Beuming, Thijs; Kniazeff, Julie; Bergmann, Marianne L; Shi, Lei; Gracia, Luis; Raniszewska, Klaudia; Newman, Amy Hauck; Javitch, Jonathan A; Weinstein, Harel; Gether, Ulrik; Løland, Claus Juul

    2008-01-01

    Cocaine is a widely abused substance with psychostimulant effects that are attributed to inhibition of the dopamine transporter (DAT). We present molecular models for DAT binding of cocaine and cocaine analogs constructed from the high-resolution structure of the bacterial transporter homolog Leu......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...

  20. 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. PMID:27046190

  1. 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.

  2. 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.

  3. 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.

  4. 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....

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. Computational Design of a DNA- and Fc-Binding Fusion Protein

    Directory of Open Access Journals (Sweden)

    Jonas Winkler

    2011-01-01

    Full Text Available Computational design of novel proteins with well-defined functions is an ongoing topic in computational biology. In this work, we generated and optimized a new synthetic fusion protein using an evolutionary approach. The optimization was guided by directed evolution based on hydrophobicity scores, molecular weight, and secondary structure predictions. Several methods were used to refine the models built from the resulting sequences. We have successfully combined two unrelated naturally occurring binding sites, the immunoglobin Fc-binding site of the Z domain and the DNA-binding motif of MyoD bHLH, into a novel stable protein.

  10. 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

  11. 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 ...

  12. 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

  13. Androgen receptor profiling predicts prostate cancer outcome

    OpenAIRE

    Stelloo, Suzan; Nevedomskaya, Ekaterina; van der Poel, Henk G.; de Jong, Jeroen; van Leenders, Geert JLH; Jenster, Guido; Wessels, Lodewyk FA; Bergman, Andries M; Zwart, Wilbert

    2015-01-01

    Prostate cancer is the second most prevalent malignancy in men. Biomarkers for outcome prediction are urgently needed, so that high-risk patients could be monitored more closely postoperatively. To identify prognostic markers and to determine causal players in prostate cancer progression, we assessed changes in chromatin state during tumor development and progression. Based on this, we assessed genomewide androgen receptor/chromatin binding and identified a distinct androgen receptor/chromati...

  14. Predicting new molecular targets for known drugs

    OpenAIRE

    Keiser, Michael J.; Setola, Vincent; Irwin, John J.; Laggner, Christian; Abbas, Atheir; Hufeisen, Sandra J.; Jensen, Niels H.; Kuijer, Michael B.; Matos, Roberto C.; Tran, Thuy B.; Whaley, Ryan; Glennon, Richard A.; Hert, Jérôme; THOMAS, KELAN L. H.; Edwards, Douglas D.

    2009-01-01

    Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 FDA-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested...

  15. The binding of lubricating films to ceramic and refractory materials

    International Nuclear Information System (INIS)

    In order to better understand the chemical bonding forces which control lubricating film stability and adhesion, the binding of lead and tin atoms on the ceramics alumina and silica was investigated by laser induced thermal evaporation combined with mass spectrometric detection of the evaporated species. The interaction between lead or tin and alumina and silica was studied as a function of coverage. The sticking probability for the interaction was measured and found to be temperature and coverage dependent. At low coverage the binding energy of lead to alumina and silica was determined as 237 and 246 kJ mol -1 respectively, while the binding energy of tin to alumina and silica is 313 and 331 kJ mol -1, respectively. A binding energy model based on thermochemical and crystallographic data is used to predict corresponding values which agree with the experimental values. In addition, the authors report temperature programmed desorption and/or decomposition (This patent describes) used to investigate the thermal and/or chemical stability of MoS2 films on molybdenum supports. The TPD spectra for S2 from Mos2 were analyzed, and activation energies found to be dependent on the film application technique

  16. 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.

  17. 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.

  18. 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.

  19. Binding of quasi two-dimensional biexcitons

    DEFF Research Database (Denmark)

    Birkedal, Dan; Singh, J; Vadim, Lyssenko; Hvam, Jørn Märcher

    Summary form only given. In this presentation we report on a determination of the biexciton binding energies in GaAs-AlGaAs quantum wells of different widths and the results of a theoretical calculation of the ratio of the biexciton binding energy to that of the exciton. We determine the binding ...

  20. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  1. 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...

  2. 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.

  3. Predicting the mechanism of phospholipidosis

    Directory of Open Access Journals (Sweden)

    Lowe Robert

    2012-01-01

    Full Text Available Abstract The mechanism of phospholipidosis is still not well understood. Numerous different mechanisms have been proposed, varying from direct inhibition of the breakdown of phospholipids to the binding of a drug compound to the phospholipid, preventing breakdown. We have used a probabilistic method, the Parzen-Rosenblatt Window approach, to build a model from the ChEMBL dataset which can predict from a compound's structure both its primary pharmaceutical target and other targets with which it forms off-target, usually weaker, interactions. Using a small dataset of 182 phospholipidosis-inducing and non-inducing compounds, we predict their off-target activity against targets which could relate to phospholipidosis as a side-effect of a drug. We link these targets to specific mechanisms of inducing this lysosomal build-up of phospholipids in cells. Thus, we show that the induction of phospholipidosis is likely to occur by separate mechanisms when triggered by different cationic amphiphilic drugs. We find that both inhibition of phospholipase activity and enhanced cholesterol biosynthesis are likely to be important mechanisms. Furthermore, we provide evidence suggesting four specific protein targets. Sphingomyelin phosphodiesterase, phospholipase A2 and lysosomal phospholipase A1 are shown to be likely targets for the induction of phospholipidosis by inhibition of phospholipase activity, while lanosterol synthase is predicted to be associated with phospholipidosis being induced by enhanced cholesterol biosynthesis. This analysis provides the impetus for further experimental tests of these hypotheses.

  4. Determining the binding mode and binding affinity constant of tyrosine kinase inhibitor PD153035 to DNA using optical tweezers

    International Nuclear Information System (INIS)

    Research highlights: → PD153035 is a DNA intercalator and intercalation occurs only under very low salt concentration. → The minimum distance between adjacent bound PD153035 ∼ 11 bp. → Binding affinity constant for PD153035 is 1.18(±0.09) x 104 (1/M). → The change of binding free energy of PD153035-DNA interaction is -5.49 kcal mol-1 at 23 ± 0.5 oC. -- Abstract: Accurately predicting binding affinity constant (KA) is highly required to determine the binding energetics of the driving forces in drug-DNA interactions. Recently, PD153035, brominated anilinoquinazoline, has been reported to be not only a highly selective inhibitor of epidermal growth factor receptor but also a DNA intercalator. Here, we use a dual-trap optical tweezers to determining KA for PD153035, where KA is determined from the changes in B-form contour length (L) of PD153035-DNA complex. Here, L is fitted using a modified wormlike chain model. We found that a noticeable increment in L in 1 mM sodium cacodylate was exhibited. Furthermore, our results showed that KA = 1.18(±0.09) x 104 (1/M) at 23 ± 0.5 oC and the minimum distance between adjacent bound PD153035 ∼ 11 bp. We anticipate that by using this approach we can determine the complete thermodynamic profiles due to the presence of DNA intercalators.

  5. Downstream prediction using a nonlinear prediction method

    Science.gov (United States)

    Adenan, N. H.; Noorani, M. S. M.

    2013-11-01

    The estimation of river flow is significantly related to the impact of urban hydrology, as this could provide information to solve important problems, such as flooding downstream. The nonlinear prediction method has been employed for analysis of four years of daily river flow data for the Langat River at Kajang, Malaysia, which is located in a downstream area. The nonlinear prediction method involves two steps; namely, the reconstruction of phase space and prediction. The reconstruction of phase space involves reconstruction from a single variable to the m-dimensional phase space in which the dimension m is based on optimal values from two methods: the correlation dimension method (Model I) and false nearest neighbour(s) (Model II). The selection of an appropriate method for selecting a combination of preliminary parameters, such as m, is important to provide an accurate prediction. From our investigation, we gather that via manipulation of the appropriate parameters for the reconstruction of the phase space, Model II provides better prediction results. In particular, we have used Model II together with the local linear prediction method to achieve the prediction results for the downstream area with a high correlation coefficient. In summary, the results show that Langat River in Kajang is chaotic, and, therefore, predictable using the nonlinear prediction method. Thus, the analysis and prediction of river flow in this area can provide river flow information to the proper authorities for the construction of flood control, particularly for the downstream area.

  6. Glucocorticoid receptor transformation and DNA binding

    International Nuclear Information System (INIS)

    The overall goal is to probe the mechanism whereby glucocorticoid receptors are transformed from a non-DNA-binding form to their active DNA-binding form. The author has examined the effect of an endogenous inhibitor purified from rat liver cytosol on receptor binding to DNA. The inhibitor binds to transformed receptors in whole cytosol and prevent their binding to DNA. He also examined the role of sulfhydryl groups in determining the DNA binding activity of the transformed receptor and in determining the transformation process. Treatment of rat liver cytosol containing temperature-transformed, [3H]dexamethasone-bound receptors at 00C with the sulfhydryl modifying reagent methyl methanethiosulfonate inhibits the DNA-binding activity of the receptor, and DNA-binding activity is restored after addition of dithiothreitol. In addition, he has examined the relationship between receptor phosphorylation and DNA binding. Untransformed receptor complexes purified from cytosol prepared from mouse L cells grown in medium containing [32P]orthophosphate contain two components, a 100 k-Da and a 90-kDa subunit, both of which are phosphoproteins. On transformation, the receptor dissociates from the 90-kDa protein. Transformation of the complex under cell free conditions does not result in a dephosphorylation of the 100-kDa steroid-binding protein. Transformed receptor that has been bound to DNA and purified by monoclonal antibody is still in a phosphorylated form. These results suggest that dephosphorylation is not required for receptor binding to DNA

  7. 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...

  8. 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.

  9. 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.

  10. Insulin binding to individual rat skeletal muscles

    International Nuclear Information System (INIS)

    Studies of insulin binding to skeletal muscle, performed using sarcolemmal membrane preparations or whole muscle incubations of mixed muscle or typical red (soleus, psoas) or white [extensor digitorum longus (EDL), gastrocnemius] muscle, have suggested that red muscle binds more insulin than white muscle. We have evaluated this hypothesis using cryostat sections of unfixed tissue to measure insulin binding in a broad range of skeletal muscles; many were of similar fiber-type profiles. Insulin binding per square millimeter of skeletal muscle slice was measured by autoradiography and computer-assisted densitometry. We found a 4.5-fold range in specific insulin tracer binding, with heart and predominantly slow-twitch oxidative muscles (SO) at the high end and the predominantly fast-twitch glycolytic (FG) muscles at the low end of the range. This pattern reflects insulin sensitivity. Evaluation of displacement curves for insulin binding yielded linear Scatchard plots. The dissociation constants varied over a ninefold range (0.26-2.06 nM). Binding capacity varied from 12.2 to 82.7 fmol/mm2. Neither binding parameter was correlated with fiber type or insulin sensitivity; e.g., among three muscles of similar fiber-type profile, the EDL had high numbers of low-affinity binding sites, whereas the quadriceps had low numbers of high-affinity sites. In summary, considerable heterogeneity in insulin binding was found among hindlimb muscles of the rat, which can be attributed to heterogeneity in binding affinities and the numbers of binding sites. It can be concluded that a given fiber type is not uniquely associated with a set of insulin binding parameters that result in high or low binding

  11. 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 ...

  12. Consensus topography in the ATP binding site of the simian virus 40 and polyomavirus large tumor antigens

    International Nuclear Information System (INIS)

    The location and sequence composition of a consensus element of the nucleotide binding site in both simian virus 40 (SV40) and polyomavirus (PyV) large tumor antigens (T antigens) can be predicted with the assistance of a computer-based pattern-matching system, ARIADNE. The latter was used to optimally align elements of T antigen primary sequence and predicted secondary structure with a descriptor for a mononucleotide binding fold. Additional consensus elements of the nucleotide binding site in these two proteins were derived from comparisons of T antigen primary and predicted secondary structures with x-ray structures of the nucleotide binding sites in four otherwise unrelated proteins. Each of these elements was predicted to be encompassed within a 110-residue segment that is highly conserved between the two T antigens residues 418-528 in SV 40 T antigen and residues 565-675 in PyV. Results of biochemical and immunologic experiments on the nucleotide binding behavior of these proteins using [32P]-Amp-labeled SV40 T antigen, were found to be consistent with these predictions. Taken together, the latter have resulted in a topological model of the ATP binding site in these two oncogene products

  13. Structural Fingerprints of Transcription Factor Binding Site Regions

    Directory of Open Access Journals (Sweden)

    Peter Willett

    2009-03-01

    Full Text Available Fourier transforms are a powerful tool in the prediction of DNA sequence properties, such as the presence/absence of codons. We have previously compiled a database of the structural properties of all 32,896 unique DNA octamers. In this work we apply Fourier techniques to the analysis of the structural properties of human chromosomes 21 and 22 and also to three sets of transcription factor binding sites within these chromosomes. We find that, for a given structural property, the structural property power spectra of chromosomes 21 and 22 are strikingly similar. We find common peaks in their power spectra for both Sp1 and p53 transcription factor binding sites. We use the power spectra as a structural fingerprint and perform similarity searching in order to find transcription factor binding site regions. This approach provides a new strategy for searching the genome data for information. Although it is difficult to understand the relationship between specific functional properties and the set of structural parameters in our database, our structural fingerprints nevertheless provide a useful tool for searching for function information in sequence data. The power spectrum fingerprints provide a simple, fast method for comparing a set of functional sequences, in this case transcription factor binding site regions, with the sequences of whole chromosomes. On its own, the power spectrum fingerprint does not find all transcription factor binding sites in a chromosome, but the results presented here show that in combination with other approaches, this technique will improve the chances of identifying functional sequences hidden in genomic data.

  14. 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.

  15. 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.

  16. Learning predictive clustering rules

    OpenAIRE

    Ženko, Bernard; Džeroski, Sašo; Struyf, Jan

    2005-01-01

    The two most commonly addressed data mining tasks are predictive modelling and clustering. Here we address the task of predictive clustering, which contains elements of both and generalizes them to some extent. We propose a novel approach to predictive clustering called predictive clustering rules, present an initial implementation and its preliminary experimental evaluation.

  17. 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....

  18. 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.

  19. 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

  20. 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)

  1. 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...

  2. 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...

  3. Predictability of social interactions

    OpenAIRE

    Xu, Kevin S.

    2013-01-01

    The ability to predict social interactions between people has profound applications including targeted marketing and prediction of information diffusion and disease propagation. Previous work has shown that the location of an individual at any given time is highly predictable. This study examines the predictability of social interactions between people to determine whether interaction patterns are similarly predictable. I find that the locations and times of interactions for an individual are...

  4. Effects of QED and Beyond from the Atomic Binding Energy

    International Nuclear Information System (INIS)

    Atomic binding energies are calculated at utmost precision. A report on the current status of Lamb-shift predictions for hydrogenlike ions, including all quantum electrodynamical corrections to first and second order in the fine structure constant α is presented. All relevant nuclear effects are taken into account. High-precision calculations for the Lamb shift in hydrogen are presented. The hyperfine structure splitting and the g factor of a bound electron in the strong electromagnetic field of a heavy nucleus is considered. Special emphasis is also put on parity violation effects in atomic systems. For all systems possible investigations beyond precision tests of quantum electrodynamics are considered

  5. 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

  6. 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.

  7. 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.

  8. GABA binding to an insect GABA receptor: a molecular dynamics and mutagenesis study.

    Science.gov (United States)

    Ashby, Jamie A; McGonigle, Ian V; Price, Kerry L; Cohen, Netta; Comitani, Federico; Dougherty, Dennis A; Molteni, Carla; Lummis, Sarah C R

    2012-11-21

    RDL receptors are GABA-activated inhibitory Cys-loop receptors found throughout the insect CNS. They are a key target for insecticides. Here, we characterize the GABA binding site in RDL receptors using computational and electrophysiological techniques. A homology model of the extracellular domain of RDL was generated and GABA docked into the binding site. Molecular dynamics simulations predicted critical GABA binding interactions with aromatic residues F206, Y254, and Y109 and hydrophilic residues E204, S176, R111, R166, S176, and T251. These residues were mutated, expressed in Xenopus oocytes, and their functions assessed using electrophysiology. The data support the binding mechanism provided by the simulations, which predict that GABA forms many interactions with binding site residues, the most significant of which are cation-π interactions with F206 and Y254, H-bonds with E204, S205, R111, S176, T251, and ionic interactions with R111 and E204. These findings clarify the roles of a range of residues in binding GABA in the RDL receptor, and also show that molecular dynamics simulations are a useful tool to identify specific interactions in Cys-loop receptors. PMID:23200041

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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....

  15. 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...

  16. firestar--advances in the prediction of functionally important residues.

    Science.gov (United States)

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php. PMID:21672959

  17. 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...

  18. 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...

  19. Exciton Binding Energy of Monolayer WS2

    OpenAIRE

    Bairen Zhu; Xi Chen; Xiaodong Cui

    2015-01-01

    The optical properties of monolayer transition metal dichalcogenides (TMDC) feature prominent excitonic natures. Here we report an experimental approach toward measuring the exciton binding energy of monolayer WS2 with linear differential transmission spectroscopy and two-photon photoluminescence excitation spectroscopy (TP-PLE). TP-PLE measurements show the exciton binding energy of 0.71eV around K valley in the Brillouin zone. The trion binding energy of 34meV, two-photon absorption cross s...

  20. 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.

  1. Binding of cryptococcal polysaccharide to Cryptococcus neoformans.

    OpenAIRE

    Kozel, T R; Hermerath, C A

    1984-01-01

    Radioiodinated cryptococcal polysaccharide was used to study binding of the soluble polysaccharide to encapsulated and non-encapsulated cryptoccoci. Binding of polysaccharide to non-encapsulated cryptococci occurred rapidly over a 30-min period and was largely complete after 2 h. Bound, labeled polysaccharide was slowly eluted from Cryptococcus neoformans after the addition of unlabeled polysaccharide, indicating reversibility of binding. Non-encapsulated cryptococci bound polysaccharide in t...

  2. 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.

  3. Numerical earthquake prediction

    International Nuclear Information System (INIS)

    Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earthquake prediction must also develop from empirical forecasting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out. (authors)

  4. 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

  5. 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.

  6. Computational exploration of a protein receptor binding space with student proposed peptide ligands.

    Science.gov (United States)

    King, Matthew D; Phillips, Paul; Turner, Matthew W; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M

    2016-01-01

    Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. PMID:26537635

  7. 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

  8. 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

  9. Novel benzimidazole inhibitors bind to a unique site in the kinesin spindle protein motor domain.

    Science.gov (United States)

    Sheth, Payal R; Shipps, Gerald W; Seghezzi, Wolfgang; Smith, Catherine K; Chuang, Cheng-Chi; Sanden, David; Basso, Andrea D; Vilenchik, Lev; Gray, Kimberly; Annis, D Allen; Nickbarg, Elliott; Ma, Yao; Lahue, Brian; Herbst, Ronald; Le, Hung V

    2010-09-28

    Affinity selection-mass spectrometry (AS-MS) screening of kinesin spindle protein (KSP) followed by enzyme inhibition studies and temperature-dependent circular dichroism (TdCD) characterization was utilized to identify a series of benzimidazole compounds. This series also binds in the presence of Ispinesib, a known anticancer KSP inhibitor in phase I/II clinical trials for breast cancer. TdCD and AS-MS analyses support simultaneous binding implying existence of a novel non-Ispinesib binding pocket within KSP. Additional TdCD analyses demonstrate direct binding of these compounds to Ispinesib-resistant mutants (D130V, A133D, and A133D + D130V double mutant), further strengthening the hypothesis that the compounds bind to a distinct binding pocket. Also importantly, binding to this pocket causes uncompetitive inhibition of KSP ATPase activity. The uncompetitive inhibition with respect to ATP is also confirmed by the requirement of nucleotide for binding of the compounds. After preliminary affinity optimization, the benzimidazole series exhibited distinctive antimitotic activity as evidenced by blockade of bipolar spindle formation and appearance of monoasters. Cancer cell growth inhibition was also demonstrated either as a single agent or in combination with Ispinesib. The combination was additive as predicted by the binding studies using TdCD and AS-MS analyses. The available data support the existence of a KSP inhibitory site hitherto unknown in the literature. The data also suggest that targeting this novel site could be a productive strategy for eluding Ispinesib-resistant tumors. Finally, AS-MS and TdCD techniques are general in scope and may enable screening other targets in the presence of known drugs, clinical candidates, or tool compounds that bind to the protein of interest in an effort to identify potency-enhancing small molecules that increase efficacy and impede resistance in combination therapy. PMID:20718440

  10. 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...

  11. 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.

  12. 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.

  13. Predictive modelling of gene expression from transcriptional regulatory elements.

    Science.gov (United States)

    Budden, David M; Hurley, Daniel G; Crampin, Edmund J

    2015-07-01

    Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. PMID:25231769

  14. 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

  15. 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

  16. 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

  17. Decreased Transcription Factor Binding Levels Nearby Primate Pseudogenes Suggest Regulatory Degeneration

    Science.gov (United States)

    Douglas, Gavin M.; Wilson, Michael D.; Moses, Alan M.

    2016-01-01

    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

  18. Peptide Binding to HLA Class I Molecules: Homogenous, High-Throughput Screening, and Affinity Assays

    DEFF Research Database (Denmark)

    Harndahl, Mikkel; Justesen, Sune Frederik Lamdahl; Lamberth, Kasper;

    2009-01-01

    The Human MHC Project aims at large-scale description of peptide-HLA binding to a wide range of HLA molecules covering all populations of the world and the accompanying generation of bioinformatics tools capable of predicting binding of any given peptide to any given HLA molecule. Here, the authors...... present a homogenous, proximity-based assay for detection of peptide binding to HLA class I molecules. It uses a conformation-dependent anti-HLA class I antibody, W6/32, as one tag and a biotinylated recombinant HLA class I molecule as the other tag, and a proximity-based signal is generated through the...... luminescent oxygen channeling immunoassay technology (abbreviated LOCI and commercialized as AlphaScreen (TM)). Compared with an enzyme-linked immunosorbent assay-based peptide-HLA class I binding assay, the LOCI assay yields virtually identical affinity measurements, although having a broader dynamic range...

  19. Serendipitous discovery and X-ray structure of a human phosphate binding apolipoprotein.

    Science.gov (United States)

    Morales, Renaud; Berna, Anne; Carpentier, Philippe; Contreras-Martel, Carlos; Renault, Frédérique; Nicodeme, Murielle; Chesne-Seck, Marie-Laure; Bernier, François; Dupuy, Jérôme; Schaeffer, Christine; Diemer, Hélène; Van-Dorsselaer, Alain; Fontecilla-Camps, Juan C; Masson, Patrick; Rochu, Daniel; Chabriere, Eric

    2006-03-01

    We report the serendipitous discovery of a human plasma phosphate binding protein (HPBP). This 38 kDa protein is copurified with the enzyme paraoxonase. Its X-ray structure is similar to the prokaryotic phosphate solute binding proteins (SBPs) associated with ATP binding cassette transmembrane transporters, though phosphate-SBPs have never been characterized or predicted from nucleic acid databases in eukaryotes. However, HPBP belongs to the family of ubiquitous eukaryotic proteins named DING, meaning that phosphate-SBPs are also widespread in eukaryotes. The systematic absence of complete genes for eukaryotic phosphate-SBP from databases is intriguing, but the astonishing 90% sequence conservation between genes belonging to evolutionary distant species suggests that the corresponding proteins play an important function. HPBP is the only known transporter capable of binding phosphate ions in human plasma and may become a new predictor of or a potential therapeutic agent for phosphate-related diseases such as atherosclerosis. PMID:16531243

  20. Self consistent single particle potential and nuclear matter binding energy

    International Nuclear Information System (INIS)

    We have obtained a self-consistent single-particle potential as a function of momentum for Fermi momenta kF= 1.4 fm. Self-consistent single particle potential is calculated from Brueckner g-matrix using Urbana v-14 interaction. Sixth order polynomial approximation is used as an input for the calculation of g-matrix. After achieving the self-consistent single particle potential we calculate the binding energy of infinite symmetric nuclear matter at different Fermi momenta, using soft-core Urbana v-14 interaction and hard-core Hamada Johnston interaction. Urbana v-14 interaction predicts overbinding of infinite nuclear matter, while HJ interaction predicts an underbound nuclear matter underbound. (author)

  1. 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...

  2. 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

  3. 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...

  4. 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...

  5. 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...

  6. Study on dopamine D2 binding capacity in vascular parkinsonism

    International Nuclear Information System (INIS)

    To investigate whether the striatal dopamine receptor function is involved in the development of vascular parkinsonism (VP), a positron emission tomography (PET) study was conducted on 9 patients with VP by using [11C] N-methylspiperone as the tracer. The rate of binding availability in the striatal dopamine D2 receptor (k3) was determined semiquantitatively, and the values were compared to the predicted normal values based on the results from 7 normal volunteers. Of 9 patients with VP, the normalized D2 receptor binding [%k3] was more than 90% in 5 patients, 89 to 87% in 3, and 75% in one. These values showed no evident correlation with the Hoehn and Yahr stage. The laterality of the striatal %k3 did not correspond to that of the parkinsonism. Thus, the striatal dopamine D2 receptor binding was not severely impaired and did not correlate with the neurological status in patients with VP. This may indicate that striatal dopamine D2 receptor function is not primarily associated with the development of the parkinsonism in VP. (author)

  7. 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

  8. 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

  9. 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.

  10. Divergence of Pumilio/fem-3 mRNA Binding Factor (PUF) Protein Specificity through Variations in an RNA-binding Pocket*

    Science.gov (United States)

    Qiu, Chen; Kershner, Aaron; Wang, Yeming; Holley, Cynthia P.; Wilinski, Daniel; Keles, Sunduz; Kimble, Judith; Wickens, Marvin; Hall, Traci M. Tanaka

    2012-01-01

    mRNA control networks depend on recognition of specific RNA sequences. Pumilio-fem-3 mRNA binding factor (PUF) RNA-binding proteins achieve that specificity through variations on a conserved scaffold. Saccharomyces cerevisiae Puf3p achieves specificity through an additional binding pocket for a cytosine base upstream of the core RNA recognition site. Here we demonstrate that this chemically simple adaptation is prevalent and contributes to the diversity of RNA specificities among PUF proteins. Bioinformatics analysis shows that mRNAs associated with Caenorhabditis elegans fem-3 mRNA binding factor (FBF)-2 in vivo contain an upstream cytosine required for biological regulation. Crystal structures of FBF-2 and C. elegans PUF-6 reveal binding pockets structurally similar to that of Puf3p, whereas sequence alignments predict a pocket in PUF-11. For Puf3p, FBF-2, PUF-6, and PUF-11, the upstream pockets and a cytosine are required for maximal binding to RNA, but the quantitative impact on binding affinity varies. Furthermore, the position of the upstream cytosine relative to the core PUF recognition site can differ, which in the case of FBF-2 originally masked the identification of this consensus sequence feature. Importantly, other PUF proteins lack the pocket and so do not discriminate upstream bases. A structure-based alignment reveals that these proteins lack key residues that would contact the cytosine, and in some instances, they also present amino acid side chains that interfere with binding. Loss of the pocket requires only substitution of one serine, as appears to have occurred during the evolution of certain fungal species. PMID:22205700

  11. Divergence of Pumilio/fem-3 mRNA binding factor (PUF) protein specificity through variations in an RNA-binding pocket.

    Science.gov (United States)

    Qiu, Chen; Kershner, Aaron; Wang, Yeming; Holley, Cynthia P; Wilinski, Daniel; Keles, Sunduz; Kimble, Judith; Wickens, Marvin; Hall, Traci M Tanaka

    2012-02-24

    mRNA control networks depend on recognition of specific RNA sequences. Pumilio-fem-3 mRNA binding factor (PUF) RNA-binding proteins achieve that specificity through variations on a conserved scaffold. Saccharomyces cerevisiae Puf3p achieves specificity through an additional binding pocket for a cytosine base upstream of the core RNA recognition site. Here we demonstrate that this chemically simple adaptation is prevalent and contributes to the diversity of RNA specificities among PUF proteins. Bioinformatics analysis shows that mRNAs associated with Caenorhabditis elegans fem-3 mRNA binding factor (FBF)-2 in vivo contain an upstream cytosine required for biological regulation. Crystal structures of FBF-2 and C. elegans PUF-6 reveal binding pockets structurally similar to that of Puf3p, whereas sequence alignments predict a pocket in PUF-11. For Puf3p, FBF-2, PUF-6, and PUF-11, the upstream pockets and a cytosine are required for maximal binding to RNA, but the quantitative impact on binding affinity varies. Furthermore, the position of the upstream cytosine relative to the core PUF recognition site can differ, which in the case of FBF-2 originally masked the identification of this consensus sequence feature. Importantly, other PUF proteins lack the pocket and so do not discriminate upstream bases. A structure-based alignment reveals that these proteins lack key residues that would contact the cytosine, and in some instances, they also present amino acid side chains that interfere with binding. Loss of the pocket requires only substitution of one serine, as appears to have occurred during the evolution of certain fungal species. PMID:22205700

  12. Optimal predictive model selection

    OpenAIRE

    Barbieri, Maria Maddalena; Berger, James O.

    2004-01-01

    Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal linear models, the optimal predictive model is often the median probability model, which is defined a...

  13. Predictive software design measures

    OpenAIRE

    Love, Randall James

    1994-01-01

    This research develops a set of predictive measures enabling software testers and designers to identify and target potential problem areas for additional and/or enhanced testing. Predictions are available as early in the design process as requirements allocation and as late as code walk-throughs. These predictions are based on characteristics of the design artifacts prior to coding. Prediction equations are formed at established points in the software development process...

  14. Docking of the Periplasmic FecB Binding Protein to the FecCD Transmembrane Proteins in the Ferric Citrate Transport System of Escherichia coli▿

    OpenAIRE

    Braun, Volkmar; Herrmann, Christina

    2007-01-01

    Citrate-mediated iron transport across the cytoplasmic membrane is catalyzed by an ABC transporter that consists of the periplasmic binding protein FecB, the transmembrane proteins FecC and FecD, and the ATPase FecE. Salt bridges between glutamate residues of the binding protein and arginine residues of the transmembrane proteins are predicted to mediate the positioning of the substrate-loaded binding protein on the transmembrane protein, based on the crystal structures of the ABC transporter...

  15. Sequence-based feature prediction and annotation of proteins

    DEFF Research Database (Denmark)

    Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea; Bernsel, Andreas; Tress, Michael L.; Bork, Peer; Von Heijne, Gunnar; Valencia, Alfonso; A Ouzounis, Christos; Casadio, Rita; Brunak, Søren

    2009-01-01

    A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....

  16. 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-...

  17. Molecularly Responsive Binding through Co-occupation of Binding Space: A Lock-Key Story.

    Science.gov (United States)

    Awino, Joseph K; Hu, Lan; Zhao, Yan

    2016-04-01

    When two guest molecules co-occupy a binding pocket of a water-soluble host, the first guest could be used as a signal molecule to turn on the binding of the second. This type of molecularly responsive binding strongly depends on the size of the two guests and the location of the signal molecule. PMID:27001464

  18. 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

  19. 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...

  20. 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.

  1. (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.

  2. [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

  3. NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure

    DEFF Research Database (Denmark)

    Nielsen, Morten; Justesen, Sune Frederik Lamdahl; Lund, Ole;

    2010-01-01

    BACKGROUND: Binding of peptides to Major Histocompatibility class II (MHC-II) molecules play a central role in governing responses of the adaptive immune system. MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from...... large efforts have therefore been placed in developing accurate computer methods capable of predicting this binding event. Prediction of peptide binding to MHC-II is complicated by the open binding cleft of the MHC-II molecule, allowing binding of peptides extending out of the binding groove. Moreover......-II binding prediction algorithm aiming at dealing with these challenges. The method is a pan-specific version of the earlier published allele-specific NN-align algorithm and does not require any pre-alignment of the input data. This allows the method to benefit also from information from alleles covered by...

  4. 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.

  5. Predicting Predictable about Natural Catastrophic Extremes

    Science.gov (United States)

    Kossobokov, Vladimir

    2015-04-01

    By definition, an extreme event is rare one in a series of kindred phenomena. Usually (e.g. in Geophysics), it implies investigating a small sample of case-histories with a help of delicate statistical methods and data of different quality, collected in various conditions. Many extreme events are clustered (far from independent) and follow fractal or some other "strange" distribution (far from uniform). Evidently, such an "unusual" situation complicates search and definition of reliable precursory behaviors to be used for forecast/prediction purposes. Making forecast/prediction claims reliable and quantitatively probabilistic in the frames of the most popular objectivists' viewpoint on probability requires a long series of "yes/no" forecast/prediction outcomes, which cannot be obtained without an extended rigorous test of the candidate method. The set of errors ("success/failure" scores and space-time measure of alarms) and other information obtained in such a control test supplies us with data necessary to judge the candidate's potential as a forecast/prediction tool and, eventually, to find its improvements. This is to be done first in comparison against random guessing, which results confidence (measured in terms of statistical significance). Note that an application of the forecast/prediction tools could be very different in cases of different natural hazards, costs and benefits that determine risks, and, therefore, requires determination of different optimal strategies minimizing reliable estimates of realistic levels of accepted losses. In their turn case specific costs and benefits may suggest a modification of the forecast/prediction tools for a more adequate "optimal" application. Fortunately, the situation is not hopeless due to the state-of-the-art understanding of the complexity and non-linear dynamics of the Earth as a Physical System and pattern recognition approaches applied to available geophysical evidences, specifically, when intending to predict

  6. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. Genome-wide conserved consensus transcription factor binding motifs are hyper-methylated

    Directory of Open Access Journals (Sweden)

    Down Thomas A

    2010-09-01

    Full Text Available Abstract Background DNA methylation can regulate gene expression by modulating the interaction between DNA and proteins or protein complexes. Conserved consensus motifs exist across the human genome ("predicted transcription factor binding sites": "predicted TFBS" but the large majority of these are proven by chromatin immunoprecipitation and high throughput sequencing (ChIP-seq not to be biological transcription factor binding sites ("empirical TFBS". We hypothesize that DNA methylation at conserved consensus motifs prevents promiscuous or disorderly transcription factor binding. Results Using genome-wide methylation maps of the human heart and sperm, we found that all conserved consensus motifs as well as the subset of those that reside outside CpG islands have an aggregate profile of hyper-methylation. In contrast, empirical TFBS with conserved consensus motifs have a profile of hypo-methylation. 40% of empirical TFBS with conserved consensus motifs resided in CpG islands whereas only 7% of all conserved consensus motifs were in CpG islands. Finally we further identified a minority subset of TF whose profiles are either hypo-methylated or neutral at their respective conserved consensus motifs implicating that these TF may be responsible for establishing or maintaining an un-methylated DNA state, or whose binding is not regulated by DNA methylation. Conclusions Our analysis supports the hypothesis that at least for a subset of TF, empirical binding to conserved consensus motifs genome-wide may be controlled by DNA methylation.

  12. Specificity of anion-binding in the substrate-pocket ofbacteriorhodopsin

    Energy Technology Data Exchange (ETDEWEB)

    Facciotti, Marc T.; Cheung, Vincent S.; Lunde, Christopher S.; Rouhani, Shahab; Baliga, Nitin S.; Glaeser, Robert M.

    2003-08-30

    The structure of the D85S mutant of bacteriorhodopsin with a nitrate anion bound in the Schiff-base binding site, and the structure of the anion-free protein have been obtained in the same crystal form. Together with the previously solved structures of this anion pump, in both the anion-free state and bromide-bound state, these new structures provide insight into how this mutant of bacteriorhodopsin is able to bind a variety of different anions in the same binding pocket. The structural analysis reveals that the main structural change that accommodates different anions is the repositioning of the polar side-chain of S85. On the basis of these x-ray crystal structures, the prediction is then made that the D85S/D212N double mutant might bind similar anions and do so over a broader pH range than does the single mutant. Experimental comparison of the dissociation constants, K{sub d}, for a variety of anions confirms this prediction and demonstrates, in addition, that the binding affinity is dramatically improved by the D212N substitution.

  13. Binding studies of a large antiviral polyamide to a natural HPV sequence.

    Science.gov (United States)

    He, Gaofei; Vasilieva, Elena; Harris, George Davis; Koeller, Kevin J; Bashkin, James K; Dupureur, Cynthia M

    2014-07-01

    PA1 is a large hairpin polyamide (dImPyPy-β-PyPyPy-γ-PyPy-β-PyPyPyPy-β-Ta; Py = pyrrole, Im = imidazole, β = beta alanine) that targets the sequence 5'-WWGWWWWWWW-3' (W = A or T) and is effective in eliminating HPV16 in cell culture (Edwards, T. G., Koeller, K. J., Slomczynska, U., Fok, K., Helmus, M., Bashkin, J. K., Fisher, C., Antiviral Res. 91 (2011) 177-186). Described here are its DNA binding properties toward a natural DNA, a 523 bp portion of HPV16 (2150-2672) containing three predicted perfect match sites. Strategies for obtaining binding data on large fragments using capillary electrophoresis are also described. Using an Fe EDTA conjugate of PA1, 19 affinity cleavage (AC) patterns were detected for this fragment. In many cases, there are multiple possible binding sequences (perfect, single and double mismatch sites) consistent with the AC data. Quantitative DNase I footprinting analysis indicates that perfect and most single mismatch sites bind PA1 with Kds between 0.7 and 4 nM, indicating excellent tolerance for the latter. Double mismatch sites exhibit Kds between 12 and 62 nM. A large fraction of the accessible sequence is susceptible to PA1 binding, much larger than predicted based on the literature of polyamide-DNA recognition rules. PMID:24582833

  14. 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....

  15. The High-Affinity Binding Site for Tricyclic Antidepressants Resides in the Outer Vestibule of the Serotonin TransporterⓈ

    OpenAIRE

    Sarker, Subhodeep; Weissensteiner, René; Steiner, Ilka; Sitte, Harald H; Ecker, Gerhard F.; Freissmuth, Michael; Sucic, Sonja

    2010-01-01

    The structure of the bacterial leucine transporter from Aquifex aeolicus (LeuTAa) has been used as a model for mammalian Na+/Cl−-dependent transporters, in particular the serotonin transporter (SERT). The crystal structure of LeuTAa liganded to tricyclic antidepressants predicts simultaneous binding of inhibitor and substrate. This is incompatible with the mutually competitive inhibition of substrates and inhibitors of SERT. We explored the binding modes of tricyclic antidepressants by homolo...

  16. Derivation of an amino acid similarity matrix for peptide:MHC binding and its application as a Bayesian prior

    Directory of Open Access Journals (Sweden)

    Sette Alessandro

    2009-11-01

    Full Text Available Abstract Background Experts in peptide:MHC binding studies are often able to estimate the impact of a single residue substitution based on a heuristic understanding of amino acid similarity in an experimental context. Our aim is to quantify this measure of similarity to improve peptide:MHC binding prediction methods. This should help compensate for holes and bias in the sequence space coverage of existing peptide binding datasets. Results Here, a novel amino acid similarity matrix (PMBEC is directly derived from the binding affinity data of combinatorial peptide mixtures. Like BLOSUM62, this matrix captures well-known physicochemical properties of amino acid residues. However, PMBEC differs markedly from existing matrices in cases where residue substitution involves a reversal of electrostatic charge. To demonstrate its usefulness, we have developed a new peptide:MHC class I binding prediction method, using the matrix as a Bayesian prior. We show that the new method can compensate for missing information on specific residues in the training data. We also carried out a large-scale benchmark, and its results indicate that prediction performance of the new method is comparable to that of the best neural network based approaches for peptide:MHC class I binding. Conclusion A novel amino acid similarity matrix has been derived for peptide:MHC binding interactions. One prominent feature of the matrix is that it disfavors substitution of residues with opposite charges. Given that the matrix was derived from experimentally determined peptide:MHC binding affinity measurements, this feature is likely shared by all peptide:protein interactions. In addition, we have demonstrated the usefulness of the matrix as a Bayesian prior in an improved scoring-matrix based peptide:MHC class I prediction method. A software implementation of the method is available at: http://www.mhc-pathway.net/smmpmbec.

  17. 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

  18. 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

  19. 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

  20. The high-affinity binding site for tricyclic antidepressants resides in the outer vestibule of the serotonin transporter.

    Science.gov (United States)

    Sarker, Subhodeep; Weissensteiner, René; Steiner, Ilka; Sitte, Harald H; Ecker, Gerhard F; Freissmuth, Michael; Sucic, Sonja

    2010-12-01

    The structure of the bacterial leucine transporter from Aquifex aeolicus (LeuT(Aa)) has been used as a model for mammalian Na(+)/Cl(-)-dependent transporters, in particular the serotonin transporter (SERT). The crystal structure of LeuT(Aa) liganded to tricyclic antidepressants predicts simultaneous binding of inhibitor and substrate. This is incompatible with the mutually competitive inhibition of substrates and inhibitors of SERT. We explored the binding modes of tricyclic antidepressants by homology modeling and docking studies. Two approaches were used subsequently to differentiate between three clusters of potential docking poses: 1) a diagnostic SERT(Y95F) mutation, which greatly reduced the affinity for [(3)H]imipramine but did not affect substrate binding; 2) competition binding experiments in the presence and absence of carbamazepine (i.e., a tricyclic imipramine analog with a short side chain that competes with [(3)H]imipramine binding to SERT). Binding of releasers (para-chloroamphetamine, methylene-dioxy-methamphetamine/ecstasy) and of carbamazepine were mutually exclusive, but Dixon plots generated in the presence of carbamazepine yielded intersecting lines for serotonin, MPP(+), paroxetine, and ibogaine. These observations are consistent with a model, in which 1) the tricyclic ring is docked into the outer vestibule and the dimethyl-aminopropyl side chain points to the substrate binding site; 2) binding of amphetamines creates a structural change in the inner and outer vestibule that precludes docking of the tricyclic ring; 3) simultaneous binding of ibogaine (which binds to the inward-facing conformation) and of carbamazepine is indicative of a second binding site in the inner vestibule, consistent with the pseudosymmetric fold of monoamine transporters. This may be the second low-affinity binding site for antidepressants. PMID:20829432

  1. Calcium Binding to Amino Acids and Small Glycine Peptides in Aqueous Solution: Toward Peptide Design for Better Calcium Bioavailability.

    Science.gov (United States)

    Tang, Ning; Skibsted, Leif H

    2016-06-01

    Deprotonation of amino acids as occurs during transfer from stomach to intestines during food digestion was found by comparison of complex formation constants as determined electrochemically for increasing pH to increase calcium binding (i) by a factor of around 6 for the neutral amino acids, (ii) by a factor of around 4 for anions of the acidic amino acids aspartic and glutamic acid, and (iii) by a factor of around 5.5 for basic amino acids. Optimized structures of the 1:1 complexes and ΔHbinding for calcium binding as calculated by density functional theory (DFT) confirmed in all complexes a stronger calcium binding and shorter calcium-oxygen bond length in the deprotonated form. In addition, the stronger calcium binding was also accompanied by a binding site shift from carboxylate binding to chelation by α-amino group and carboxylate oxygen for leucine, aspartate, glutamate, alanine, and asparagine. For binary amino acid mixtures, the calcium-binding constant was close to the predicted geometric mean of the individual amino acid binding constants indicating separate binding of calcium to two amino acids when present together in solution. At high pH, corresponding to conditions for calcium absorption, the binding affinity increased in the order Lys < Arg < Cys < Gln < Gly ∼ Ala < Asn < His < Leu < Glu< Asp. In a series of glycine peptides, calcium-binding affinity was found to increase in the order Gly-Leu ∼ Gly-Gly < Ala-Gly < Gly-His ∼ Gly-Lys-Gly < Glu-Cys-Gly < Gly-Glu, an ordering confirmed by DFT calculations for the dipeptides and which also accounted for large synergistic effects in calcium binding for up to 6 kJ/mol when compared to the corresponding amino acid mixtures. PMID:27159329

  2. Glycolipid binding preferences of Shiga toxin variants.

    Directory of Open Access Journals (Sweden)

    Sayali S Karve

    Full Text Available The major virulence factor of Shiga toxin producing E. coli, is Shiga toxin (Stx, an AB5 toxin that consists of a ribosomal RNA-cleaving A-subunit surrounded by a pentamer of receptor-binding B subunits. The two major isoforms, Stx1 and Stx2, and Stx2 variants (Stx2a-h significantly differ in toxicity. The exact reason for this toxicity difference is unknown, however different receptor binding preferences are speculated to play a role. Previous studies used enzyme linked immunosorbent assay (ELISA to study binding of Stx1 and Stx2a toxoids to glycolipid receptors. Here, we studied binding of holotoxin and B-subunits of Stx1, Stx2a, Stx2b, Stx2c and Stx2d to glycolipid receptors globotriaosylceramide (Gb3 and globotetraosylceramide (Gb4 in the presence of cell membrane components such as phosphatidylcholine (PC, cholesterol (Ch and other neutral glycolipids. In the absence of PC and Ch, holotoxins of Stx2 variants bound to mixtures of Gb3 with other glycolipids but not to Gb3 or Gb4 alone. Binding of all Stx holotoxins significantly increased in the presence of PC and Ch. Previously, Stx2a has been shown to form a less stable B-pentamer compared to Stx1. However, its effect on glycolipid receptor binding is unknown. In this study, we showed that even in the absence of the A-subunit, the B-subunits of both Stx1 and Stx2a were able to bind to the glycolipids and the more stable B-pentamer formed by Stx1 bound better than the less stable pentamer of Stx2a. B-subunit mutant of Stx1 L41Q, which shows similar stability as Stx2a B-subunits, lacked glycolipid binding, suggesting that pentamerization is more critical for binding of Stx1 than Stx2a.

  3. Prediction of proteasome cleavage motifs by neural networks

    DEFF Research Database (Denmark)

    Kesimir, C.; Nussbaum, A.K.; Schild, H.;

    2002-01-01

    We present a predictive method that can simulate an essential step in the antigen presentation in higher vertebrates, namely the step involving the proteasomal degradation of polypeptides into fragments which have the potential to bind to MHC Class I molecules. Proteasomal cleavage prediction...... the prediction of MHC Class I ligand boundaries more accurate: 65% of the cleavage sites and 85% of the non-cleavage sites are correctly determined. Moreover, we show that the neural networks trained on the constitutive proteasome data learns a specificity that differs from that of the networks...

  4. Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

    KAUST Repository

    Guturu, H.

    2013-11-11

    Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and \\'through-DNA\\' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

  5. Predicting Resistance Mutations Using Protein Design Algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Frey, K.; Georgiev, I; Donald, B; Anderson, A

    2010-01-01

    Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.

  6. Binding of uranyl by humic acid

    International Nuclear Information System (INIS)

    The binding of tracer level UO2+2 to a soil humic acid was measured by a solvent extraction technique. The binding is interpreted as involving only the carboxylate groups of the humate and both 1:1 and 1:2 UO2+2:CO2-binding is observed. Estimates based on these values indicate that uranyl complexing by humic and/or fulvic materials is not significant in sea water but may play a role in fresh water systems. Retention of uranyl from ground water by soil humics would be strong. (author)

  7. Measuring Binding Affinity of Protein-Ligand Interaction Using Spectrophotometry: Binding of Neutral Red to Riboflavin-Binding Protein

    Science.gov (United States)

    Chenprakhon, Pirom; Sucharitakul, Jeerus; Panijpan, Bhinyo; Chaiyen, Pimchai

    2010-01-01

    The dissociation constant, K[subscript d], of the binding of riboflavin-binding protein (RP) with neutral red (NR) can be determined by titrating RP to a fixed concentration of NR. Upon adding RP to the NR solution, the maximum absorption peak of NR shifts to 545 nm from 450 nm for the free NR. The change of the absorption can be used to determine…

  8. Exploring the binding mechanisms of MIF to CXCR2 using theoretical approaches.

    Science.gov (United States)

    Xu, Lei; Li, Youyong; Li, Dan; Xu, Peng; Tian, Sheng; Sun, Huiyong; Liu, Hui; Hou, Tingjun

    2015-02-01

    Macrophage migration inhibitory factor (MIF) is a multi-functional protein that acts as a cytokine and as an enzyme. Recently, MIF was identified as a non-canonical ligand of G protein-coupled chemokine receptor CXCR2 with low nanomolar affinity in leukocyte arrest and chemotaxis, but the precise knowledge of the molecular determinants of the MIF-CXCR2 interface has remained unknown. Therefore, we employed homology modeling, protein-protein docking, molecular dynamics (MD) simulations, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding free energy calculations and MM/GBSA binding free energy decomposition to obtain insights into the molecular recognition of MIF with CXCR2. The predicted binding pattern of MIF-CXCR2 is in good agreement with the experimental data and sheds light on the functional role of important MIF-CXCR2 interface residues in association with binding and signaling. According to our predictions, the R11A/D44A double mutations of MIF exhibit a pronounced defect in the binding affinity of MIF to CXCR2, resulting in large conformational changes. The potential two-site binding model for the MIF-CXCR2 recognition was proposed: initialized primarily by the non-polar interactions including the van der Waals and hydrophobic interactions, the N-terminal region of CXCR2 contacts the N-like loop and β-sheet of MIF (site 1), and then the ECL2 and ECL3 regions of CXCR2 form strong interactions with the pseudo-(E)LR motif and C-terminus of MIF, which induces the molecular thermodynamic motion of TMs for signal transduction (site 2). This study will extend our understanding to the binding mechanisms of MIF to CXCR2 and provide useful information for the rational design of potent inhibitors selectively targeting the MIF-CXCR2 interactions. PMID:25526079

  9. Identification and design of p53-derived HLA-A2-binding peptides with increased CTL immunogenicity

    DEFF Research Database (Denmark)

    Petersen, T R; Buus, S; Brunak, S;

    2001-01-01

    peptide binding to HLA-A2 molecules, we identified three p53 protein-derived nonamer peptides with intermediate binding owing to suboptimal amino acids in the P2 anchor position. These peptides were synthesized along with the corresponding analogs, where the natural P2 residue had been replaced with the...... HLA-A2 transgenic mouse fibrosarcoma cells transfected with human p53 DNA. The data suggest that modified self-peptides derived from overexpressed tumour-associated proteins can be used in vaccine development against cancer, and that quantitative predictions of HLA binding is of value in the rational...

  10. Escherichia coli Single-Stranded DNA-Binding Protein: NanoESI-MS Studies of Salt-Modulated Subunit Exchange and DNA Binding Transactions

    Science.gov (United States)

    Mason, Claire E.; Jergic, Slobodan; Lo, Allen T. Y.; Wang, Yao; Dixon, Nicholas E.; Beck, Jennifer L.

    2013-02-01

    Single-stranded DNA-binding proteins (SSBs) are ubiquitous oligomeric proteins that bind with very high affinity to single-stranded DNA and have a variety of essential roles in DNA metabolism. Nanoelectrospray ionization mass spectrometry (nanoESI-MS) was used to monitor subunit exchange in full-length and truncated forms of the homotetrameric SSB from Escherichia coli. Subunit exchange in the native protein was found to occur slowly over a period of hours, but was significantly more rapid in a truncated variant of SSB from which the eight C-terminal residues were deleted. This effect is proposed to result from C-terminus mediated stabilization of the SSB tetramer, in which the C-termini interact with the DNA-binding cores of adjacent subunits. NanoESI-MS was also used to examine DNA binding to the SSB tetramer. Binding of single-stranded oligonucleotides [one molecule of (dT)70, one molecule of (dT)35, or two molecules of (dT)35] was found to prevent SSB subunit exchange. Transfer of SSB tetramers between discrete oligonucleotides was also observed and is consistent with predictions from solution-phase studies, suggesting that SSB-DNA complexes can be reliably analyzed by ESI mass spectrometry.

  11. Mapping the Anopheles gambiae odorant binding protein 1 (AgamOBP1) using modeling techniques, site directed mutagenesis, circular dichroism and ligand binding assays.

    Science.gov (United States)

    Rusconi, B; Maranhao, A C; Fuhrer, J P; Krotee, P; Choi, S H; Grun, F; Thireou, T; Dimitratos, S D; Woods, D F; Marinotti, O; Walter, M F; Eliopoulos, E

    2012-08-01

    The major malaria vector in Sub-Saharan Africa is the Anopheles gambiae mosquito. This species is a key target of malaria control measures. Mosquitoes find humans primarily through olfaction, yet the molecular mechanisms associated with host-seeking behavior remain largely unknown. To further understand the functionality of A. gambiae odorant binding protein 1 (AgamOBP1), we combined in silico protein structure modeling and site-directed mutagenesis to generate 16 AgamOBP1 protein analogues containing single point mutations of interest. Circular dichroism (CD) and ligand-binding assays provided data necessary to probe the effects of the point mutations on ligand binding and the overall structure of AgamOBP1. Far-UV CD spectra of mutated AgamOBP1 variants displayed both substantial decreases to ordered α-helix structure (up to22%) and increases to disordered α-helix structure(up to 15%) with only minimal changes in random coil (unordered) structure. In mutations Y54A, Y122A and W114Q, aromatic side chain removal from the binding site significantly reduced N-phenyl-1-naphthylamine binding. Several non-aromatic mutations (L15T, L19T, L58T, L58Y, M84Q, M84K, H111A, Y122A and L124T) elicited changes to protein conformation with subsequent effects on ligand binding. This study provides empirical evidence for the in silico predicted functions of specific amino acids in AgamOBP1 folding and ligand binding characteristics. PMID:22564768

  12. Visualizing Risk Prediction Models

    OpenAIRE

    Vanya Van Belle; Ben Van Calster

    2015-01-01

    Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...

  13. Pyroshock prediction procedures

    Science.gov (United States)

    Piersol, Allan G.

    2002-05-01

    Given sufficient effort, pyroshock loads can be predicted by direct analytical procedures using Hydrocodes that analytically model the details of the pyrotechnic explosion and its interaction with adjacent structures, including nonlinear effects. However, it is more common to predict pyroshock environments using empirical procedures based upon extensive studies of past pyroshock data. Various empirical pyroshock prediction procedures are discussed, including those developed by the Jet Propulsion Laboratory, Lockheed-Martin, and Boeing.

  14. Predicting transformers oil parameters

    OpenAIRE

    Shaban, K.; El-Hag, A.; Matveev, A.

    2009-01-01

    In this paper different configurations of artificial neural networks are applied to predict various transformers oil parameters. The prediction is performed through modeling the relationship between the transformer insulation resistance extracted from the Megger test and the breakdown strength, interfacial tension, acidity and the water content of the transformers oil. The process of predicting these oil parameters statuses is carried out using two different configurations of neural networks....

  15. Is Suicide Predictable?

    OpenAIRE

    Asmaee, S; Mosavi, N; R Abdul Rashid; H Habi; Seghatoleslam, T; Naseri, A.

    2012-01-01

    Background: The current study aimed to test the hypothesis: Is suicide predictable? And try to classify the predictive factors in multiple suicide attempts. Methods: A cross-sectional study was administered to 223 multiple attempters, women who came to a medical poison centre after a suicide attempt. The participants were young, poor, and single. A Logistic Regression Analiysis was used to classify the predictive factors of suicide. Results: Women who had multiple suicide attempts exhibited a...

  16. Erythrocyte 3H-ouabain binding and digitalis treatment in ethanol addicted patients

    International Nuclear Information System (INIS)

    The binding of 3H-ouabain to human erythrocytes was analyzed in a population of hospitalized male ethanol addicted patients under long term digitalis treatment. In the non-alcoholic patient group the long term digitalis treatment induced an increase in Bmax and Kd values; such modification was not observed in the alcoholic patients. Chronic alcohol intake itself induced an increase in 3H-ouabain kinetic parameters. These observations confirm that ouabain binding to human erythrocytes is subject to pharmacological and toxicological regulation and that adaptive changes in peripheral tissues can be useful in predicting possible parallel modifications in other less accessible tissues. 22 references, 1 table

  17. In silico mechanistic profiling to probe small molecule binding to sulfotransferases.

    Directory of Open Access Journals (Sweden)

    Virginie Y Martiny

    Full Text Available Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug-drug interactions. We focus on sulfotransferases (SULTs, a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands' binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes.

  18. Genetics Home Reference: mannose-binding lectin deficiency

    Science.gov (United States)

    ... Health Conditions mannose-binding lectin deficiency mannose-binding lectin deficiency Enable Javascript to view the expand/collapse ... PDF Open All Close All Description Mannose-binding lectin deficiency is a condition that affects the immune ...

  19. Peptide binding specificity of the chaperone calreticulin

    DEFF Research Database (Denmark)

    Sandhu, N.; Duus, K.; Jorgensen, C.S.;

    2007-01-01

    Calreticulin is a molecular chaperone with specificity for polypeptides and N-linked monoglucosylated glycans. In order to determine the specificity of polypeptide binding, the interaction of calreticulin with polypeptides was investigated using synthetic peptides of different length and composit...

  20. Hardware device binding and mutual authentication

    Energy Technology Data Exchange (ETDEWEB)

    Hamlet, Jason R; Pierson, Lyndon G

    2014-03-04

    Detection and deterrence of device tampering and subversion by substitution may be achieved by including a cryptographic unit within a computing device for binding multiple hardware devices and mutually authenticating the devices. The cryptographic unit includes a physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generates a binding PUF value. The cryptographic unit uses the binding PUF value during an enrollment phase and subsequent authentication phases. During a subsequent authentication phase, the cryptographic unit uses the binding PUF values of the multiple hardware devices to generate a challenge to send to the other device, and to verify a challenge received from the other device to mutually authenticate the hardware devices.

  1. Hydrogen binding in vacancy clusters in platinum

    International Nuclear Information System (INIS)

    The binding of hydrogen in different vacancy complexes in platinum metal was investigated with atomic-scale sensitivity using perturbed angular correlations of gamma rays (PAC). Hydrogen was introduced by cathodic charging. Detrapping was monitored microscopically during desorption at 294 K by changes in site fractions of hydrogen-decorated and undecorated complexes. Analysis of desorption includes effects of retrapping of hydrogen at other sites. Assuming a trap concentration of 10-3, binding enthalpies of 0.23(2), 0.28(1), 0.24(1) and >0.20 eV are obtained for hydrogen atoms in 1V to 4V complexes, respectively. The small differences between the binding enthalpies demonstrate that hydrogen binding is insensitive to the detailed geometrical structure of small vacancy complexes. However, the magnitudes found here are a factor of two smaller than in the literature. (orig.)

  2. System Support for Managing Invalid Bindings

    CERN Document Server

    Das, Lachhman; Shah, Azhar; Khoumbati, Khalil; 10.5121/iju.2011.2303

    2011-01-01

    Context-aware adaptation is a central aspect of pervasive computing applications, enabling them to adapt and perform tasks based on contextual information. One of the aspects of context-aware adaptation is reconfiguration in which bindings are created between application component and remote services in order to realize new behaviour in response to contextual information. Various research efforts provide reconfiguration support and allow the development of adaptive context-aware applications from high-level specifications, but don't consider failure conditions that might arise during execution of such applications, making bindings between application and remote services invalid. To this end, we propose and implement our design approach to reconfiguration to manage invalid bindings. The development and modification of adaptive context-aware applications is a complex task, and an issue of an invalidity of bindings further complicates development efforts. To reduce the development efforts, our approach provides ...

  3. Combinatorial microRNA target predictions

    DEFF Research Database (Denmark)

    Krek, Azra; Grün, Dominic; Poy, Matthew N.;

    2005-01-01

    MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript1, 2, 3. Different combinations of microRNAs are expressed in...... different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published micro......RNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results...

  4. Binding of heparan sulfate to Staphylococcus aureus.

    OpenAIRE

    Liang, O D; Ascencio, F; Fransson, L A; Wadström, T

    1992-01-01

    Heparan sulfate binds to proteins present on the surface of Staphylococcus aureus cells. Binding of 125I-heparan sulfate to S. aureus was time dependent, saturable, and influenced by pH and ionic strength, and cell-bound 125I-heparan sulfate was displaced by unlabelled heparan sulfate or heparin. Other glycosaminoglycans of comparable size (chondroitin sulfate and dermatan sulfate), highly glycosylated glycoprotein (hog gastric mucin), and some anionic polysaccharides (dextran sulfate and RNA...

  5. DNA-Aptamers Binding Aminoglycoside Antibiotics

    OpenAIRE

    Nadia Nikolaus; Beate Strehlitz

    2014-01-01

    Aptamers are short, single stranded DNA or RNA oligonucleotides that are able to bind specifically and with high affinity to their non-nucleic acid target molecules. This binding reaction enables their application as biorecognition elements in biosensors and assays. As antibiotic residues pose a problem contributing to the emergence of antibiotic-resistant pathogens and thereby reducing the effectiveness of the drug to fight human infections, we selected aptamers targeted against the aminog...

  6. Penicillin-Binding Protein Imaging Probes

    OpenAIRE

    Kocaoglu, Ozden; Carlson, Erin E.

    2013-01-01

    Penicillin-binding proteins (PBPs) are membrane-associated proteins involved in the biosynthesis of peptidoglycan (PG), the main component of bacterial cell walls. These proteins were discovered and named for their affinity to bind the β-lactam antibiotic penicillin. The importance of the PBPs has long been appreciated; however, the apparent functional redundancy of the ~5–15 proteins that most bacteria possess makes determination of their individual roles difficult. Existing techniques to st...

  7. Photonic Binding in Silicon-Colloid Microcavities

    OpenAIRE

    Xifré-Pérez, E.; García de Abajo, Francisco Javier; Fenollosa Esteve, Roberto; Meseguer, Francisco

    2009-01-01

    Photonic binding between two identical silicon-colloid-based microcavities is studied by using a generalized multipolar expansion. In contrast with previous works, we focus on low-order cavity modes that resemble low-energy electronic orbitals. For conservative light intensities, the interaction between cavity modes with moderate Q factors produces extremely large particle acceleration values. Optical forces dominate over vanderWaals, gravity, and Brownian motion, and they show a binding-anti...

  8. Liver Fatty Acid Binding Protein and Obesity

    OpenAIRE

    Atshaves, B.P.; Martin, G G; Hostetler, H.A.; McIntosh, A.L.; Kier, A B; Schroeder, F.

    2010-01-01

    While low levels of unesterified long chain fatty acids (LCFAs) are normal metabolic intermediates of dietary and endogenous fat, LCFAs are also potent regulators of key receptors/enzymes, and at high levels become toxic detergents within the cell. Elevated levels of LCFAs are associated with diabetes, obesity, and metabolic syndrome. Consequently, mammals evolved fatty acid binding proteins (FABPs) that bind/sequester these potentially toxic free fatty acids in the cytosol and present them f...

  9. Copper binding to soil fulvic and humic acids: NICA-Donnan modeling and conditional affinity spectra.

    Science.gov (United States)

    Xu, Jinling; Tan, Wenfeng; Xiong, Juan; Wang, Mingxia; Fang, Linchuan; Koopal, Luuk K

    2016-07-01

    Binding of Cu(II) to soil fulvic acid (JGFA), soil humic acids (JGHA, JLHA), and lignite-based humic acid (PAHA) was investigated through NICA-Donnan modeling and conditional affinity spectrum (CAS). It is to extend the knowledge of copper binding by soil humic substances (HS) both in respect of enlarging the database of metal ion binding to HS and obtaining a good insight into Cu binding to the functional groups of FA and HA by using the NICA-Donnan model to unravel the intrinsic and conditional affinity spectra. Results showed that Cu binding to HS increased with increasing pH and decreasing ionic strength. The amount of Cu bound to the HAs was larger than the amount bound to JGFA. Milne's generic parameters did not provide satisfactory predictions for the present soil HS samples, while material-specific NICA-Donnan model parameters described and predicted Cu binding to the HS well. Both the 'low' and 'high' concentration fitting procedures indicated a substantial bidentate structure of the Cu complexes with HS. By means of CAS underlying NICA isotherm, which was scarcely used, the nature of the binding at different solution conditions for a given sample and the differences in binding mode were illustrated. It was indicated that carboxylic group played an indispensable role in Cu binding to HS in that the carboxylic CAS had stronger conditional affinity than the phenolic distribution due to its large degree of proton dissociation. The fact was especially true for JGFA and JLHA which contain much larger amount of carboxylic groups, and the occupation of phenolic sites by Cu was negligible. Comparable amounts of carboxylic and phenolic groups on PAHA and JGHA, increased the occupation of phenolic type sites by Cu. The binding strength of PAHA-Cu and JGHA-Cu was stronger than that of JGFA-Cu and JLHA-Cu. The presence of phenolic groups increased the chance of forming more stable complexes, such as the salicylate-Cu or catechol-Cu type structures. PMID:27061366

  10. Radiation damage to DNA-binding proteins

    International Nuclear Information System (INIS)

    The DNA-binding properties of proteins are strongly affected upon irradiation. The tetrameric lactose repressor (a dimer of dimers) losses its ability to bind operator DNA as soon as at least two damages per protomer of each dimer occur. The monomeric MC1 protein losses its ability to bind DNA in two steps : i) at low doses only the specific binding is abolished, whereas the non-specific one is still possible; ii) at high doses all binding vanishes. Moreover, the DNA bending induced by MC1 binding is less pronounced for a protein that underwent the low dose irradiation. When the entire DNA-protein complexes are irradiated, the observed disruption of the complexes is mainly due to the damage of the proteins and not to that of DNA. The doses necessary for complex disruption are higher than those inactivating the free protein. This difference, larger for MC1 than for lactose repressor, is due to the protection of the protein by the bound DNA. The oxidation of the protein side chains that are accessible to the radiation-induced hydroxyl radicals seems to represent the inactivating damage

  11. Impact of receptor clustering on ligand binding

    Directory of Open Access Journals (Sweden)

    Caré Bertrand R

    2011-03-01

    Full Text Available Abstract Background Cellular response to changes in the concentration of different chemical species in the extracellular medium is induced by ligand binding to dedicated transmembrane receptors. Receptor density, distribution, and clustering may be key spatial features that influence effective and proper physical and biochemical cellular responses to many regulatory signals. Classical equations describing this kind of binding kinetics assume the distributions of interacting species to be homogeneous, neglecting by doing so the impact of clustering. As there is experimental evidence that receptors tend to group in clusters inside membrane domains, we investigated the effects of receptor clustering on cellular receptor ligand binding. Results We implemented a model of receptor binding using a Monte-Carlo algorithm to simulate ligand diffusion and binding. In some simple cases, analytic solutions for binding equilibrium of ligand on clusters of receptors are provided, and supported by simulation results. Our simulations show that the so-called "apparent" affinity of the ligand for the receptor decreases with clustering although the microscopic affinity remains constant. Conclusions Changing membrane receptors clustering could be a simple mechanism that allows cells to change and adapt its affinity/sensitivity toward a given stimulus.

  12. The readiness potential reflects intentional binding

    Directory of Open Access Journals (Sweden)

    Han-Gue eJo

    2014-06-01

    Full Text Available When a voluntary action is causally linked with a sensory outcome, the action and its consequent effect are perceived as being closer together in time. This effect is called intentional binding. Although many experiments were conducted on this phenomenon, the underlying neural mechanisms are not well understood. While intentional binding is specific to voluntary action, we presumed that preconscious brain activity (the readiness potential, RP, which occurs before an action is made, might play an important role in this binding effect. In this study, the brain dynamics were recorded with electroencephalography (EEG and analyzed in single-trials in order to estimate whether intentional binding is correlated with the early neural processes. Moreover, we were interested in different behavioral performance between meditators and non-meditators since meditators are expected to be able to keep attention more consistently on a task. Thus, we performed the intentional binding paradigm with twenty mindfulness meditators and compared them to matched controls. Although, we did not observe a group effect on either behavioral data or EEG recordings, we found that self-initiated movements following ongoing negative deflections of slow cortical potentials (SCPs result in a stronger binding effect compared to positive potentials, especially regarding the perceived time of the consequent effect. Our results provide the first direct evidence that the early neural activity within the range of SCPs affects perceived time of a sensory outcome that is caused by intentional action.

  13. DNA-Aptamers Binding Aminoglycoside Antibiotics

    Directory of Open Access Journals (Sweden)

    Nadia Nikolaus

    2014-02-01

    Full Text Available Aptamers are short, single stranded DNA or RNA oligonucleotides that are able to bind specifically and with high affinity to their non-nucleic acid target molecules. This binding reaction enables their application as biorecognition elements in biosensors and assays. As antibiotic residues pose a problem contributing to the emergence of antibiotic-resistant pathogens and thereby reducing the effectiveness of the drug to fight human infections, we selected aptamers targeted against the aminoglycoside antibiotic kanamycin A with the aim of constructing a robust and functional assay that can be used for water analysis. With this work we show that aptamers that were derived from a Capture-SELEX procedure targeting against kanamycin A also display binding to related aminoglycoside antibiotics. The binding patterns differ among all tested aptamers so that there are highly substance specific aptamers and more group specific aptamers binding to a different variety of aminoglycoside antibiotics. Also the region of the aminoglycoside antibiotics responsible for aptamer binding can be estimated. Affinities of the different aptamers for their target substance, kanamycin A, are measured with different approaches and are in the micromolar range. Finally, the proof of principle of an assay for detection of kanamycin A in a real water sample is given.

  14. Protein Dynamics in an RNA Binding Protein

    Science.gov (United States)

    Hall, Kathleen

    2006-03-01

    Using ^15N NMR relaxation measurements, analyzed with the Lipari-Szabo formalism, we have found that the human U1A RNA binding protein has ps-ns motions in those loops that make contact with RNA. Specific mutations can alter the extent and pattern of motions, and those proteins inevitably lose RNA binding affinity. Proteins with enhanced mobility of loops and termini presumably lose affinity due to increased conformational sampling by those parts of the protein that interact directly with RNA. There is an entropic penalty associated with locking down those elements upon RNA binding, in addition to a loss of binding efficiency caused by the increased number of conformations adopted by the protein. However, in addition to local conformational heterogeneity, analysis of molecular dynamics trajectories by Reorientational Eigenmode Dynamics reveals that loops of the wild type protein undergo correlated motions that link distal sites across the binding surface. Mutations that disrupt correlated motions result in weaker RNA binding, implying that there is a network of interactions across the surface of the protein. (KBH was a Postdoctoral Fellow with Al Redfield from 1985-1990). This work was supported by the NIH (to KBH) and NSF (SAS).

  15. The readiness potential reflects intentional binding

    Science.gov (United States)

    Jo, Han-Gue; Wittmann, Marc; Hinterberger, Thilo; Schmidt, Stefan

    2014-01-01

    When a voluntary action is causally linked with a sensory outcome, the action and its consequent effect are perceived as being closer together in time. This effect is called intentional binding. Although many experiments were conducted on this phenomenon, the underlying neural mechanisms are not well understood. While intentional binding is specific to voluntary action, we presumed that preconscious brain activity (the readiness potential, RP), which occurs before an action is made, might play an important role in this binding effect. In this study, the brain dynamics were recorded with electroencephalography (EEG) and analyzed in single-trials in order to estimate whether intentional binding is correlated with the early neural processes. Moreover, we were interested in different behavioral performance between meditators and non-meditators since meditators are expected to be able to keep attention more consistently on a task. Thus, we performed the intentional binding paradigm with 20 mindfulness meditators and compared them to matched controls. Although, we did not observe a group effect on either behavioral data or EEG recordings, we found that self-initiated movements following ongoing negative deflections of slow cortical potentials (SCPs) result in a stronger binding effect compared to positive potentials, especially regarding the perceived time of the consequent effect. Our results provide the first direct evidence that the early neural activity within the range of SCPs affects perceived time of a sensory outcome that is caused by intentional action. PMID:24959135

  16. Theoretical studies of binding of mannose-binding protein to monosaccharides

    Science.gov (United States)

    Aida-Hyugaji, Sachiko; Takano, Keiko; Takada, Toshikazu; Hosoya, Haruo; Kojima, Naoya; Mizuochi, Tsuguo; Inoue, Yasushi

    2004-11-01

    Binding properties of mannose-binding protein (MBP) to monosaccharides are discussed based on ab initio molecular orbital calculations for cluster models constructed. The calculated binding energies indicate that MBP has an affinity for N-acetyl- D-glucosamine, D-mannose, L-fucose, and D-glucose rather than D-galactose and N-acetyl- D-galactosamine, which is consistent with the biochemical experimental results. Electrostatic potential surfaces at the binding site of four monosaccharides having binding properties matched well with that of MBP. A vacant frontier orbital was found to be localized around the binding site of MBP, suggesting that MBP-monosaccharide interaction may occur through electrostatic and orbital interactions.

  17. To Bind or not to Bind: It’s in the Contract

    DEFF Research Database (Denmark)

    Tvarnø, Christina D.

    2016-01-01

    This article discusses the formalization of collaboration through partnering contracts in the construction industry in the USA, Great Britain and Denmark. The article compares the different types of collaborative partnering contracts in the three countries, and provides a conclusion on whether the...... collaborative partnering contract should be binding or non-binding, based on the three empirical contracts analyzed in this article. The partnering contracts in Great Britain and Denmark are legally binding, while in the USA the partnering agreements are non-binding charters or letters of intent. This article...... discusses, in a theoretical perspective, the legal reasoning behind the different partnering approaches, both from a historical and contract law perspective, and furthermore applies a game theoretical approach in evaluating binding versus non-binding partnering contracts. The analysis focuses on private...

  18. Thermodynamic parameters of the binding of retinol to binding proteins and to membranes

    International Nuclear Information System (INIS)

    Retinol (vitamin A alcohol) is a hydrophobic compound and distributes in vivo mainly between binding proteins and cellular membranes. To better clarify the nature of the interactions of retinol with these phases which have a high affinity for it, the thermodynamic parameters of these interactions were studied. The temperature-dependence profiles of the binding of retinol to bovine retinol binding protein, bovine serum albumin, unilamellar vesicles of dioleoylphosphatidylcholine, and plasma membranes from rat liver were determined. It was found that binding of retinol to retinol binding protein is characterized by a large increase in entropy and no change in enthalpy. Binding to albumin is driven by enthalpy and is accompanied by a decrease in entropy. Partitioning of retinal into unilamellar vesicles and into plasma membranes is stabilized both by enthalpic and by entropic components. The implications of these finding are discussed

  19. Sequence and chromatin determinants of cell-type-specific transcription factor binding.

    Science.gov (United States)

    Arvey, Aaron; Agius, Phaedra; Noble, William Stafford; Leslie, Christina

    2012-09-01

    Gene regulatory programs in distinct cell types are maintained in large part through the cell-type-specific binding of transcription factors (TFs). The determinants of TF binding include direct DNA sequence preferences, DNA sequence preferences of cofactors, and the local cell-dependent chromatin context. To explore the contribution of DNA sequence signal, histone modifications, and DNase accessibility to cell-type-specific binding, we analyzed 286 ChIP-seq experiments performed by the ENCODE Consortium. This analysis included experiments for 67 transcriptional regulators, 15 of which were profiled in both the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines. To model TF-bound regions, we trained support vector machines (SVMs) that use flexible k-mer patterns to capture DNA sequence signals more accurately than traditional motif approaches. In addition, we trained SVM spatial chromatin signatures to model local histone modifications and DNase accessibility, obtaining significantly more accurate TF occupancy predictions than simpler approaches. Consistent with previous studies, we find that DNase accessibility can explain cell-line-specific binding for many factors. However, we also find that of the 10 factors with prominent cell-type-specific binding patterns, four display distinct cell-type-specific DNA sequence preferences according to our models. Moreover, for two factors we identify cell-specific binding sites that are accessible in both cell types but bound only in one. For these sites, cell-type-specific sequence models, rather than DNase accessibility, are better able to explain differential binding. Our results suggest that using a single motif for each TF and filtering for chromatin accessible loci is not always sufficient to accurately account for cell-type-specific binding profiles. PMID:22955984

  20. Structural Determinants of DNA Binding by a P. falciparum ApiAP2 Transcriptional Regulator

    Energy Technology Data Exchange (ETDEWEB)

    Lindner, Scott E.; De Silva, Erandi K.; Keck, James L.; Llinás, Manuel (Princeton); (UW-MED)

    2010-11-05

    Putative transcription factors have only recently been identified in the Plasmodium spp., with the major family of regulators comprising the Apicomplexan Apetala2 (AP2) proteins. To better understand the DNA-binding mechanisms of these transcriptional regulators, we characterized the structure and in vitro function of an AP2 DNA-binding domain from a prototypical Apicomplexan AP2 protein, PF14{_}0633 from Plasmodium falciparum. The X-ray crystal structure of the PF14{_}0633 AP2 domain bound to DNA reveals a {beta}-sheet fold that binds the DNA major groove through base-specific and backbone contacts; a prominent {alpha}-helix supports the {beta}-sheet structure. Substitution of predicted DNA-binding residues with alanine weakened or eliminated DNA binding in solution. In contrast to plant AP2 domains, the PF14{_}0633 AP2 domain dimerizes upon binding to DNA through a domain-swapping mechanism in which the {alpha}-helices of the AP2 domains pack against the {beta}-sheets of the dimer mates. DNA-induced dimerization of PF14{_}0633 may be important for tethering two distal DNA loci together in the nucleus and/or for inducing functional rearrangements of its domains to facilitate transcriptional regulation. Consistent with a multisite binding mode, at least two copies of the consensus sequence recognized by PF14{_}0633 are present upstream of a previously identified group of sporozoite-stage genes. Taken together, these findings illustrate how Plasmodium has adapted the AP2 DNA-binding domain for genome-wide transcriptional regulation.