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Sample records for protein sequence signatures

  1. Shotgun protein sequencing.

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    Faulon, Jean-Loup Michel; Heffelfinger, Grant S.

    2009-06-01

    A novel experimental and computational technique based on multiple enzymatic digestion of a protein or protein mixture that reconstructs protein sequences from sequences of overlapping peptides is described in this SAND report. This approach, analogous to shotgun sequencing of DNA, is to be used to sequence alternative spliced proteins, to identify post-translational modifications, and to sequence genetically engineered proteins.

  2. Movement Pattern Analysis Based on Sequence Signatures

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    Seyed Hossein Chavoshi

    2015-09-01

    Full Text Available Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC, a type of calculus that represents qualitative data on moving point objects (MPOs, and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.

  3. Protein signature of lung cancer tissues.

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    Michael R Mehan

    Full Text Available Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan to compare protein expression signatures of non small-cell lung cancer (NSCLC tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.

  4. The 82-plex plasma protein signature that predicts increasing inflammation

    DEFF Research Database (Denmark)

    Tepel, Martin; Beck, Hans C; Tan, Qihua

    2015-01-01

    The objective of the study was to define the specific plasma protein signature that predicts the increase of the inflammation marker C-reactive protein from index day to next-day using proteome analysis and novel bioinformatics tools. We performed a prospective study of 91 incident kidney....... The prediction model selected and validated 82 plasma proteins which determined increased next-day C-reactive protein (area under receiver-operator-characteristics curve, 0.772; 95% confidence interval, 0.669 to 0.876; P signature (P ....001) was associated with observed increased next-day C-reactive protein. The 82-plex protein signature outperformed routine clinical procedures. The category-free net reclassification index improved with 82-plex plasma protein signature (total net reclassification index, 88.3%). Using the 82-plex plasma protein...

  5. Protein sequence comparison and protein evolution

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    Pearson, W.R. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Biochemistry

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. This tutorial examines how the information conserved during the evolution of a protein molecule can be used to infer reliably homology, and thus a shared proteinfold and possibly a shared active site or function. The authors start by reviewing a geological/evolutionary time scale. Next they look at the evolution of several protein families. During the tutorial, these families will be used to demonstrate that homologous protein ancestry can be inferred with confidence. They also examine different modes of protein evolution and consider some hypotheses that have been presented to explain the very earliest events in protein evolution. The next part of the tutorial will examine the technical aspects of protein sequence comparison. Both optimal and heuristic algorithms and their associated parameters that are used to characterize protein sequence similarities are discussed. Perhaps more importantly, they survey the statistics of local similarity scores, and how these statistics can both be used to improve the selectivity of a search and to evaluate the significance of a match. They them examine distantly related members of three protein families, the serine proteases, the glutathione transferases, and the G-protein-coupled receptors (GCRs). Finally, the discuss how sequence similarity can be used to examine internal repeated or mosaic structures in proteins.

  6. Sequence analysis of the aminoacylase-1 family. A new proposed signature for metalloexopeptidases.

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    Biagini, A; Puigserver, A

    2001-03-01

    The amino acid sequence analysis of the human and porcine aminoacylases-1, the carboxypeptidase S precursor from Saccharomyces cerevisiae, the succinyl-diaminopimelate desuccinylase from Escherichia coli, Haemophilus influenzae and Corynebacterium glutamicum, the acetylornithine deacetylase from Escherichia coli and Dictyostelium discoideum and the carboxypeptidase G(2) precursor from Pseudomonas strain, using the Basic Local Alignment Search Tool (BLAST) and the Position-Specific Iterated BLAST (PSI-BLAST), allowed us to suggest that all these enzymes, which share common functional and biochemical features, belong to the same structural family. The three amino acid blocks which were found to be highly conserved, using the CLUSTAL W program, could be assigned to the catalytic active site, based on the general three-dimensional structure of the carboxypeptidase G(2) from the Pseudomonas strain precursor. Six additional proteins with the same signature have been retrieved after performing two successive PSI-BLAST iterations using the sequence of the conserved motif, namely Lactobacillus delbrueckii aminoacyl-histidine dipeptidase, Streptomyces griseus aminopeptidase, Saccharomyces cerevisiae aminopeptidase Y precursor, two Bacillus stearothermophilus N-carbamyl-L-amino acid amidohydrolases and Pseudomonas sp. hydantoin utilization protein C. The three conserved amino acid motifs corresponded to the following blocks: (i) [S, G, A]-H-x-D-x-V; (ii) G-x-x-D; and (iii) x-E-E. This new sequence signature is clearly different from that commonly reported in the literature for proteins belonging to the ArgE/DapE/CPG2/YscS family.

  7. A distinct epigenetic signature at targets of a leukemia protein

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    van der Spek Peter

    2007-02-01

    Full Text Available Abstract Background Human myelogenous leukemia characterized by either the non random t(8; 21(q22; q22 or t(16; 21(q24; q22 chromosome translocations differ for both their biological and clinical features. Some of these features could be consequent to differential epigenetic transcriptional deregulation at AML1 targets imposed by AML1-MTG8 and AML1-MTG16, the fusion proteins deriving from the two translocations. Preliminary findings showing that these fusion proteins lead to transcriptional downregulation of AML1 targets, marked by repressive chromatin changes, would support this hypothesis. Here we show that combining conventional global gene expression arrays with the power of bioinformatic genomic survey of AML1-consensus sequences is an effective strategy to identify AML1 targets whose transcription is epigenetically downregulated by the leukemia-associated AML1-MTG16 protein. Results We interrogated mouse gene expression microarrays with probes generated either from 32D cells infected with a retroviral vector carrying AML1-MTG16 and unable of granulocyte differentiation and proliferation in response to the granulocyte colony stimulating factor (G-CSF, or from 32D cells infected with the cognate empty vector. From the analysis of differential gene expression alone (using as criteria a p value 3, we were unable to conclude which of the 37 genes downregulated by AML1-MTG16 were, or not, direct AML1 targets. However, when we applied a bioinformatic approach to search for AML1-consensus sequences in the 10 Kb around the gene transcription start sites, we closed on 17 potential direct AML1 targets. By focusing on the most significantly downregulated genes, we found that both the AML1-consensus and the transcription start site chromatin regions were significantly marked by aberrant repressive histone tail changes. Further, the promoter of one of these genes, containing a CpG island, was aberrantly methylated. Conclusion This study shows that a

  8. Signature proteins for the major clades of Cyanobacteria

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    Mathews Divya W

    2010-01-01

    Full Text Available Abstract Background The phylogeny and taxonomy of cyanobacteria is currently poorly understood due to paucity of reliable markers for identification and circumscription of its major clades. Results A combination of phylogenomic and protein signature based approaches was used to characterize the major clades of cyanobacteria. Phylogenetic trees were constructed for 44 cyanobacteria based on 44 conserved proteins. In parallel, Blastp searches were carried out on each ORF in the genomes of Synechococcus WH8102, Synechocystis PCC6803, Nostoc PCC7120, Synechococcus JA-3-3Ab, Prochlorococcus MIT9215 and Prochlor. marinus subsp. marinus CCMP1375 to identify proteins that are specific for various main clades of cyanobacteria. These studies have identified 39 proteins that are specific for all (or most cyanobacteria and large numbers of proteins for other cyanobacterial clades. The identified signature proteins include: (i 14 proteins for a deep branching clade (Clade A of Gloebacter violaceus and two diazotrophic Synechococcus strains (JA-3-3Ab and JA2-3-B'a; (ii 5 proteins that are present in all other cyanobacteria except those from Clade A; (iii 60 proteins that are specific for a clade (Clade C consisting of various marine unicellular cyanobacteria (viz. Synechococcus and Prochlorococcus; (iv 14 and 19 signature proteins that are specific for the Clade C Synechococcus and Prochlorococcus strains, respectively; (v 67 proteins that are specific for the Low B/A ecotype Prochlorococcus strains, containing lower ratio of chl b/a2 and adapted to growth at high light intensities; (vi 65 and 8 proteins that are specific for the Nostocales and Chroococcales orders, respectively; and (vii 22 and 9 proteins that are uniquely shared by various Nostocales and Oscillatoriales orders, or by these two orders and the Chroococcales, respectively. We also describe 3 conserved indels in flavoprotein, heme oxygenase and protochlorophyllide oxidoreductase proteins that

  9. Novel algorithms for protein sequence analysis

    NARCIS (Netherlands)

    Ye, Kai

    2008-01-01

    Each protein is characterized by its unique sequential order of amino acids, the so-called protein sequence. Biology”s paradigm is that this order of amino acids determines the protein”s architecture and function. In this thesis, we introduce novel algorithms to analyze protein sequences. Chapter 1

  10. Nature of protein family signatures: insights from singular value analysis of position-specific scoring matrices.

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    Akira R Kinjo

    Full Text Available Position-specific scoring matrices (PSSMs are useful for detecting weak homology in protein sequence analysis, and they are thought to contain some essential signatures of the protein families. In order to elucidate what kind of ingredients constitute such family-specific signatures, we apply singular value decomposition to a set of PSSMs and examine the properties of dominant right and left singular vectors. The first right singular vectors were correlated with various amino acid indices including relative mutability, amino acid composition in protein interior, hydropathy, or turn propensity, depending on proteins. A significant correlation between the first left singular vector and a measure of site conservation was observed. It is shown that the contribution of the first singular component to the PSSMs act to disfavor potentially but falsely functionally important residues at conserved sites. The second right singular vectors were highly correlated with hydrophobicity scales, and the corresponding left singular vectors with contact numbers of protein structures. It is suggested that sequence alignment with a PSSM is essentially equivalent to threading supplemented with functional information. In addition, singular vectors may be useful for analyzing and annotating the characteristics of conserved sites in protein families.

  11. HIV protein sequence hotspots for crosstalk with host hub proteins.

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    Mahdi Sarmady

    Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

  12. Global transcriptional profiling of the toxic dinoflagellate Alexandrium fundyense using Massively Parallel Signature Sequencing

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    Anderson Donald M

    2006-04-01

    Full Text Available Abstract Background Dinoflagellates are one of the most important classes of marine and freshwater algae, notable both for their functional diversity and ecological significance. They occur naturally as free-living cells, as endosymbionts of marine invertebrates and are well known for their involvement in "red tides". Dinoflagellates are also notable for their unusual genome content and structure, which suggests that the organization and regulation of dinoflagellate genes may be very different from that of most eukaryotes. To investigate the content and regulation of the dinoflagellate genome, we performed a global analysis of the transcriptome of the toxic dinoflagellate Alexandrium fundyense under nitrate- and phosphate-limited conditions using Massively Parallel Signature Sequencing (MPSS. Results Data from the two MPSS libraries showed that the number of unique signatures found in A. fundyense cells is similar to that of humans and Arabidopsis thaliana, two eukaryotes that have been extensively analyzed using this method. The general distribution, abundance and expression patterns of the A. fundyense signatures were also quite similar to other eukaryotes, and at least 10% of the A. fundyense signatures were differentially expressed between the two conditions. RACE amplification and sequencing of a subset of signatures showed that multiple signatures arose from sequence variants of a single gene. Single signatures also mapped to different sequence variants of the same gene. Conclusion The MPSS data presented here provide a quantitative view of the transcriptome and its regulation in these unusual single-celled eukaryotes. The observed signature abundance and distribution in Alexandrium is similar to that of other eukaryotes that have been analyzed using MPSS. Results of signature mapping via RACE indicate that many signatures result from sequence variants of individual genes. These data add to the growing body of evidence for widespread gene

  13. Protein signatures using electrostatic molecular surfaces in harmonic space

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    C. Sofia Carvalho

    2013-10-01

    Full Text Available We developed a novel method based on the Fourier analysis of protein molecular surfaces to speed up the analysis of the vast structural data generated in the post-genomic era. This method computes the power spectrum of surfaces of the molecular electrostatic potential, whose three-dimensional coordinates have been either experimentally or theoretically determined. Thus we achieve a reduction of the initial three-dimensional information on the molecular surface to the one-dimensional information on pairs of points at a fixed scale apart. Consequently, the similarity search in our method is computationally less demanding and significantly faster than shape comparison methods. As proof of principle, we applied our method to a training set of viral proteins that are involved in major diseases such as Hepatitis C, Dengue fever, Yellow fever, Bovine viral diarrhea and West Nile fever. The training set contains proteins of four different protein families, as well as a mammalian representative enzyme. We found that the power spectrum successfully assigns a unique signature to each protein included in our training set, thus providing a direct probe of functional similarity among proteins. The results agree with established biological data from conventional structural biochemistry analyses.

  14. WildSpan: mining structured motifs from protein sequences

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    Chen Chien-Yu

    2011-03-01

    of WildSpan is developed for discovering functional regions of a single protein by referring to a set of related sequences (e.g. its homologues. The discovered W-patterns are used to characterize the protein sequence and the results are compared with the conserved positions identified by multiple sequence alignment (MSA. The family-based mining mode of WildSpan is developed for extracting sequence signatures for a group of related proteins (e.g. a protein family for protein function classification. In this situation, the discovered W-patterns are compared with PROSITE patterns as well as the patterns generated by three existing methods performing the similar task. Finally, analysis on execution time of running WildSpan reveals that the proposed pruning strategy is effective in improving the scalability of the proposed algorithm. Conclusions The mining results conducted in this study reveal that WildSpan is efficient and effective in discovering functional signatures of proteins directly from sequences. The proposed pruning strategy is effective in improving the scalability of WildSpan. It is demonstrated in this study that the W-patterns discovered by WildSpan provides useful information in characterizing protein sequences. The WildSpan executable and open source codes are available on the web (http://biominer.csie.cyu.edu.tw/wildspan.

  15. Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest.

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    Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

    2017-05-25

    Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understanding interspecies transmission of influenza viruses, we are no closer to predicting zoonotic strains that can lead to an outbreak. We have previously discovered distinct host tropism protein signatures of avian, human and zoonotic influenza strains obtained from host tropism predictions on individual protein sequences. Here, we apply machine learning approaches on the signatures to build a computational model capable of predicting zoonotic strains. The zoonotic strain prediction model can classify avian, human or zoonotic strains with high accuracy, as well as providing an estimated zoonotic risk. This would therefore allow us to quickly determine if an influenza virus strain has the potential to be zoonotic using only protein sequences. The swift identification of potential zoonotic strains in the animal population using the zoonotic strain prediction model could provide us with an early indication of an imminent influenza outbreak.

  16. Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest

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    Christine L. P. Eng

    2017-05-01

    Full Text Available Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understanding interspecies transmission of influenza viruses, we are no closer to predicting zoonotic strains that can lead to an outbreak. We have previously discovered distinct host tropism protein signatures of avian, human and zoonotic influenza strains obtained from host tropism predictions on individual protein sequences. Here, we apply machine learning approaches on the signatures to build a computational model capable of predicting zoonotic strains. The zoonotic strain prediction model can classify avian, human or zoonotic strains with high accuracy, as well as providing an estimated zoonotic risk. This would therefore allow us to quickly determine if an influenza virus strain has the potential to be zoonotic using only protein sequences. The swift identification of potential zoonotic strains in the animal population using the zoonotic strain prediction model could provide us with an early indication of an imminent influenza outbreak.

  17. RNA Sequencing Reveals that Kaposi Sarcoma-Associated Herpesvirus Infection Mimics Hypoxia Gene Expression Signature

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    Viollet, Coralie; Davis, David A.; Tekeste, Shewit S.; Reczko, Martin; Pezzella, Francesco; Ragoussis, Jiannis

    2017-01-01

    Kaposi sarcoma-associated herpesvirus (KSHV) causes several tumors and hyperproliferative disorders. Hypoxia and hypoxia-inducible factors (HIFs) activate latent and lytic KSHV genes, and several KSHV proteins increase the cellular levels of HIF. Here, we used RNA sequencing, qRT-PCR, Taqman assays, and pathway analysis to explore the miRNA and mRNA response of uninfected and KSHV-infected cells to hypoxia, to compare this with the genetic changes seen in chronic latent KSHV infection, and to explore the degree to which hypoxia and KSHV infection interact in modulating mRNA and miRNA expression. We found that the gene expression signatures for KSHV infection and hypoxia have a 34% overlap. Moreover, there were considerable similarities between the genes up-regulated by hypoxia in uninfected (SLK) and in KSHV-infected (SLKK) cells. hsa-miR-210, a HIF-target known to have pro-angiogenic and anti-apoptotic properties, was significantly up-regulated by both KSHV infection and hypoxia using Taqman assays. Interestingly, expression of KSHV-encoded miRNAs was not affected by hypoxia. These results demonstrate that KSHV harnesses a part of the hypoxic cellular response and that a substantial portion of hypoxia-induced changes in cellular gene expression are induced by KSHV infection. Therefore, targeting hypoxic pathways may be a useful way to develop therapeutic strategies for KSHV-related diseases. PMID:28046107

  18. Repeat Sequence Proteins as Matrices for Nanocomposites

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    Drummy, L.; Koerner, H; Phillips, D; McAuliffe, J; Kumar, M; Farmer, B; Vaia, R; Naik, R

    2009-01-01

    Recombinant protein-inorganic nanocomposites comprised of exfoliated Na+ montmorillonite (MMT) in a recombinant protein matrix based on silk-like and elastin-like amino acid motifs (silk elastin-like protein (SELP)) were formed via a solution blending process. Charged residues along the protein backbone are shown to dominate long-range interactions, whereas the SELP repeat sequence leads to local protein/MMT compatibility. Up to a 50% increase in room temperature modulus and a comparable decrease in high temperature coefficient of thermal expansion occur for cast films containing 2-10 wt.% MMT.

  19. A species-specific nucleosomal signature defines a periodic distribution of amino acids in proteins.

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    Quintales, Luis; Soriano, Ignacio; Vázquez, Enrique; Segurado, Mónica; Antequera, Francisco

    2015-04-01

    Nucleosomes are the basic structural units of chromatin. Most of the yeast genome is organized in a pattern of positioned nucleosomes that is stably maintained under a wide range of physiological conditions. In this work, we have searched for sequence determinants associated with positioned nucleosomes in four species of fission and budding yeasts. We show that mononucleosomal DNA follows a highly structured base composition pattern, which differs among species despite the high degree of histone conservation. These nucleosomal signatures are present in transcribed and non-transcribed regions across the genome. In the case of open reading frames, they correctly predict the relative distribution of codons on mononucleosomal DNA, and they also determine a periodicity in the average distribution of amino acids along the proteins. These results establish a direct and species-specific connection between the position of each codon around the histone octamer and protein composition.

  20. Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

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    Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

    2014-03-01

    Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

  1. Bromine isotopic signature facilitates de novo sequencing of peptides in free-radical-initiated peptide sequencing (FRIPS) mass spectrometry.

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    Nam, Jungjoo; Kwon, Hyuksu; Jang, Inae; Jeon, Aeran; Moon, Jingyu; Lee, Sun Young; Kang, Dukjin; Han, Sang Yun; Moon, Bongjin; Oh, Han Bin

    2015-02-01

    We recently showed that free-radical-initiated peptide sequencing mass spectrometry (FRIPS MS) assisted by the remarkable thermochemical stability of (2,2,6,6-tetramethyl-piperidin-1-yl)oxyl (TEMPO) is another attractive radical-driven peptide fragmentation MS tool. Facile homolytic cleavage of the bond between the benzylic carbon and the oxygen of the TEMPO moiety in o-TEMPO-Bz-C(O)-peptide and the high reactivity of the benzylic radical species generated in •Bz-C(O)-peptide are key elements leading to extensive radical-driven peptide backbone fragmentation. In the present study, we demonstrate that the incorporation of bromine into the benzene ring, i.e. o-TEMPO-Bz(Br)-C(O)-peptide, allows unambiguous distinction of the N-terminal peptide fragments from the C-terminal fragments through the unique bromine doublet isotopic signature. Furthermore, bromine substitution does not alter the overall radical-driven peptide backbone dissociation pathways of o-TEMPO-Bz-C(O)-peptide. From a practical perspective, the presence of the bromine isotopic signature in the N-terminal peptide fragments in TEMPO-assisted FRIPS MS represents a useful and cost-effective opportunity for de novo peptide sequencing. Copyright © 2015 John Wiley & Sons, Ltd.

  2. Scoring protein relationships in functional interaction networks predicted from sequence data.

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    Gaston K Mazandu

    Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

  3. CoverageAnalyzer (CAn: A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

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    Ralf Hauenschild

    2016-11-01

    Full Text Available Combination of reverse transcription (RT and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq data, up to sophisticated modification analysis with significance-based modification candidate calling.

  4. Generation of sequence signatures from DNA amplification fingerprints with mini-hairpin and microsatellite primers.

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    Caetano-Anollés, G; Gresshoff, P M

    1996-06-01

    DNA amplification fingerprinting (DAF) with mini-hairpins harboring arbitrary "core" sequences at their 3' termini were used to fingerprint a variety of templates, including PCR products and whole genomes, to establish genetic relationships between plant tax at the interspecific and intraspecific level, and to identify closely related fungal isolates and plant accessions. No correlation was observed between the sequence of the arbitrary core, the stability of the mini-hairpin structure and DAF efficiency. Mini-hairpin primers with short arbitrary cores and primers complementary to simple sequence repeats present in microsatellites were also used to generate arbitrary signatures from amplification profiles (ASAP). The ASAP strategy is a dual-step amplification procedure that uses at least one primer in each fingerprinting stage. ASAP was able to reproducibly amplify DAF products (representing about 10-15 kb of sequence) following careful optimization of amplification parameters such as primer and template concentration. Avoidance of primer sequences partially complementary to DAF product termini was necessary in order to produce distinct fingerprints. This allowed the combinatorial use of oligomers in nucleic acid screening, with numerous ASAP fingerprinting reactions based on a limited number of primer sequences. Mini-hairpin primers and ASAP analysis significantly increased detection of polymorphic DNA, separating closely related bermudagrass (Cynodon) cultivars and detecting putatively linked markers in bulked segregant analysis of the soybean (Glycine max) supernodulation (nitrate-tolerant symbiosis) locus.

  5. Nonlinear deterministic structures and the randomness of protein sequences

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    Huang Yan Zhao

    2003-01-01

    To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.

  6. A New Method to Represent Speech Signals Via Predefined Signature and Envelope Sequences

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    Binboga Sıddık Yarman

    2007-01-01

    Full Text Available A novel systematic procedure referred to as “SYMPES” to model speech signals is introduced. The structure of SYMPES is based on the creation of the so-called predefined “signature S={SR(n} and envelope E={EK(n}” sets. These sets are speaker and language independent. Once the speech signals are divided into frames with selected lengths, then each frame sequence Xi(n is reconstructed by means of the mathematical form Xi(n=CiEK(nSR(n. In this representation, Ci is called the gain factor, SR(n and EK(n are properly assigned from the predefined signature and envelope sets, respectively. Examples are given to exhibit the implementation of SYMPES. It is shown that for the same compression ratio or better, SYMPES yields considerably better speech quality over the commercially available coders such as G.726 (ADPCM at 16 kbps and voice excited LPC-10E (FS1015 at 2.4 kbps.

  7. Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

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    Zhou, Zhi; Cao, Zongjie; Pi, Yiming

    2017-12-21

    The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

  8. Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses.

    Science.gov (United States)

    Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

    2016-01-01

    Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.

  9. The SWISS-PROT protein sequence data bank: current status.

    OpenAIRE

    Bairoch, A; Boeckmann, B

    1994-01-01

    SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library. The SWISS-PROT protein sequence data bank consist of sequence entries. Sequence entries are composed of different lines types, each with their own format. For standardization purposes the format of SWISS-PROT follows as closely as possible that of the EMBL Nucleotide Sequence Databa...

  10. Unique Protein Signature of Circulating Microparticles in Systemic Lupus Erythematosus

    DEFF Research Database (Denmark)

    Østergaard, Ole; Nielsen, Christoffer; Iversen, Line V

    2013-01-01

    To characterize the unique qualities of proteins associated with circulating subcellular material in systemic lupus erythematosus (SLE) patients compared with healthy controls and patients with other chronic autoimmune diseases.......To characterize the unique qualities of proteins associated with circulating subcellular material in systemic lupus erythematosus (SLE) patients compared with healthy controls and patients with other chronic autoimmune diseases....

  11. Next-Generation Sequencing for Binary Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Bernhard eSuter

    2015-12-01

    Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

  12. Learning from soil gas change and isotopic signatures during 2012 Emilia seismic sequence.

    Science.gov (United States)

    Sciarra, Alessandra; Cantucci, Barbara; Coltorti, Massimo

    2017-10-27

    Soil surveys were performed in Medolla (Italy), a peculiar area characterized by spotty high soil temperature, gas vent, and lack of vegetation, to determine the migration mechanisms and spatial behavior of gas species. Hereby we present soil gas measurements and their isotopic ratios measured between 2008 and 2015, including the 2012 Emilia-Romagna seismic sequence. We found that soil gas concentrations markedly changed during the main shocks of May 20 and 29, 2012 (Mw 6.1 and 6.0, respectively), highlighting the presence of a buried fault intersecting the gas vents. We suggest that crustal dilation associated with seismic activity favored the uprising of geogas towards the surface. Changes in the isotopic signature highlight the contribution of two distinct sources, one deeper, thermogenic and another superficial related to organic-rich layer, whose relative contribution varied before, during and after the earthquake. We suppose an increase of microbial component likely due to the ground shaking of shallower layers linked to seismic sequence, which masks the thermogenic contribution. Although the changes we detect are specific for an alluvial plain, we deduce that analogous processes may be active elsewhere, and that soil gas geochemistry represents an useful tool to discriminate the gas migration related to seismic activity.

  13. Next generation sequencing reveals distinct fecal pollution signatures in aquatic sediments across gradients of anthropogenic influence

    Directory of Open Access Journals (Sweden)

    Gian Marco Luna

    2016-11-01

    Full Text Available Aquatic sediments are the repository of a variety of anthropogenic pollutants, including bacteria of fecal origin, that reach the aquatic environment from a variety of sources. Although fecal bacteria can survive for long periods of time in aquatic sediments, the microbiological quality of sediments is almost entirely neglected when performing quality assessments of aquatic ecosystems. Here we investigated the relative abundance, patterns and diversity of fecal bacterial populations in two coastal areas in the Northern Adriatic Sea (Italy: the Po river prodelta (PRP, an estuarine area receiving significant contaminant discharge from one of the largest European rivers and the Lagoon of Venice (LV, a transitional environment impacted by a multitude of anthropogenic stressors. From both areas, several indicators of fecal and sewage contamination were determined in the sediments using Next Generation Sequencing (NGS of 16S rDNA amplicons. At both areas, fecal contamination was high, with fecal bacteria accounting for up to 3.96% and 1.12% of the sediment bacterial assemblages in PRP and LV, respectively. The magnitude of the fecal signature was highest in the PRP site, highlighting the major role of the Po river in spreading microbial contaminants into the adjacent coastal area. In the LV site, fecal pollution was highest in the urban area, and almost disappeared when moving to the open sea. Our analysis revealed a large number of fecal Operational Taxonomic Units (OTU, 960 and 181 in PRP and LV, respectively and showed a different fecal signature in the two areas, suggesting a diverse contribution of human and non-human sources of contamination. These results highlight the potential of NGS techniques to gain insights into the origin and fate of different fecal bacteria populations in aquatic sediments.

  14. Simple sequence proteins in prokaryotic proteomes

    Directory of Open Access Journals (Sweden)

    Ramachandran Srinivasan

    2006-06-01

    Full Text Available Abstract Background The structural and functional features associated with Simple Sequence Proteins (SSPs are non-globularity, disease states, signaling and post-translational modification. SSPs are also an important source of genetic and possibly phenotypic variation. Analysis of 249 prokaryotic proteomes offers a new opportunity to examine the genomic properties of SSPs. Results SSPs are a minority but they grow with proteome size. This relationship is exhibited across species varying in genomic GC, mutational bias, life style, and pathogenicity. Their proportion in each proteome is strongly influenced by genomic base compositional bias. In most species simple duplications is favoured, but in a few cases such as Mycobacteria, large families of duplications occur. Amino acid preference in SSPs exhibits a trend towards low cost of biosynthesis. In SSPs and in non-SSPs, Alanine, Glycine, Leucine, and Valine are abundant in species widely varying in genomic GC whereas Isoleucine and Lysine are rich only in organisms with low genomic GC. Arginine is abundant in SSPs of two species and in the non-SSPs of Xanthomonas oryzae. Asparagine is abundant only in SSPs of low GC species. Aspartic acid is abundant only in the non-SSPs of Halobacterium sp NRC1. The abundance of Serine in SSPs of 62 species extends over a broader range compared to that of non-SSPs. Threonine(T is abundant only in SSPs of a couple of species. SSPs exhibit preferential association with Cell surface, Cell membrane and Transport functions and a negative association with Metabolism. Mesophiles and Thermophiles display similar ranges in the content of SSPs. Conclusion Although SSPs are a minority, the genomic forces of base compositional bias and duplications influence their growth and pattern in each species. The preferences and abundance of amino acids are governed by low biosynthetic cost, evolutionary age and base composition of codons. Abundance of charged amino acids Arginine

  15. Genetic signatures of adaptation revealed from transcriptome sequencing of Arctic and red foxes.

    Science.gov (United States)

    Kumar, Vikas; Kutschera, Verena E; Nilsson, Maria A; Janke, Axel

    2015-08-07

    The genus Vulpes (true foxes) comprises numerous species that inhabit a wide range of habitats and climatic conditions, including one species, the Arctic fox (Vulpes lagopus) which is adapted to the arctic region. A close relative to the Arctic fox, the red fox (Vulpes vulpes), occurs in subarctic to subtropical habitats. To study the genetic basis of their adaptations to different environments, transcriptome sequences from two Arctic foxes and one red fox individual were generated and analyzed for signatures of positive selection. In addition, the data allowed for a phylogenetic analysis and divergence time estimate between the two fox species. The de novo assembly of reads resulted in more than 160,000 contigs/transcripts per individual. Approximately 17,000 homologous genes were identified using human and the non-redundant databases. Positive selection analyses revealed several genes involved in various metabolic and molecular processes such as energy metabolism, cardiac gene regulation, apoptosis and blood coagulation to be under positive selection in foxes. Branch site tests identified four genes to be under positive selection in the Arctic fox transcriptome, two of which are fat metabolism genes. In the red fox transcriptome eight genes are under positive selection, including molecular process genes, notably genes involved in ATP metabolism. Analysis of the three transcriptomes and five Sanger re-sequenced genes in additional individuals identified a lower genetic variability within Arctic foxes compared to red foxes, which is consistent with distribution range differences and demographic responses to past climatic fluctuations. A phylogenomic analysis estimated that the Arctic and red fox lineages diverged about three million years ago. Transcriptome data are an economic way to generate genomic resources for evolutionary studies. Despite not representing an entire genome, this transcriptome analysis identified numerous genes that are relevant to arctic

  16. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-01-01

    operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching

  17. Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma.

    Directory of Open Access Journals (Sweden)

    Biaoyang Lin

    Full Text Available BACKGROUND: A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM is essential for developing effective therapeutic approaches for this deadly disease. METHODOLOGY/PRINCIPAL FINDINGS: Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS, we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- beta pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF beta signaling network identified two alternative TGF-beta signaling pathways mediated by SOX4 (sex determining region Y-box 4 and TGFBI (Transforming growth factor beta induced. Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF-beta stimulation and decreased by a specific inhibitor of TGF-beta receptor 1 kinase. CONCLUSIONS/SIGNIFICANCE: Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF-beta signaling pathways acting through SOX4 and TGFBI (GENE ID:7045 in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF-beta signaling in GBM. Finally, the construction of an extended TGF-beta signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.

  18. Use of designed sequences in protein structure recognition.

    Science.gov (United States)

    Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

    2018-05-09

    Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

  19. Partial sequence determination of metabolically labeled radioactive proteins and peptides

    International Nuclear Information System (INIS)

    Anderson, C.W.

    1982-01-01

    The author has used the sequence analysis of radioactive proteins and peptides to approach several problems during the past few years. They, in collaboration with others, have mapped precisely several adenovirus proteins with respect to the nucleotide sequence of the adenovirus genome; identified hitherto missed proteins encoded by bacteriophage MS2 and by simian virus 40; analyzed the aminoterminal maturation of several virus proteins; determined the cleavage sites for processing of the poliovirus polyprotein; and analyzed the mechanism of frameshifting by excess normal tRNAs during cell-free protein synthesis. This chapter is designed to aid those without prior experience at protein sequence determinations. It is based primarily on the experience gained in the studies cited above, which made use of the Beckman 890 series automated protein sequencers

  20. Complete cDNA sequence coding for human docking protein

    Energy Technology Data Exchange (ETDEWEB)

    Hortsch, M; Labeit, S; Meyer, D I

    1988-01-11

    Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.

  1. AlignMe—a membrane protein sequence alignment web server

    Science.gov (United States)

    Stamm, Marcus; Staritzbichler, René; Khafizov, Kamil; Forrest, Lucy R.

    2014-01-01

    We present a web server for pair-wise alignment of membrane protein sequences, using the program AlignMe. The server makes available two operational modes of AlignMe: (i) sequence to sequence alignment, taking two sequences in fasta format as input, combining information about each sequence from multiple sources and producing a pair-wise alignment (PW mode); and (ii) alignment of two multiple sequence alignments to create family-averaged hydropathy profile alignments (HP mode). For the PW sequence alignment mode, four different optimized parameter sets are provided, each suited to pairs of sequences with a specific similarity level. These settings utilize different types of inputs: (position-specific) substitution matrices, secondary structure predictions and transmembrane propensities from transmembrane predictions or hydrophobicity scales. In the second (HP) mode, each input multiple sequence alignment is converted into a hydrophobicity profile averaged over the provided set of sequence homologs; the two profiles are then aligned. The HP mode enables qualitative comparison of transmembrane topologies (and therefore potentially of 3D folds) of two membrane proteins, which can be useful if the proteins have low sequence similarity. In summary, the AlignMe web server provides user-friendly access to a set of tools for analysis and comparison of membrane protein sequences. Access is available at http://www.bioinfo.mpg.de/AlignMe PMID:24753425

  2. MIPS: a database for protein sequences and complete genomes.

    Science.gov (United States)

    Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D

    1998-01-01

    The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795

  3. A proteomics analysis for certain signature proteins of rabbit lacrimal passages after 125I seeds brachytherapy

    International Nuclear Information System (INIS)

    Li Dandan; Liu Lin; Gao Shi; Qi Liangchen; Ma Qingjie; Jin Longyun

    2010-01-01

    To search for certain signature proteins and the expression profiles in lacrimal passage stenosis, rabbit models of lacrimal passage stenosis were treated by 125 I seed brachytherapy. All the signature proteins were separated by two-dimensional electrophoresis, and identified by mass spectrometry. The results show that the up-regulated proteins are peptidyl-prolyl cis-trans isomerase A (PPIase A), and epidermal fatty acid-binding protein (E-FABP), while the down-regulated proteins are myosin light chain 1 (isomer of skeletal muscle), myosin light polypeptide 6 (isomer 1 of smooth muscle and non-muscle), myosin light chain 1 (isomer of slow-twitch muscle A), isomer 2 of ERC protein 2, and α-crystalline family protein. The proteins may play a role in healing the wound and regulating synaptic active zone of neurons due to correlation to cell apoptosis, proliferation and migration of smooth muscle cell. These provide molecular mechanism for preventing stenosis and restenosis of lacrimal passage. (authors)

  4. Dynamics of domain coverage of the protein sequence universe

    Science.gov (United States)

    2012-01-01

    Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data. PMID:23157439

  5. Dynamics of domain coverage of the protein sequence universe

    Directory of Open Access Journals (Sweden)

    Rekapalli Bhanu

    2012-11-01

    Full Text Available Abstract Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data.

  6. Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Sara Garamszegi

    Full Text Available A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1 domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2 domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral

  7. Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

    Science.gov (United States)

    Garamszegi, Sara; Franzosa, Eric A; Xia, Yu

    2013-01-01

    A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are

  8. Development of multigene expression signature maps at the protein level from digitized immunohistochemistry slides.

    Directory of Open Access Journals (Sweden)

    Gregory J Metzger

    Full Text Available Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions.

  9. Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-10-01

    Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.

  10. Nonlinear analysis of sequence repeats of multi-domain proteins

    Energy Technology Data Exchange (ETDEWEB)

    Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: lmf_bill@sina.com

    2007-11-15

    Many multi-domain proteins have repetitive three-dimensional structures but nearly-random amino acid sequences. In the present paper, by using a modified recurrence plot proposed by us previously, we show that these amino acid sequences have hidden repetitions in fact. These results indicate that the repetitive domain structures are encoded by the repetitive sequences. This also gives a method to detect the repetitive domain structures directly from amino acid sequences.

  11. Interim Report on Multiple Sequence Alignments and TaqMan Signature Mapping to Phylogenetic Trees

    Energy Technology Data Exchange (ETDEWEB)

    Gardner, S; Jaing, C

    2012-03-27

    The goal of this project is to develop forensic genotyping assays for select agent viruses, addressing a significant capability gap for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the Taqman signature development for South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.

  12. An algorithm to find all palindromic sequences in proteins

    Indian Academy of Sciences (India)

    2013-01-20

    Jan 20, 2013 ... 1976; Karrer and Gall 1976; Vogt and Braun 1976) and (iii) in the formation of hairpin loops in the newly transcribed RNA. Palindromic sequences are observed in various classes of proteins like histones (Cheng et al. 1989), prion proteins (Sulkowski 1992; Kazim 1993),. DNA-binding proteins (Suzuki 1992; ...

  13. Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning

    NARCIS (Netherlands)

    Shahib, Ali Al-; Gilbert, David; Breitling, Rainer

    2007-01-01

    Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this

  14. Penicillin-Binding Protein Transpeptidase Signatures for Tracking and Predicting β-Lactam Resistance Levels in Streptococcus pneumoniae

    Directory of Open Access Journals (Sweden)

    Yuan Li

    2016-06-01

    Full Text Available β-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of β-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking β-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a “PBP type” based on sequence signatures in the transpeptidase domains (TPDs of the three critical penicillin-binding proteins (PBPs, PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six β-lactams based on broth microdilution. We found that increased β-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to β-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution of >98%, category agreement (interpretive results agree of >94%, a major discrepancy (sensitive isolate predicted as resistant rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive rate of <2% for all six β-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different β-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing.

  15. The relationship of protein conservation and sequence length

    Directory of Open Access Journals (Sweden)

    Panchenko Anna R

    2002-11-01

    Full Text Available Abstract Background In general, the length of a protein sequence is determined by its function and the wide variance in the lengths of an organism's proteins reflects the diversity of specific functional roles for these proteins. However, additional evolutionary forces that affect the length of a protein may be revealed by studying the length distributions of proteins evolving under weaker functional constraints. Results We performed sequence comparisons to distinguish highly conserved and poorly conserved proteins from the bacterium Escherichia coli, the archaeon Archaeoglobus fulgidus, and the eukaryotes Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. For all organisms studied, the conserved and nonconserved proteins have strikingly different length distributions. The conserved proteins are, on average, longer than the poorly conserved ones, and the length distributions for the poorly conserved proteins have a relatively narrow peak, in contrast to the conserved proteins whose lengths spread over a wider range of values. For the two prokaryotes studied, the poorly conserved proteins approximate the minimal length distribution expected for a diverse range of structural folds. Conclusions There is a relationship between protein conservation and sequence length. For all the organisms studied, there seems to be a significant evolutionary trend favoring shorter proteins in the absence of other, more specific functional constraints.

  16. Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

    KAUST Repository

    Zhang, Zhang; Yu, Jun

    2010-01-01

    Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.

  17. Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

    KAUST Repository

    Zhang, Zhang

    2010-11-08

    Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.

  18. Inverse statistical physics of protein sequences: a key issues review.

    Science.gov (United States)

    Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

    2018-03-01

    In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

  19. The SWISS-PROT protein sequence data bank

    OpenAIRE

    Bairoch, Amos; Boeckmann, Brigitte

    1992-01-01

    SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library

  20. Aligning protein sequence and analysing substitution pattern using ...

    Indian Academy of Sciences (India)

    Prakash

    Aligning protein sequences using a score matrix has became a routine but valuable method in modern biological ..... the amino acids according to their substitution behaviour ...... which may cause great change (e.g. prolonging the helix) in.

  1. Formatt: Correcting protein multiple structural alignments by incorporating sequence alignment

    Directory of Open Access Journals (Sweden)

    Daniels Noah M

    2012-10-01

    Full Text Available Abstract Background The quality of multiple protein structure alignments are usually computed and assessed based on geometric functions of the coordinates of the backbone atoms from the protein chains. These purely geometric methods do not utilize directly protein sequence similarity, and in fact, determining the proper way to incorporate sequence similarity measures into the construction and assessment of protein multiple structure alignments has proved surprisingly difficult. Results We present Formatt, a multiple structure alignment based on the Matt purely geometric multiple structure alignment program, that also takes into account sequence similarity when constructing alignments. We show that Formatt outperforms Matt and other popular structure alignment programs on the popular HOMSTRAD benchmark. For the SABMark twilight zone benchmark set that captures more remote homology, Formatt and Matt outperform other programs; depending on choice of embedded sequence aligner, Formatt produces either better sequence and structural alignments with a smaller core size than Matt, or similarly sized alignments with better sequence similarity, for a small cost in average RMSD. Conclusions Considering sequence information as well as purely geometric information seems to improve quality of multiple structure alignments, though defining what constitutes the best alignment when sequence and structural measures would suggest different alignments remains a difficult open question.

  2. Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

    Science.gov (United States)

    Borrebaeck, Carl A K

    2017-03-01

    Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

  3. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

    The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

  4. Protein 3D structure computed from evolutionary sequence variation.

    Directory of Open Access Journals (Sweden)

    Debora S Marks

    Full Text Available The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing.In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy.We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues, including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7-4.8 Å C(α-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org. This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of

  5. Phylogeny and molecular signatures (conserved proteins and indels that are specific for the Bacteroidetes and Chlorobi species

    Directory of Open Access Journals (Sweden)

    Lorenzini Emily

    2007-05-01

    reported based on concatenated sequences for 12 conserved proteins by different methods including the character compatibility (or clique approach. The placement of Salinibacter ruber with other Bacteroidetes species was not resolved by other phylogenetic methods, but this affiliation was strongly supported by the character compatibility approach. Conclusion The molecular signatures described here provide novel tools for identifying and circumscribing species from the Bacteroidetes and Chlorobi phyla as well as some of their main groups in clear terms. These results also provide strong evidence that species from these two phyla (and also possibly Fibrobacteres are specifically related to each other and they form a single superphylum. Functional studies on these proteins and indels should aid in the discovery of novel biochemical and physiological characteristics that are unique to these groups of bacteria.

  6. Quantiprot - a Python package for quantitative analysis of protein sequences.

    Science.gov (United States)

    Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

    2017-07-17

    The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

  7. Taxonomic colouring of phylogenetic trees of protein sequences

    Directory of Open Access Journals (Sweden)

    Andrade-Navarro Miguel A

    2006-02-01

    Full Text Available Abstract Background Phylogenetic analyses of protein families are used to define the evolutionary relationships between homologous proteins. The interpretation of protein-sequence phylogenetic trees requires the examination of the taxonomic properties of the species associated to those sequences. However, there is no online tool to facilitate this interpretation, for example, by automatically attaching taxonomic information to the nodes of a tree, or by interactively colouring the branches of a tree according to any combination of taxonomic divisions. This is especially problematic if the tree contains on the order of hundreds of sequences, which, given the accelerated increase in the size of the protein sequence databases, is a situation that is becoming common. Results We have developed PhyloView, a web based tool for colouring phylogenetic trees upon arbitrary taxonomic properties of the species represented in a protein sequence phylogenetic tree. Provided that the tree contains SwissProt, SpTrembl, or GenBank protein identifiers, the tool retrieves the taxonomic information from the corresponding database. A colour picker displays a summary of the findings and allows the user to associate colours to the leaves of the tree according to any number of taxonomic partitions. Then, the colours are propagated to the branches of the tree. Conclusion PhyloView can be used at http://www.ogic.ca/projects/phyloview/. A tutorial, the software with documentation, and GPL licensed source code, can be accessed at the same web address.

  8. MIPS: a database for genomes and protein sequences.

    Science.gov (United States)

    Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

    2002-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

  9. Quantitative Evaluation of Serum Proteins Uncovers a Protein Signature Related to Maturity-Onset Diabetes of the Young (MODY).

    Science.gov (United States)

    Tuerxunyiming, Muhadasi; Xian, Feng; Zi, Jin; Yimamu, Yilihamujiang; Abuduwayite, Reshalaiti; Ren, Yan; Li, Qidan; Abudula, Abulizi; Liu, SiQi; Mohemaiti, Patamu

    2018-01-05

    Maturity-onset diabetes of the young (MODY) is an inherited monogenic type of diabetes. Genetic mutations in MODY often cause nonsynonymous changes that directly lead to the functional distortion of proteins and the pathological consequences. Herein, we proposed that the inherited mutations found in a MODY family could cause a disturbance of protein abundance, specifically in serum. The serum samples were collected from a Uyghur MODY family through three generations, and the serum proteins after depletion treatment were examined by quantitative proteomics to characterize the MODY-related serum proteins followed by verification using target quantification of proteomics. A total of 32 serum proteins were preliminarily identified as the MODY-related. Further verification test toward the individual samples demonstrated the 12 candidates with the significantly different abundance in the MODY patients. A comparison of the 12 proteins among the sera of type 1 diabetes, type 2 diabetes, MODY, and healthy subjects was conducted and revealed a protein signature related with MODY composed of the serum proteins such as SERPINA7, APOC4, LPA, C6, and F5.

  10. High-resolution characterization of sequence signatures due to non-random cleavage of cell-free DNA.

    Science.gov (United States)

    Chandrananda, Dineika; Thorne, Natalie P; Bahlo, Melanie

    2015-06-17

    High-throughput sequencing of cell-free DNA fragments found in human plasma has been used to non-invasively detect fetal aneuploidy, monitor organ transplants and investigate tumor DNA. However, many biological properties of this extracellular genetic material remain unknown. Research that further characterizes circulating DNA could substantially increase its diagnostic value by allowing the application of more sophisticated bioinformatics tools that lead to an improved signal to noise ratio in the sequencing data. In this study, we investigate various features of cell-free DNA in plasma using deep-sequencing data from two pregnant women (>70X, >50X) and compare them with matched cellular DNA. We utilize a descriptive approach to examine how the biological cleavage of cell-free DNA affects different sequence signatures such as fragment lengths, sequence motifs at fragment ends and the distribution of cleavage sites along the genome. We show that the size distributions of these cell-free DNA molecules are dependent on their autosomal and mitochondrial origin as well as the genomic location within chromosomes. DNA mapping to particular microsatellites and alpha repeat elements display unique size signatures. We show how cell-free fragments occur in clusters along the genome, localizing to nucleosomal arrays and are preferentially cleaved at linker regions by correlating the mapping locations of these fragments with ENCODE annotation of chromatin organization. Our work further demonstrates that cell-free autosomal DNA cleavage is sequence dependent. The region spanning up to 10 positions on either side of the DNA cleavage site show a consistent pattern of preference for specific nucleotides. This sequence motif is present in cleavage sites localized to nucleosomal cores and linker regions but is absent in nucleosome-free mitochondrial DNA. These background signals in cell-free DNA sequencing data stem from the non-random biological cleavage of these fragments. This

  11. Correlation between protein sequence similarity and x-ray diffraction quality in the protein data bank.

    Science.gov (United States)

    Lu, Hui-Meng; Yin, Da-Chuan; Ye, Ya-Jing; Luo, Hui-Min; Geng, Li-Qiang; Li, Hai-Sheng; Guo, Wei-Hong; Shang, Peng

    2009-01-01

    As the most widely utilized technique to determine the 3-dimensional structure of protein molecules, X-ray crystallography can provide structure of the highest resolution among the developed techniques. The resolution obtained via X-ray crystallography is known to be influenced by many factors, such as the crystal quality, diffraction techniques, and X-ray sources, etc. In this paper, the authors found that the protein sequence could also be one of the factors. We extracted information of the resolution and the sequence of proteins from the Protein Data Bank (PDB), classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the best resolution obtained. The results showed that there was a pronounced correlation between the sequence similarity and the obtained resolution. These results indicate that protein structure itself is one variable that may affect resolution when X-ray crystallography is used.

  12. Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.

    Directory of Open Access Journals (Sweden)

    Matthew R Mason

    Full Text Available Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual's ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.

  13. Can Natural Proteins Designed with ‘Inverted’ Peptide Sequences Adopt Native-Like Protein Folds?

    Science.gov (United States)

    Sridhar, Settu; Guruprasad, Kunchur

    2014-01-01

    We have carried out a systematic computational analysis on a representative dataset of proteins of known three-dimensional structure, in order to evaluate whether it would possible to ‘swap’ certain short peptide sequences in naturally occurring proteins with their corresponding ‘inverted’ peptides and generate ‘artificial’ proteins that are predicted to retain native-like protein fold. The analysis of 3,967 representative proteins from the Protein Data Bank revealed 102,677 unique identical inverted peptide sequence pairs that vary in sequence length between 5–12 and 18 amino acid residues. Our analysis illustrates with examples that such ‘artificial’ proteins may be generated by identifying peptides with ‘similar structural environment’ and by using comparative protein modeling and validation studies. Our analysis suggests that natural proteins may be tolerant to accommodating such peptides. PMID:25210740

  14. Correlated mutations in protein sequences: Phylogenetic and structural effects

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.S. [Los Alamos National Lab., NM (United States). Theoretical Div.]|[Santa Fe Inst., NM (United States); Giraud, B.G. [C.E.N. Saclay, Gif/Yvette (France). Service Physique Theorique; Liu, L.C. [Los Alamos National Lab., NM (United States). Theoretical Div.; Stormo, G.D. [Univ. of Colorado, Boulder, CO (United States). Dept. of Molecular, Cellular and Developmental Biology

    1998-12-01

    Covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. Covariation analysis of sets of aligned sequences for protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In this paper the authors identify two reasons why naive use of covariation analysis for protein sequences fails to reliably indicate sequence positions that are spatially proximate. The first reason involves the bias introduced in calculation of covariation measures due to the fact that biological sequences are generally related by a non-trivial phylogenetic tree. The authors present a null-model approach to solve this problem. The second reason involves linked chains of covariation which can result in pairs of sites displaying significant covariation even though they are not spatially proximate. They present a maximum entropy solution to this classic problem of causation versus correlation. The methodologies are validated in simulation.

  15. Semi-Supervised Learning for Classification of Protein Sequence Data

    Directory of Open Access Journals (Sweden)

    Brian R. King

    2008-01-01

    Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.

  16. Single-molecule protein sequencing through fingerprinting: computational assessment

    Science.gov (United States)

    Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

    2015-10-01

    Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.

  17. Single-molecule protein sequencing through fingerprinting: computational assessment

    International Nuclear Information System (INIS)

    Yao, Yao; Docter, Margreet; Van Ginkel, Jetty; Joo, Chirlmin; De Ridder, Dick

    2015-01-01

    Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences. (paper)

  18. Deep sequencing methods for protein engineering and design.

    Science.gov (United States)

    Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

    2017-08-01

    The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Sequence analysis reveals how G protein-coupled receptors transduce the signal to the G protein.

    NARCIS (Netherlands)

    Oliveira, L.; Paiva, P.B.; Paiva, A.C.; Vriend, G.

    2003-01-01

    Sequence entropy-variability plots based on alignments of very large numbers of sequences-can indicate the location in proteins of the main active site and modulator sites. In the previous article in this issue, we applied this observation to a series of well-studied proteins and concluded that it

  20. POST-MERGER SIGNATURES OF RED-SEQUENCE GALAXIES IN RICH ABELL CLUSTERS AT z ∼< 0.1

    International Nuclear Information System (INIS)

    Sheen, Yun-Kyeong; Yi, Sukyoung K.; Lee, Jaehyun; Ree, Chang H.

    2012-01-01

    We have investigated the post-merger signatures of red-sequence galaxies in rich Abell clusters at z ∼ r < –20) cluster red-sequence galaxies show post-merger signatures in four clusters consistently. Most (∼71%) of the featured galaxies were found to be bulge dominated, and for the subsample of bulge-dominated red-sequence galaxies, the post-merger fraction rises to ∼38%. We also found that roughly 4% of bulge-dominated red-sequence galaxies interact (ongoing merger). A total of 42% (38% post-merger, 4% ongoing merger) of galaxies show merger-related features. Compared to a field galaxy study with a similar limiting magnitude by van Dokkum in 2005, our cluster study presents a similar post-merger fraction but a markedly lower ongoing merger fraction. The merger fraction derived is surprisingly high for the high density of our clusters, where the fast internal motions of galaxies are thought to play a negative role in galaxy mergers. The fraction of post-merger and ongoing merger galaxies can be explained as follows. Most of the post-merger galaxies may have carried over their merger features from their previous halo environment, whereas interacting galaxies interact in the current cluster in situ. According to our semi-analytic calculation, massive cluster halos may very well have experienced tens of halo mergers over the last 4-5 Gyr; post-merger features last that long, allowing these features to be detected in our clusters today. The apparent lack of dependence of the merger fraction on the clustocentric distance is naturally explained this way. In this scenario, the galaxy morphology and properties can be properly interpreted only when the halo evolution characteristics are understood first.

  1. Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

    Science.gov (United States)

    Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

    2016-11-23

    The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

  2. Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

    International Nuclear Information System (INIS)

    Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

    2014-01-01

    Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

  3. Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

    Energy Technology Data Exchange (ETDEWEB)

    Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun, E-mail: jianjunq@tju.edu.cn; Zhang, Weiwen, E-mail: jianjunq@tju.edu.cn [Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin (China); Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin (China); SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering, Tianjin (China)

    2014-11-03

    Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

  4. Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Martín Gómez Ravetti

    Full Text Available BACKGROUND: Alzheimer's disease (AD is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer's is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1alpha, IL-3, EGF, TNF-alpha and G-CSF. METHODOLOGY/PRINCIPAL FINDINGS: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a abundance quantization, b feature selection, c literature analysis, d selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani's discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. CONCLUSIONS/SIGNIFICANCE: the previous study has provided an extremely

  5. Origin and spread of photosynthesis based upon conserved sequence features in key bacteriochlorophyll biosynthesis proteins.

    Science.gov (United States)

    Gupta, Radhey S

    2012-11-01

    The origin of photosynthesis and how this capability has spread to other bacterial phyla remain important unresolved questions. I describe here a number of conserved signature indels (CSIs) in key proteins involved in bacteriochlorophyll (Bchl) biosynthesis that provide important insights in these regards. The proteins BchL and BchX, which are essential for Bchl biosynthesis, are derived by gene duplication in a common ancestor of all phototrophs. More ancient gene duplication gave rise to the BchX-BchL proteins and the NifH protein of the nitrogenase complex. The sequence alignment of NifH-BchX-BchL proteins contain two CSIs that are uniquely shared by all NifH and BchX homologs, but not by any BchL homologs. These CSIs and phylogenetic analysis of NifH-BchX-BchL protein sequences strongly suggest that the BchX homologs are ancestral to BchL and that the Bchl-based anoxygenic photosynthesis originated prior to the chlorophyll (Chl)-based photosynthesis in cyanobacteria. Another CSI in the BchX-BchL sequence alignment that is uniquely shared by all BchX homologs and the BchL sequences from Heliobacteriaceae, but absent in all other BchL homologs, suggests that the BchL homologs from Heliobacteriaceae are primitive in comparison to all other photosynthetic lineages. Several other identified CSIs in the BchN homologs are commonly shared by all proteobacterial homologs and a clade consisting of the marine unicellular Cyanobacteria (Clade C). These CSIs in conjunction with the results of phylogenetic analyses and pair-wise sequence similarity on the BchL, BchN, and BchB proteins, where the homologs from Clade C Cyanobacteria and Proteobacteria exhibited close relationship, provide strong evidence that these two groups have incurred lateral gene transfers. Additionally, phylogenetic analyses and several CSIs in the BchL-N-B proteins that are uniquely shared by all Chlorobi and Chloroflexi homologs provide evidence that the genes for these proteins have also been

  6. Methods of Generating Key Sequences Based on Parameters of Handwritten Passwords and Signatures

    Directory of Open Access Journals (Sweden)

    Pavel Lozhnikov

    2016-10-01

    Full Text Available The modern encryption methods are reliable if strong keys (passwords are used, but the human factor issue cannot be solved by cryptographic methods. The best variant is binding all authenticators (passwords, encryption keys, and others to the identities. When a user is authenticated by biometrical characteristics, the problem of protecting a biometrical template stored on a remote server becomes a concern. The paper proposes several methods of generating keys (passwords by means of the fuzzy extractors method based on signature parameters without storing templates in an open way.

  7. Structure and Sequence Search on Aptamer-Protein Docking

    Science.gov (United States)

    Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

    2015-03-01

    Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.

  8. Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System

    Directory of Open Access Journals (Sweden)

    Jinjian Jiang

    2017-07-01

    Full Text Available Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences. Moreover, almost all of the predictors identified hotspots from the interfaces of protein complexes, seldom from the whole protein sequences. Therefore, determining hotspots from whole protein sequences by sequence information alone is urgent. To address the issue of hotspot predictions from the whole sequences of proteins, we proposed an ensemble system with random projections using statistical physicochemical properties of amino acids. First, an encoding scheme involving sequence profiles of residues and physicochemical properties from the AAindex1 dataset is developed. Then, the random projection technique was adopted to project the encoding instances into a reduced space. Then, several better random projections were obtained by training an IBk classifier based on the training dataset, which were thus applied to the test dataset. The ensemble of random projection classifiers is therefore obtained. Experimental results showed that although the performance of our method is not good enough for real applications of hotspots, it is very promising in the determination of hotspot residues from whole sequences.

  9. Proteoform profiling of peripheral blood serum proteins from pregnant women provides a molecular IUGR signature.

    Science.gov (United States)

    Wölter, M; Röwer, C; Koy, C; Rath, W; Pecks, U; Glocker, M O

    2016-10-21

    Intrauterine growth restriction (IUGR) is an important cause of perinatal morbidity and mortality and contributes substantially to medically indicated preterm birth; preventing fetal death. Molecular profiling of the mothers' peripheral blood was desired to monitor the health conditions of the fetuses. To develop such a minimally invasive assay, we applied a protein affinity fractionation method to peripheral blood serum samples from pregnant women belonging to either the IUGR or to the control group. Proof-of-principle was shown by relative quantitation analysis of mixtures of intact proteoforms using MALDI-ToF mass spectrometry. The two best differentiating proteins and proteoforms, respectively, were apolipoprotein C-II and apolipoprotein C-III 0 . Together with three robustly expressed protein proteoforms proapolipoprotein C-II, apolipoprotein C-III 1 , and apolipoprotein C-III 2 , which served as landmarks for relative quantitation analysis, they constituted the maternal IUGR proteome signature. Separation confidence of our IUGR proteoform signature reached a sensitivity of 0.73 and a specificity of 0.87 with an area under curve of 0.86 in receiver operator characteristics. Identification of IUGR newborns in the case room is required as children are severely diseased and need specialized care during infancy. Yet, at time of birth there is no readily applicable clinical test available. Hence, a molecular profiling assay is highly desired. It needs to be mentioned that current clinical definitions and recommendations for IUGR are unfortunately misleading and are not universally applicable. The most commonly adopted definition is an abdominal circumference (AC) or estimated fetal weight measurement protein composition (IUGR signature) which can be determined just ahead of delivery and at date of delivery, respectively using a minimal invasive blood sampling approach. With this manuscript we describe the use of a mass spectrometric profiling method of 30

  10. Osteocalcin protein sequences of Neanderthals and modern primates.

    Science.gov (United States)

    Nielsen-Marsh, Christina M; Richards, Michael P; Hauschka, Peter V; Thomas-Oates, Jane E; Trinkaus, Erik; Pettitt, Paul B; Karavanic, Ivor; Poinar, Hendrik; Collins, Matthew J

    2005-03-22

    We report here protein sequences of fossil hominids, from two Neanderthals dating to approximately 75,000 years old from Shanidar Cave in Iraq. These sequences, the oldest reported fossil primate protein sequences, are of bone osteocalcin, which was extracted and sequenced by using MALDI-TOF/TOF mass spectrometry. Through a combination of direct sequencing and peptide mass mapping, we determined that Neanderthals have an osteocalcin amino acid sequence that is identical to that of modern humans. We also report complete osteocalcin sequences for chimpanzee (Pan troglodytes) and gorilla (Gorilla gorilla gorilla) and a partial sequence for orangutan (Pongo pygmaeus), all of which are previously unreported. We found that the osteocalcin sequences of Neanderthals, modern human, chimpanzee, and orangutan are unusual among mammals in that the ninth amino acid is proline (Pro-9), whereas most species have hydroxyproline (Hyp-9). Posttranslational hydroxylation of Pro-9 in osteocalcin by prolyl-4-hydroxylase requires adequate concentrations of vitamin C (l-ascorbic acid), molecular O(2), Fe(2+), and 2-oxoglutarate, and also depends on enzyme recognition of the target proline substrate consensus sequence Leu-Gly-Ala-Pro-9-Ala-Pro-Tyr occurring in most mammals. In five species with Pro-9-Val-10, hydroxylation is blocked, whereas in gorilla there is a mixture of Pro-9 and Hyp-9. We suggest that the absence of hydroxylation of Pro-9 in Pan, Pongo, and Homo may reflect response to a selective pressure related to a decline in vitamin C in the diet during omnivorous dietary adaptation, either independently or through the common ancestor of these species.

  11. Experimental Rugged Fitness Landscape in Protein Sequence Space

    OpenAIRE

    HAYASHI, Yuuki; 相田, 拓洋; TOYOTA, Hitoshi; 伏見, 譲; URABE, Itaru; YOMO, Tetsuya

    2006-01-01

    The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phag...

  12. Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

    Directory of Open Access Journals (Sweden)

    Perry Evans

    Full Text Available Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs. MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.

  13. EST2Prot: Mapping EST sequences to proteins

    Directory of Open Access Journals (Sweden)

    Lin David M

    2006-03-01

    Full Text Available Abstract Background EST libraries are used in various biological studies, from microarray experiments to proteomic and genetic screens. These libraries usually contain many uncharacterized ESTs that are typically ignored since they cannot be mapped to known genes. Consequently, new discoveries are possibly overlooked. Results We describe a system (EST2Prot that uses multiple elements to map EST sequences to their corresponding protein products. EST2Prot uses UniGene clusters, substring analysis, information about protein coding regions in existing DNA sequences and protein database searches to detect protein products related to a query EST sequence. Gene Ontology terms, Swiss-Prot keywords, and protein similarity data are used to map the ESTs to functional descriptors. Conclusion EST2Prot extends and significantly enriches the popular UniGene mapping by utilizing multiple relations between known biological entities. It produces a mapping between ESTs and proteins in real-time through a simple web-interface. The system is part of the Biozon database and is accessible at http://biozon.org/tools/est/.

  14. HomPPI: a class of sequence homology based protein-protein interface prediction methods

    Directory of Open Access Journals (Sweden)

    Dobbs Drena

    2011-06-01

    Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

  15. Sequence analysis corresponding to the PPE and PE proteins in ...

    Indian Academy of Sciences (India)

    Unknown

    AB repeats; Mycobacterium tuberculosis genome; PE-PPE domain; PPE, PE proteins; sequence analysis; surface antigens. J. Biosci. | Vol. ... bacterium tuberculosis genomes resulted in the identification of a previously uncharacterized 225 amino acid- ...... Vega Lopez F, Brooks L A, Dockrell H M, De Smet K A,. Thompson ...

  16. Representation of protein-sequence information by amino acid subalphabets

    DEFF Research Database (Denmark)

    Andersen, C.A.F.; Brunak, Søren

    2004-01-01

    -sequence information, using machine learning strategies, where the primary goal is the discovery of novel powerful representations for use in AI techniques. In the case of proteins and the 20 different amino acids they typically contain, it is also a secondary goal to discover how the current selection of amino acids...

  17. GuiTope: an application for mapping random-sequence peptides to protein sequences.

    Science.gov (United States)

    Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

    2012-01-03

    Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

  18. GuiTope: an application for mapping random-sequence peptides to protein sequences

    Directory of Open Access Journals (Sweden)

    Halperin Rebecca F

    2012-01-01

    Full Text Available Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

  19. The HMMER Web Server for Protein Sequence Similarity Search.

    Science.gov (United States)

    Prakash, Ananth; Jeffryes, Matt; Bateman, Alex; Finn, Robert D

    2017-12-08

    Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  20. Biophysical and structural considerations for protein sequence evolution

    Directory of Open Access Journals (Sweden)

    Grahnen Johan A

    2011-12-01

    Full Text Available Abstract Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model.

  1. The Danish STR sequence database: duplicate typing of 363 Danes with the ForenSeq™ DNA Signature Prep Kit.

    Science.gov (United States)

    Hussing, C; Bytyci, R; Huber, C; Morling, N; Børsting, C

    2018-05-24

    Some STR loci have internal sequence variations, which are not revealed by the standard STR typing methods used in forensic genetics (PCR and fragment length analysis by capillary electrophoresis (CE)). Typing of STRs with next-generation sequencing (NGS) uncovers the sequence variation in the repeat region and in the flanking regions. In this study, 363 Danish individuals were typed for 56 STRs (26 autosomal STRs, 24 Y-STRs, and 6 X-STRs) using the ForenSeq™ DNA Signature Prep Kit to establish a Danish STR sequence database. Increased allelic diversity was observed in 34 STRs by the PCR-NGS assay. The largest increases were found in DYS389II and D12S391, where the numbers of sequenced alleles were around four times larger than the numbers of alleles determined by repeat length alone. Thirteen SNPs and one InDel were identified in the flanking regions of 12 STRs. Furthermore, 36 single positions and five longer stretches in the STR flanking regions were found to have dubious genotyping quality. The combined match probability of the 26 autosomal STRs was 10,000 times larger using the PCR-NGS assay than by using PCR-CE. The typical paternity indices for trios and duos were 500 and 100 times larger, respectively, than those obtained with PCR-CE. The assay also amplified 94 SNPs selected for human identification. Eleven of these loci were not in Hardy-Weinberg equilibrium in the Danish population, most likely because the minimum threshold for allele calling (30 reads) in the ForenSeq™ Universal Analysis Software was too low and frequent allele dropouts were not detected.

  2. Protein sequencing via nanopore based devices: a nanofluidics perspective

    Science.gov (United States)

    Chinappi, Mauro; Cecconi, Fabio

    2018-05-01

    Proteins perform a huge number of central functions in living organisms, thus all the new techniques allowing their precise, fast and accurate characterization at single-molecule level certainly represent a burst in proteomics with important biomedical impact. In this review, we describe the recent progresses in the developing of nanopore based devices for protein sequencing. We start with a critical analysis of the main technical requirements for nanopore protein sequencing, summarizing some ideas and methodologies that have recently appeared in the literature. In the last sections, we focus on the physical modelling of the transport phenomena occurring in nanopore based devices. The multiscale nature of the problem is discussed and, in this respect, some of the main possible computational approaches are illustrated.

  3. Sequence heterogeneity accelerates protein search for targets on DNA

    International Nuclear Information System (INIS)

    Shvets, Alexey A.; Kolomeisky, Anatoly B.

    2015-01-01

    The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome

  4. Sequence heterogeneity accelerates protein search for targets on DNA

    Energy Technology Data Exchange (ETDEWEB)

    Shvets, Alexey A.; Kolomeisky, Anatoly B., E-mail: tolya@rice.edu [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

    2015-12-28

    The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome.

  5. Determining and comparing protein function in Bacterial genome sequences

    DEFF Research Database (Denmark)

    Vesth, Tammi Camilla

    of this class have very little homology to other known genomes making functional annotation based on sequence similarity very difficult. Inspired in part by this analysis, an approach for comparative functional annotation was created based public sequenced genomes, CMGfunc. Functionally related groups......In November 2013, there was around 21.000 different prokaryotic genomes sequenced and publicly available, and the number is growing daily with another 20.000 or more genomes expected to be sequenced and deposited by the end of 2014. An important part of the analysis of this data is the functional...... annotation of genes – the descriptions assigned to genes that describe the likely function of the encoded proteins. This process is limited by several factors, including the definition of a function which can be more or less specific as well as how many genes can actually be assigned a function based...

  6. Relationships between residue Voronoi volume and sequence conservation in proteins.

    Science.gov (United States)

    Liu, Jen-Wei; Cheng, Chih-Wen; Lin, Yu-Feng; Chen, Shao-Yu; Hwang, Jenn-Kang; Yen, Shih-Chung

    2018-02-01

    Functional and biophysical constraints can cause different levels of sequence conservation in proteins. Previously, structural properties, e.g., relative solvent accessibility (RSA) and packing density of the weighted contact number (WCN), have been found to be related to protein sequence conservation (CS). The Voronoi volume has recently been recognized as a new structural property of the local protein structural environment reflecting CS. However, for surface residues, it is sensitive to water molecules surrounding the protein structure. Herein, we present a simple structural determinant termed the relative space of Voronoi volume (RSV); it uses the Voronoi volume and the van der Waals volume of particular residues to quantify the local structural environment. RSV (range, 0-1) is defined as (Voronoi volume-van der Waals volume)/Voronoi volume of the target residue. The concept of RSV describes the extent of available space for every protein residue. RSV and Voronoi profiles with and without water molecules (RSVw, RSV, VOw, and VO) were compared for 554 non-homologous proteins. RSV (without water) showed better Pearson's correlations with CS than did RSVw, VO, or VOw values. The mean correlation coefficient between RSV and CS was 0.51, which is comparable to the correlation between RSA and CS (0.49) and that between WCN and CS (0.56). RSV is a robust structural descriptor with and without water molecules and can quantitatively reflect evolutionary information in a single protein structure. Therefore, it may represent a practical structural determinant to study protein sequence, structure, and function relationships. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

    Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and

  8. Ultra-fast evaluation of protein energies directly from sequence.

    Directory of Open Access Journals (Sweden)

    Gevorg Grigoryan

    2006-06-01

    Full Text Available The structure, function, stability, and many other properties of a protein in a fixed environment are fully specified by its sequence, but in a manner that is difficult to discern. We present a general approach for rapidly mapping sequences directly to their energies on a pre-specified rigid backbone, an important sub-problem in computational protein design and in some methods for protein structure prediction. The cluster expansion (CE method that we employ can, in principle, be extended to model any computable or measurable protein property directly as a function of sequence. Here we show how CE can be applied to the problem of computational protein design, and use it to derive excellent approximations of physical potentials. The approach provides several attractive advantages. First, following a one-time derivation of a CE expansion, the amount of time necessary to evaluate the energy of a sequence adopting a specified backbone conformation is reduced by a factor of 10(7 compared to standard full-atom methods for the same task. Second, the agreement between two full-atom methods that we tested and their CE sequence-based expressions is very high (root mean square deviation 1.1-4.7 kcal/mol, R2 = 0.7-1.0. Third, the functional form of the CE energy expression is such that individual terms of the expansion have clear physical interpretations. We derived expressions for the energies of three classic protein design targets-a coiled coil, a zinc finger, and a WW domain-as functions of sequence, and examined the most significant terms. Single-residue and residue-pair interactions are sufficient to accurately capture the energetics of the dimeric coiled coil, whereas higher-order contributions are important for the two more globular folds. For the task of designing novel zinc-finger sequences, a CE-derived energy function provides significantly better solutions than a standard design protocol, in comparable computation time. Given these advantages

  9. Genetic signatures of adaptation revealed from transcriptome sequencing of Arctic and red foxes

    OpenAIRE

    Kumar, Vikas; Kutschera, Verena E.; Nilsson, Maria A.; Janke, Axel

    2015-01-01

    Background The genus Vulpes (true foxes) comprises numerous species that inhabit a wide range of habitats and climatic conditions, including one species, the Arctic fox (Vulpes lagopus) which is adapted to the arctic region. A close relative to the Arctic fox, the red fox (Vulpes vulpes), occurs in subarctic to subtropical habitats. To study the genetic basis of their adaptations to different environments, transcriptome sequences from two Arctic foxes and one red fox individual were generated...

  10. Deep sequencing of the oral microbiome reveals signatures of periodontal disease.

    Directory of Open Access Journals (Sweden)

    Bo Liu

    Full Text Available The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (~2 lanes Illumina 76 bp PE and high human DNA contamination (up to ~90% we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.

  11. HLA DNA sequence variation among human populations: molecular signatures of demographic and selective events.

    Directory of Open Access Journals (Sweden)

    Stéphane Buhler

    2011-02-01

    Full Text Available Molecular differences between HLA alleles vary up to 57 nucleotides within the peptide binding coding region of human Major Histocompatibility Complex (MHC genes, but it is still unclear whether this variation results from a stochastic process or from selective constraints related to functional differences among HLA molecules. Although HLA alleles are generally treated as equidistant molecular units in population genetic studies, DNA sequence diversity among populations is also crucial to interpret the observed HLA polymorphism. In this study, we used a large dataset of 2,062 DNA sequences defined for the different HLA alleles to analyze nucleotide diversity of seven HLA genes in 23,500 individuals of about 200 populations spread worldwide. We first analyzed the HLA molecular structure and diversity of these populations in relation to geographic variation and we further investigated possible departures from selective neutrality through Tajima's tests and mismatch distributions. All results were compared to those obtained by classical approaches applied to HLA allele frequencies.Our study shows that the global patterns of HLA nucleotide diversity among populations are significantly correlated to geography, although in some specific cases the molecular information reveals unexpected genetic relationships. At all loci except HLA-DPB1, populations have accumulated a high proportion of very divergent alleles, suggesting an advantage of heterozygotes expressing molecularly distant HLA molecules (asymmetric overdominant selection model. However, both different intensities of selection and unequal levels of gene conversion may explain the heterogeneous mismatch distributions observed among the loci. Also, distinctive patterns of sequence divergence observed at the HLA-DPB1 locus suggest current neutrality but old selective pressures on this gene. We conclude that HLA DNA sequences advantageously complement HLA allele frequencies as a source of data used

  12. Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

    Directory of Open Access Journals (Sweden)

    Colin A Smith

    Full Text Available Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface, interactions between and within parts of the structure (e.g. domains can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

  13. SAAS: Short Amino Acid Sequence - A Promising Protein Secondary Structure Prediction Method of Single Sequence

    Directory of Open Access Journals (Sweden)

    Zhou Yuan Wu

    2013-07-01

    Full Text Available In statistical methods of predicting protein secondary structure, many researchers focus on single amino acid frequencies in α-helices, β-sheets, and so on, or the impact near amino acids on an amino acid forming a secondary structure. But the paper considers a short sequence of amino acids (3, 4, 5 or 6 amino acids as integer, and statistics short sequence's probability forming secondary structure. Also, many researchers select low homologous sequences as statistical database. But this paper select whole PDB database. In this paper we propose a strategy to predict protein secondary structure using simple statistical method. Numerical computation shows that, short amino acids sequence as integer to statistics, which can easy see trend of short sequence forming secondary structure, and it will work well to select large statistical database (whole PDB database without considering homologous, and Q3 accuracy is ca. 74% using this paper proposed simple statistical method, but accuracy of others statistical methods is less than 70%.

  14. An estrogen-responsive plasma protein expression signature in Atlantic cod (Gadus morhua) revealed by SELDI-TOF MS

    DEFF Research Database (Denmark)

    Nielsen, Mari Mæland; Meyer, Sonnich; Larsen, Bodil Katrine

    2011-01-01

    Compound-specific protein expression signatures( PESs) can be revealed by proteomic techniques. The SELDI-TOF MS approach is advantageous due to its simplicity and high-throughput capacity,however, there are concerns regarding the reproducibility of this method. The aim of this study was to define...

  15. Protein sequences bound to mineral surfaces persist into deep time

    DEFF Research Database (Denmark)

    Demarchi, Beatrice; Hall, Shaun; Roncal-Herrero, Teresa

    2016-01-01

    of Laetoli (3.8 Ma) and Olduvai Gorge (1.3 Ma) in Tanzania. By tracking protein diagenesis back in time we find consistent patterns of preservation, demonstrating authenticity of the surviving sequences. Molecular dynamics simulations of struthiocalcin-1 and -2, the dominant proteins within the eggshell......, reveal that distinct domains bind to the mineral surface. It is the domain with the strongest calculated binding energy to the calcite surface that is selectively preserved. Thermal age calculations demonstrate that the Laetoli and Olduvai peptides are 50 times older than any previously authenticated...

  16. Requirement for asparagine in the aquaporin NPA sequence signature motifs for cation exclusion

    DEFF Research Database (Denmark)

    Wree, Dorothea; Wu, Binghua; Zeuthen, Thomas

    2011-01-01

    Two highly conserved NPA motifs are a hallmark of the aquaporin (AQP) family. The NPA triplets form N-terminal helix capping structures with the Asn side chains located in the centre of the water or solute-conducting channel, and are considered to play an important role in AQP selectivity. Although...... interchangeable at both NPA sites without affecting protein expression or water, glycerol and methylamine permeability. However, other mutations in the NPA region led to reduced permeability (S186C and S186D), to nonfunctional channels (N64D), or even to lack of protein expression (S186A and S186T). Using...... electrophysiology, we found that an analogous mammalian AQP1 N76S mutant excluded protons and potassium ions, but leaked sodium ions, providing an argument for the overwhelming prevalence of Asn over other amino acids. We conclude that, at the first position in the NPA motifs, only Asn provides efficient helix cap...

  17. Identifying Genetic Signatures of Natural Selection Using Pooled Population Sequencing in Picea abies.

    Science.gov (United States)

    Chen, Jun; Källman, Thomas; Ma, Xiao-Fei; Zaina, Giusi; Morgante, Michele; Lascoux, Martin

    2016-07-07

    The joint inference of selection and past demography remain a costly and demanding task. We used next generation sequencing of two pools of 48 Norway spruce mother trees, one corresponding to the Fennoscandian domain, and the other to the Alpine domain, to assess nucleotide polymorphism at 88 nuclear genes. These genes are candidate genes for phenological traits, and most belong to the photoperiod pathway. Estimates of population genetic summary statistics from the pooled data are similar to previous estimates, suggesting that pooled sequencing is reliable. The nonsynonymous SNPs tended to have both lower frequency differences and lower FST values between the two domains than silent ones. These results suggest the presence of purifying selection. The divergence between the two domains based on synonymous changes was around 5 million yr, a time similar to a recent phylogenetic estimate of 6 million yr, but much larger than earlier estimates based on isozymes. Two approaches, one of them novel and that considers both FST and difference in allele frequencies between the two domains, were used to identify SNPs potentially under diversifying selection. SNPs from around 20 genes were detected, including genes previously identified as main target for selection, such as PaPRR3 and PaGI. Copyright © 2016 Chen et al.

  18. Computational identification of MoRFs in protein sequences.

    Science.gov (United States)

    Malhis, Nawar; Gsponer, Jörg

    2015-06-01

    Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important computational challenge. In this study, we introduce MoRFCHiBi, a new computational approach for fast and accurate prediction of MoRFs in protein sequences. MoRFCHiBi combines the outcomes of two support vector machine (SVM) models that take advantage of two different kernels with high noise tolerance. The first, SVMS, is designed to extract maximal information from the general contrast in amino acid compositions between MoRFs, their surrounding regions (Flanks), and the remainders of the sequences. The second, SVMT, is used to identify similarities between regions in a query sequence and MoRFs of the training set. We evaluated the performance of our predictor by comparing its results with those of two currently available MoRF predictors, MoRFpred and ANCHOR. Using three test sets that have previously been collected and used to evaluate MoRFpred and ANCHOR, we demonstrate that MoRFCHiBi outperforms the other predictors with respect to different evaluation metrics. In addition, MoRFCHiBi is downloadable and fast, which makes it useful as a component in other computational prediction tools. http://www.chibi.ubc.ca/morf/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. Functional analysis of bipartite begomovirus coat protein promoter sequences

    International Nuclear Information System (INIS)

    Lacatus, Gabriela; Sunter, Garry

    2008-01-01

    We demonstrate that the AL2 gene of Cabbage leaf curl virus (CaLCuV) activates the CP promoter in mesophyll and acts to derepress the promoter in vascular tissue, similar to that observed for Tomato golden mosaic virus (TGMV). Binding studies indicate that sequences mediating repression and activation of the TGMV and CaLCuV CP promoter specifically bind different nuclear factors common to Nicotiana benthamiana, spinach and tomato. However, chromatin immunoprecipitation demonstrates that TGMV AL2 can interact with both sequences independently. Binding of nuclear protein(s) from different crop species to viral sequences conserved in both bipartite and monopartite begomoviruses, including TGMV, CaLCuV, Pepper golden mosaic virus and Tomato yellow leaf curl virus suggests that bipartite begomoviruses bind common host factors to regulate the CP promoter. This is consistent with a model in which AL2 interacts with different components of the cellular transcription machinery that bind viral sequences important for repression and activation of begomovirus CP promoters

  20. Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

    Science.gov (United States)

    Hayat, Maqsood; Khan, Asifullah

    2011-02-21

    Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

    Science.gov (United States)

    Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

    2015-01-01

    There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

  2. Properties of Sequence Conservation in Upstream Regulatory and Protein Coding Sequences among Paralogs in Arabidopsis thaliana

    Science.gov (United States)

    Richardson, Dale N.; Wiehe, Thomas

    Whole genome duplication (WGD) has catalyzed the formation of new species, genes with novel functions, altered expression patterns, complexified signaling pathways and has provided organisms a level of genetic robustness. We studied the long-term evolution and interrelationships of 5’ upstream regulatory sequences (URSs), protein coding sequences (CDSs) and expression correlations (EC) of duplicated gene pairs in Arabidopsis. Three distinct methods revealed significant evolutionary conservation between paralogous URSs and were highly correlated with microarray-based expression correlation of the respective gene pairs. Positional information on exact matches between sequences unveiled the contribution of micro-chromosomal rearrangements on expression divergence. A three-way rank analysis of URS similarity, CDS divergence and EC uncovered specific gene functional biases. Transcription factor activity was associated with gene pairs exhibiting conserved URSs and divergent CDSs, whereas a broad array of metabolic enzymes was found to be associated with gene pairs showing diverged URSs but conserved CDSs.

  3. RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

    Science.gov (United States)

    Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

    2016-10-07

    RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

  4. CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences

    Directory of Open Access Journals (Sweden)

    Charalambos Chrysostomou

    2015-01-01

    Full Text Available Complex informational spectrum analysis for protein sequences (CISAPS and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.

  5. Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

    Directory of Open Access Journals (Sweden)

    Mile Sikić

    2009-01-01

    Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

  6. Outlier Loci and Selection Signatures of Simple Sequence Repeats (SSRs) in Flax (Linum usitatissimum L.).

    Science.gov (United States)

    Soto-Cerda, Braulio J; Cloutier, Sylvie

    2013-01-01

    Genomic microsatellites (gSSRs) and expressed sequence tag-derived SSRs (EST-SSRs) have gained wide application for elucidating genetic diversity and population structure in plants. Both marker systems are assumed to be selectively neutral when making demographic inferences, but this assumption is rarely tested. In this study, three neutrality tests were assessed for identifying outlier loci among 150 SSRs (85 gSSRs and 65 EST-SSRs) that likely influence estimates of population structure in three differentiated flax sub-populations ( F ST  = 0.19). Moreover, the utility of gSSRs, EST-SSRs, and the combined sets of SSRs was also evaluated in assessing genetic diversity and population structure in flax. Six outlier loci were identified by at least two neutrality tests showing footprints of balancing selection. After removing the outlier loci, the STRUCTURE analysis and the dendrogram topology of EST-SSRs improved. Conversely, gSSRs and combined SSRs results did not change significantly, possibly as a consequence of the higher number of neutral loci assessed. Taken together, the genetic structure analyses established the superiority of gSSRs to determine the genetic relationships among flax accessions, although the combined SSRs produced the best results. Genetic diversity parameters did not differ statistically ( P  > 0.05) between gSSRs and EST-SSRs, an observation partially explained by the similar number of repeat motifs. Our study provides new insights into the ability of gSSRs and EST-SSRs to measure genetic diversity and structure in flax and confirms the importance of testing for the occurrence of outlier loci to properly assess natural and breeding populations, particularly in studies considering only few loci.

  7. Messenger RNA biomarker signatures for forensic body fluid identification revealed by targeted RNA sequencing.

    Science.gov (United States)

    Hanson, E; Ingold, S; Haas, C; Ballantyne, J

    2018-05-01

    The recovery of a DNA profile from the perpetrator or victim in criminal investigations can provide valuable 'source level' information for investigators. However, a DNA profile does not reveal the circumstances by which biological material was transferred. Some contextual information can be obtained by a determination of the tissue or fluid source of origin of the biological material as it is potentially indicative of some behavioral activity on behalf of the individual that resulted in its transfer from the body. Here, we sought to improve upon established RNA based methods for body fluid identification by developing a targeted multiplexed next generation mRNA sequencing assay comprising a panel of approximately equal sized gene amplicons. The multiplexed biomarker panel includes several highly specific gene targets with the necessary specificity to definitively identify most forensically relevant biological fluids and tissues (blood, semen, saliva, vaginal secretions, menstrual blood and skin). In developing the biomarker panel we evaluated 66 gene targets, with a progressive iteration of testing target combinations that exhibited optimal sensitivity and specificity using a training set of forensically relevant body fluid samples. The current assay comprises 33 targets: 6 blood, 6 semen, 6 saliva, 4 vaginal secretions, 5 menstrual blood and 6 skin markers. We demonstrate the sensitivity and specificity of the assay and the ability to identify body fluids in single source and admixed stains. A 16 sample blind test was carried out by one lab with samples provided by the other participating lab. The blinded lab correctly identified the body fluids present in 15 of the samples with the major component identified in the 16th. Various classification methods are being investigated to permit inference of the body fluid/tissue in dried physiological stains. These include the percentage of reads in a sample that are due to each of the 6 tissues/body fluids tested and

  8. Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

    Science.gov (United States)

    Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

    2011-08-21

    Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Analysis of correlations between sites in models of protein sequences

    International Nuclear Information System (INIS)

    Giraud, B.G.; Lapedes, A.; Liu, L.C.

    1998-01-01

    A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society

  10. Protein model discrimination using mutational sensitivity derived from deep sequencing.

    Science.gov (United States)

    Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

    2012-02-08

    A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. Nucleation phenomena in protein folding: the modulating role of protein sequence

    International Nuclear Information System (INIS)

    Travasso, Rui D M; FaIsca, Patricia F N; Gama, Margarida M Telo da

    2007-01-01

    For the vast majority of naturally occurring, small, single-domain proteins, folding is often described as a two-state process that lacks detectable intermediates. This observation has often been rationalized on the basis of a nucleation mechanism for protein folding whose basic premise is the idea that, after completion of a specific set of contacts forming the so-called folding nucleus, the native state is achieved promptly. Here we propose a methodology to identify folding nuclei in small lattice polymers and apply it to the study of protein molecules with a chain length of N = 48. To investigate the extent to which protein topology is a robust determinant of the nucleation mechanism, we compare the nucleation scenario of a native-centric model with that of a sequence-specific model sharing the same native fold. To evaluate the impact of the sequence's finer details in the nucleation mechanism, we consider the folding of two non-homologous sequences. We conclude that, in a sequence-specific model, the folding nucleus is, to some extent, formed by the most stable contacts in the protein and that the less stable linkages in the folding nucleus are solely determined by the fold's topology. We have also found that, independently of the protein sequence, the folding nucleus performs the same 'topological' function. This unifying feature of the nucleation mechanism results from the residues forming the folding nucleus being distributed along the protein chain in a similar and well-defined manner that is determined by the fold's topological features

  12. Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences | Center for Cancer Research

    Science.gov (United States)

    A graphical method is presented for displaying how binding proteins and other macromolecules interact with individual bases of nucleotide sequences. Characters representing the sequence are either oriented normally and placed above a line indicating favorable contact, or upside-down and placed below the line indicating unfavorable contact. The positive or negative height of each letter shows the contribution of that base to the average sequence conservation of the binding site, as represented by a sequence logo.

  13. Experimental Rugged Fitness Landscape in Protein Sequence Space

    Science.gov (United States)

    Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

    2006-01-01

    The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

  14. Experimental rugged fitness landscape in protein sequence space.

    Science.gov (United States)

    Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

    2006-12-20

    The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

  15. Experimental rugged fitness landscape in protein sequence space.

    Directory of Open Access Journals (Sweden)

    Yuuki Hayashi

    Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

  16. The SBASE protein domain library, release 8.0: a collection of annotated protein sequence segments.

    Science.gov (United States)

    Murvai, J; Vlahovicek, K; Barta, E; Pongor, S

    2001-01-01

    SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc. hu/sbase/.

  17. Major urinary protein (MUP) profiles show dynamic changes rather than individual ‘barcode’ signatures

    Science.gov (United States)

    Thoß, M.; Luzynski, K.C.; Ante, M.; Miller, I.; Penn, D.J.

    2016-01-01

    House mice (Mus musculus) produce a variable number of major urinary proteins (MUPs), and studies suggest that each individual produces a unique MUP profile that provides a distinctive odor signature controlling individual and kin recognition. This ‘barcode hypothesis’ requires that MUP urinary profiles show high individual variability within populations and also high individual consistency over time, but tests of these assumptions are lacking. We analyzed urinary MUP profiles of 66 wild-caught house mice from eight populations using isoelectric focusing. We found that MUP profiles of wild male house mice are not individually unique, and though they were highly variable, closer inspection revealed that the variation strongly depended on MUP band type. The prominent (‘major) bands were surprisingly homogenous (and hence most MUPs are not polymorphic), but we also found inconspicuous (‘minor’) bands that were highly variable and therefore potential candidates for individual fingerprints. We also examined changes in urinary MUP profiles of 58 males over time (from 6 to 24 weeks of age), and found that individual MUP profiles and MUP concentration were surprisingly dynamic, and showed significant changes after puberty and during adulthood. Contrary to what we expected, however, the minor bands were the most variable over time, thus no good candidates for individual fingerprints. Although MUP profiles do not provide individual fingerprints, we found that MUP profiles were more similar among siblings than non-kin despite considerable fluctuation. Our findings show that MUP profiles are not highly stable over time, they do not show strong individual clustering, and thus challenge the barcode hypothesis. Within-individual dynamics of MUP profiles indicate a different function of MUPs in individual recognition than previously assumed and advocate an alternative hypothesis (‘dynamic changes’ hypothesis). PMID:26973837

  18. Major urinary protein (MUP) profiles show dynamic changes rather than individual 'barcode' signatures.

    Science.gov (United States)

    Thoß, M; Luzynski, K C; Ante, M; Miller, I; Penn, D J

    2015-06-30

    House mice ( Mus musculus) produce a variable number of major urinary proteins (MUPs), and studies suggest that each individual produces a unique MUP profile that provides a distinctive odor signature controlling individual and kin recognition. This 'barcode hypothesis' requires that MUP urinary profiles show high individual variability within populations and also high individual consistency over time, but tests of these assumptions are lacking. We analyzed urinary MUP profiles of 66 wild-caught house mice from eight populations using isoelectric focusing. We found that MUP profiles of wild male house mice are not individually unique, and though they were highly variable, closer inspection revealed that the variation strongly depended on MUP band type. The prominent ('major) bands were surprisingly homogenous (and hence most MUPs are not polymorphic), but we also found inconspicuous ('minor') bands that were highly variable and therefore potential candidates for individual fingerprints. We also examined changes in urinary MUP profiles of 58 males over time (from 6 to 24 weeks of age), and found that individual MUP profiles and MUP concentration were surprisingly dynamic, and showed significant changes after puberty and during adulthood. Contrary to what we expected, however, the minor bands were the most variable over time, thus no good candidates for individual fingerprints. Although MUP profiles do not provide individual fingerprints, we found that MUP profiles were more similar among siblings than non-kin despite considerable fluctuation. Our findings show that MUP profiles are not highly stable over time, they do not show strong individual clustering, and thus challenge the barcode hypothesis. Within-individual dynamics of MUP profiles indicate a different function of MUPs in individual recognition than previously assumed and advocate an alternative hypothesis ('dynamic changes' hypothesis).

  19. Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

    Directory of Open Access Journals (Sweden)

    Cheng-Hsien Wu

    Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

  20. Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

    International Nuclear Information System (INIS)

    Oudes, Asa J; Roach, Jared C; Walashek, Laura S; Eichner, Lillian J; True, Lawrence D; Vessella, Robert L; Liu, Alvin Y

    2005-01-01

    Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases

  1. DNA-mediated dimerization on a compact sequence signature controls enhancer engagement and regulation by FOXA1.

    Science.gov (United States)

    Wang, Xuecong; Srivastava, Yogesh; Jankowski, Aleksander; Malik, Vikas; Wei, Yuanjie; Del Rosario, Ricardo C H; Cojocaru, Vlad; Prabhakar, Shyam; Jauch, Ralf

    2018-04-14

    FOXA1 is a transcription factor capable to bind silenced chromatin to direct context-dependent cell fate conversion. Here, we demonstrate that a compact palindromic DNA element (termed 'DIV' for its diverging half-sites) induces the homodimerization of FOXA1 with strongly positive cooperativity. Alternative structural models are consistent with either an indirect DNA-mediated cooperativity or a direct protein-protein interaction. The cooperative homodimer formation is strictly constrained by precise half-site spacing. Re-analysis of chromatin immunoprecipitation sequencing data indicates that the DIV is effectively targeted by FOXA1 in the context of chromatin. Reporter assays show that FOXA1-dependent transcriptional activity declines when homodimeric binding is disrupted. In response to phosphatidylinositol-3 kinase inhibition DIV sites pre-bound by FOXA1 such as at the PVT1/MYC locus exhibit a strong increase in accessibility suggesting a role of the DIV configuration in the chromatin closed-open dynamics. Moreover, several disease-associated single nucleotide polymorphisms map to DIV elements and show allelic differences in FOXA1 homodimerization, reporter gene expression and are annotated as quantitative trait loci. This includes the rs541455835 variant at the MAPT locus encoding the Tau protein associated with Parkinson's disease. Collectively, the DIV guides chromatin engagement and regulation by FOXA1 and its perturbation could be linked to disease etiologies.

  2. Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences.

    Directory of Open Access Journals (Sweden)

    Alexander M Sevy

    2015-07-01

    Full Text Available Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD paradigm. Multi-specificity design (MSD, on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON. The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.

  3. Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

    Science.gov (United States)

    Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

    2018-01-01

    We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation.  Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases.  We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes.  Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.

  4. Fragmentation of the CRISPR-Cas Type I-B signature protein Cas8b.

    Science.gov (United States)

    Richter, Hagen; Rompf, Judith; Wiegel, Julia; Rau, Kristina; Randau, Lennart

    2017-11-01

    CRISPR arrays are transcribed into long precursor RNA species, which are further processed into mature CRISPR RNAs (crRNAs). Cas proteins utilize these crRNAs, which contain spacer sequences that can be derived from mobile genetic elements, to mediate immunity during a reoccurring virus infection. Type I CRISPR-Cas systems are defined by the presence of different Cascade interference complexes containing large and small subunits that play major roles during target DNA selection. Here, we produce the protein and crRNA components of the Type I-B CRISPR-Cas complex of Clostridium thermocellum and Methanococcus maripaludis. The C. thermocellum Cascade complexes were reconstituted and analyzed via size-exclusion chromatography. Activity of the heterologous M. maripaludis CRISPR-Cas system was followed using phage lambda plaques assays. The reconstituted Type-I-B Cascade complex contains Cas7, Cas5, Cas6b and the large subunit Cas8b. Cas6b can be omitted from the reconstitution protocol. The large subunit Cas8b was found to be represented by two tightly associated protein fragments and a small C-terminal Cas8b segment was identified in recombinant complexes and C. thermocellum cell lysate. Production of Cas8b generates a small C-terminal fragment, which is suggested to fulfill the role of the missing small subunit. A heterologous, synthetic M. maripaludis Type I-B system is active in E. coli against phage lambda, highlighting a potential for genome editing using endogenous Type-I-B CRISPR-Cas machineries. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

    NARCIS (Netherlands)

    Al-Shahib, A.; Breitling, R.; Gilbert, D.

    2005-01-01

    Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

  6. Designing sequence to control protein function in an EF-hand protein.

    Science.gov (United States)

    Bunick, Christopher G; Nelson, Melanie R; Mangahas, Sheryll; Hunter, Michael J; Sheehan, Jonathan H; Mizoue, Laura S; Bunick, Gerard J; Chazin, Walter J

    2004-05-19

    The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.

  7. How Many Protein Sequences Fold to a Given Structure? A Coevolutionary Analysis.

    Science.gov (United States)

    Tian, Pengfei; Best, Robert B

    2017-10-17

    Quantifying the relationship between protein sequence and structure is key to understanding the protein universe. A fundamental measure of this relationship is the total number of amino acid sequences that can fold to a target protein structure, known as the "sequence capacity," which has been suggested as a proxy for how designable a given protein fold is. Although sequence capacity has been extensively studied using lattice models and theory, numerical estimates for real protein structures are currently lacking. In this work, we have quantitatively estimated the sequence capacity of 10 proteins with a variety of different structures using a statistical model based on residue-residue co-evolution to capture the variation of sequences from the same protein family. Remarkably, we find that even for the smallest protein folds, such as the WW domain, the number of foldable sequences is extremely large, exceeding the Avogadro constant. In agreement with earlier theoretical work, the calculated sequence capacity is positively correlated with the size of the protein, or better, the density of contacts. This allows the absolute sequence capacity of a given protein to be approximately predicted from its structure. On the other hand, the relative sequence capacity, i.e., normalized by the total number of possible sequences, is an extremely tiny number and is strongly anti-correlated with the protein length. Thus, although there may be more foldable sequences for larger proteins, it will be much harder to find them. Lastly, we have correlated the evolutionary age of proteins in the CATH database with their sequence capacity as predicted by our model. The results suggest a trade-off between the opposing requirements of high designability and the likelihood of a novel fold emerging by chance. Published by Elsevier Inc.

  8. CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

    KAUST Repository

    Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

    2016-01-01

    Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment

  9. A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

    Science.gov (United States)

    Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

    2017-05-25

    Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

  10. SPiCE : A web-based tool for sequence-based protein classification and exploration

    NARCIS (Netherlands)

    Van den Berg, B.A.; Reinders, M.J.; Roubos, J.A.; De Ridder, D.

    2014-01-01

    Background Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction,

  11. Sequence protein identification by randomized sequence database and transcriptome mass spectrometry (SPIDER-TMS): from manual to automatic application of a 'de novo sequencing' approach.

    Science.gov (United States)

    Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Sarli Calace, Renzo; Falabella, Patrizia; Bianco, Giuliana

    Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.

  12. Formation of a Multiple Protein Complex on the Adenovirus Packaging Sequence by the IVa2 Protein▿

    OpenAIRE

    Tyler, Ryan E.; Ewing, Sean G.; Imperiale, Michael J.

    2007-01-01

    During adenovirus virion assembly, the packaging sequence mediates the encapsidation of the viral genome. This sequence is composed of seven functional units, termed A repeats. Recent evidence suggests that the adenovirus IVa2 protein binds the packaging sequence and is involved in packaging of the genome. Study of the IVa2-packaging sequence interaction has been hindered by difficulty in purifying the protein produced in virus-infected cells or by recombinant techniques. We report the first ...

  13. MIPS: a database for protein sequences, homology data and yeast genome information.

    Science.gov (United States)

    Mewes, H W; Albermann, K; Heumann, K; Liebl, S; Pfeiffer, F

    1997-01-01

    The MIPS group (Martinsried Institute for Protein Sequences) at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, collects, processes and distributes protein sequence data within the framework of the tripartite association of the PIR-International Protein Sequence Database (,). MIPS contributes nearly 50% of the data input to the PIR-International Protein Sequence Database. The database is distributed on CD-ROM together with PATCHX, an exhaustive supplement of unique, unverified protein sequences from external sources compiled by MIPS. Through its WWW server (http://www.mips.biochem.mpg.de/ ) MIPS permits internet access to sequence databases, homology data and to yeast genome information. (i) Sequence similarity results from the FASTA program () are stored in the FASTA database for all proteins from PIR-International and PATCHX. The database is dynamically maintained and permits instant access to FASTA results. (ii) Starting with FASTA database queries, proteins have been classified into families and superfamilies (PROT-FAM). (iii) The HPT (hashed position tree) data structure () developed at MIPS is a new approach for rapid sequence and pattern searching. (iv) MIPS provides access to the sequence and annotation of the complete yeast genome (), the functional classification of yeast genes (FunCat) and its graphical display, the 'Genome Browser' (). A CD-ROM based on the JAVA programming language providing dynamic interactive access to the yeast genome and the related protein sequences has been compiled and is available on request. PMID:9016498

  14. Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

    Directory of Open Access Journals (Sweden)

    Kevin R Ramkissoon

    Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

  15. Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

    Science.gov (United States)

    Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

    2013-01-01

    The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

  16. Elman RNN based classification of proteins sequences on account of their mutual information.

    Science.gov (United States)

    Mishra, Pooja; Nath Pandey, Paras

    2012-10-21

    In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. JACOP: A simple and robust method for the automated classification of protein sequences with modular architecture

    Directory of Open Access Journals (Sweden)

    Pagni Marco

    2005-08-01

    Full Text Available Abstract Background Whole-genome sequencing projects are rapidly producing an enormous number of new sequences. Consequently almost every family of proteins now contains hundreds of members. It has thus become necessary to develop tools, which classify protein sequences automatically and also quickly and reliably. The difficulty of this task is intimately linked to the mechanism by which protein sequences diverge, i.e. by simultaneous residue substitutions, insertions and/or deletions and whole domain reorganisations (duplications/swapping/fusion. Results Here we present a novel approach, which is based on random sampling of sub-sequences (probes out of a set of input sequences. The probes are compared to the input sequences, after a normalisation step; the results are used to partition the input sequences into homogeneous groups of proteins. In addition, this method provides information on diagnostic parts of the proteins. The performance of this method is challenged by two data sets. The first one contains the sequences of prokaryotic lyases that could be arranged as a multiple sequence alignment. The second one contains all proteins from Swiss-Prot Release 36 with at least one Src homology 2 (SH2 domain – a classical example for proteins with modular architecture. Conclusion The outcome of our method is robust, highly reproducible as shown using bootstrap and resampling validation procedures. The results are essentially coherent with the biology. This method depends solely on well-established publicly available software and algorithms.

  18. Analysis of long-range correlation in sequences data of proteins

    OpenAIRE

    ADRIANA ISVORAN; LAURA UNIPAN; DANA CRACIUN; VASILE MORARIU

    2007-01-01

    The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment....

  19. Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

    Science.gov (United States)

    Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

    2017-05-25

    Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

  20. Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

    Directory of Open Access Journals (Sweden)

    Yunyun Liang

    2015-01-01

    Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

  1. Exploring Sequence Characteristics Related to High- Level Production of Secreted Proteins in Aspergillus niger

    NARCIS (Netherlands)

    Van den Berg, B.A.; Reinders, M.J.T.; Hulsman, M.; Wu, L.; Pel, H.J.; Roubos, J.A.; De Ridder, D.

    2012-01-01

    Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large

  2. Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

    Directory of Open Access Journals (Sweden)

    Mahdi Sarmady

    Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

  3. Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

    Science.gov (United States)

    Higgins, Sean A; Savage, David F

    2018-01-09

    A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

  4. Microwave-assisted acid and base hydrolysis of intact proteins containing disulfide bonds for protein sequence analysis by mass spectrometry.

    Science.gov (United States)

    Reiz, Bela; Li, Liang

    2010-09-01

    Controlled hydrolysis of proteins to generate peptide ladders combined with mass spectrometric analysis of the resultant peptides can be used for protein sequencing. In this paper, two methods of improving the microwave-assisted protein hydrolysis process are described to enable rapid sequencing of proteins containing disulfide bonds and increase sequence coverage, respectively. It was demonstrated that proteins containing disulfide bonds could be sequenced by MS analysis by first performing hydrolysis for less than 2 min, followed by 1 h of reduction to release the peptides originally linked by disulfide bonds. It was shown that a strong base could be used as a catalyst for microwave-assisted protein hydrolysis, producing complementary sequence information to that generated by microwave-assisted acid hydrolysis. However, using either acid or base hydrolysis, amide bond breakages in small regions of the polypeptide chains of the model proteins (e.g., cytochrome c and lysozyme) were not detected. Dynamic light scattering measurement of the proteins solubilized in an acid or base indicated that protein-protein interaction or aggregation was not the cause of the failure to hydrolyze certain amide bonds. It was speculated that there were some unknown local structures that might play a role in preventing an acid or base from reacting with the peptide bonds therein. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

  5. Protein and DNA sequence determinants of thermophilic adaptation.

    Directory of Open Access Journals (Sweden)

    Konstantin B Zeldovich

    2007-01-01

    Full Text Available There have been considerable attempts in the past to relate phenotypic trait--habitat temperature of organisms--to their genotypes, most importantly compositions of their genomes and proteomes. However, despite accumulation of anecdotal evidence, an exact and conclusive relationship between the former and the latter has been elusive. We present an exhaustive study of the relationship between amino acid composition of proteomes, nucleotide composition of DNA, and optimal growth temperature (OGT of prokaryotes. Based on 204 complete proteomes of archaea and bacteria spanning the temperature range from -10 degrees C to 110 degrees C, we performed an exhaustive enumeration of all possible sets of amino acids and found a set of amino acids whose total fraction in a proteome is correlated, to a remarkable extent, with the OGT. The universal set is Ile, Val, Tyr, Trp, Arg, Glu, Leu (IVYWREL, and the correlation coefficient is as high as 0.93. We also found that the G + C content in 204 complete genomes does not exhibit a significant correlation with OGT (R = -0.10. On the other hand, the fraction of A + G in coding DNA is correlated with temperature, to a considerable extent, due to codon patterns of IVYWREL amino acids. Further, we found strong and independent correlation between OGT and the frequency with which pairs of A and G nucleotides appear as nearest neighbors in genome sequences. This adaptation is achieved via codon bias. These findings present a direct link between principles of proteins structure and stability and evolutionary mechanisms of thermophylic adaptation. On the nucleotide level, the analysis provides an example of how nature utilizes codon bias for evolutionary adaptation to extreme conditions. Together these results provide a complete picture of how compositions of proteomes and genomes in prokaryotes adjust to the extreme conditions of the environment.

  6. Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

    Directory of Open Access Journals (Sweden)

    Selbig Joachim

    2009-04-01

    Full Text Available Abstract Background Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D structural information available in the protein data bank (PDB and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as

  7. Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction

    Directory of Open Access Journals (Sweden)

    Minsuk eKwak

    2013-02-01

    Full Text Available Secreted proteins including cytokines, chemokines and growth factors represent important functional regulators mediating a range of cellular behavior and cell-cell paracrine/autocrine signaling, e.g. in the immunological system, tumor microenvironment or stem cell niche. Detection of these proteins is of great value not only in basic cell biology but also for diagnosis and therapeutic monitoring of human diseases such as cancer. However, due to co-production of multiple effector proteins from a single cell, referred to as polyfunctionality, it is biologically informative to measure a panel of secreted proteins, or secretomic signature, at the level of single cells. Recent evidence further indicates that a genetically-identical cell population can give rise to diverse phenotypic differences. It is known that cytokines, for example, in the immune system define the effector functions and lineage differentiation of immune cells. In this Perspective Article, we hypothesize that protein secretion profile may represent a universal measure to identify the definitive correlate in the larger context of cellular functions to dissect cellular heterogeneity and evolutionary lineage relationship in human cancer.

  8. Nonlinear analysis of sequence symmetry of beta-trefoil family proteins

    Energy Technology Data Exchange (ETDEWEB)

    Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xu Ruizhen [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: yxiao@mail.hust.edu.cn

    2005-07-01

    The tertiary structures of proteins of beta-trefoil family have three-fold quasi-symmetry while their amino acid sequences appear almost at random. In the present paper we show that these amino acid sequences have hidden symmetries in fact and furthermore the degrees of these hidden symmetries are the same as those of their tertiary structures. We shall present a modified recurrence plot to reveal hidden symmetries in protein sequences. Our results can explain the contradiction in sequence-structure relations of proteins of beta-trefoil family.

  9. CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

    KAUST Repository

    Cui, Xuefeng

    2016-06-15

    Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.

  10. Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry.

    Science.gov (United States)

    Asara, John M; Schweitzer, Mary H; Freimark, Lisa M; Phillips, Matthew; Cantley, Lewis C

    2007-04-13

    Fossilized bones from extinct taxa harbor the potential for obtaining protein or DNA sequences that could reveal evolutionary links to extant species. We used mass spectrometry to obtain protein sequences from bones of a 160,000- to 600,000-year-old extinct mastodon (Mammut americanum) and a 68-million-year-old dinosaur (Tyrannosaurus rex). The presence of T. rex sequences indicates that their peptide bonds were remarkably stable. Mass spectrometry can thus be used to determine unique sequences from ancient organisms from peptide fragmentation patterns, a valuable tool to study the evolution and adaptation of ancient taxa from which genomic sequences are unlikely to be obtained.

  11. Four signature motifs define the first class of structurally related large coiled-coil proteins in plants.

    Directory of Open Access Journals (Sweden)

    Meier Iris

    2002-04-01

    Full Text Available Abstract Background Animal and yeast proteins containing long coiled-coil domains are involved in attaching other proteins to the large, solid-state components of the cell. One subgroup of long coiled-coil proteins are the nuclear lamins, which are involved in attaching chromatin to the nuclear envelope and have recently been implicated in inherited human diseases. In contrast to other eukaryotes, long coiled-coil proteins have been barely investigated in plants. Results We have searched the completed Arabidopsis genome and have identified a family of structurally related long coiled-coil proteins. Filament-like plant proteins (FPP were identified by sequence similarity to a tomato cDNA that encodes a coiled-coil protein which interacts with the nuclear envelope-associated protein, MAF1. The FPP family is defined by four novel unique sequence motifs and by two clusters of long coiled-coil domains separated by a non-coiled-coil linker. All family members are expressed in a variety of Arabidopsis tissues. A homolog sharing the structural features was identified in the monocot rice, indicating conservation among angiosperms. Conclusion Except for myosins, this is the first characterization of a family of long coiled-coil proteins in plants. The tomato homolog of the FPP family binds in a yeast two-hybrid assay to a nuclear envelope-associated protein. This might suggest that FPP family members function in nuclear envelope biology. Because the full Arabidopsis genome does not appear to contain genes for lamins, it is of interest to investigate other long coiled-coil proteins, which might functionally replace lamins in the plant kingdom.

  12. The effects of different representations on static structure analysis of computer malware signatures.

    Science.gov (United States)

    Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

    2013-01-01

    The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka.

  13. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

    Directory of Open Access Journals (Sweden)

    Jun Wang

    2017-11-01

    Full Text Available Protein-protein interactions (PPIs play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs and a novel local conjoint triad description (LCTD feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

  14. Data-driven modelling of protein synthesis : A sequence perspective

    NARCIS (Netherlands)

    Gritsenko, A.

    2017-01-01

    Recent advances in DNA sequencing, synthesis and genetic engineering have enabled the introduction of choice DNA sequences into living cells. This is an exciting prospect for the field of industrial biotechnology, which aims at using microorganisms to produce foods, beverages, pharmaceuticals and

  15. Biological sequence analysis: probabilistic models of proteins and nucleic acids

    National Research Council Canada - National Science Library

    Durbin, Richard

    1998-01-01

    ... analysis methods are now based on principles of probabilistic modelling. Examples of such methods include the use of probabilistically derived score matrices to determine the significance of sequence alignments, the use of hidden Markov models as the basis for profile searches to identify distant members of sequence families, and the inference...

  16. Comparative analysis of the prion protein gene sequences in African lion.

    Science.gov (United States)

    Wu, Chang-De; Pang, Wan-Yong; Zhao, De-Ming

    2006-10-01

    The prion protein gene of African lion (Panthera Leo) was first cloned and polymorphisms screened. The results suggest that the prion protein gene of eight African lions is highly homogenous. The amino acid sequences of the prion protein (PrP) of all samples tested were identical. Four single nucleotide polymorphisms (C42T, C81A, C420T, T600C) in the prion protein gene (Prnp) of African lion were found, but no amino acid substitutions. Sequence analysis showed that the higher homology is observed to felis catus AF003087 (96.7%) and to sheep number M31313.1 (96.2%) Genbank accessed. With respect to all the mammalian prion protein sequences compared, the African lion prion protein sequence has three amino acid substitutions. The homology might in turn affect the potential intermolecular interactions critical for cross species transmission of prion disease.

  17. 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.

  18. Chaos game representation of functional protein sequences, and simulation and multifractal analysis of induced measures

    International Nuclear Information System (INIS)

    Zu-Guo, Yu; Qian-Jun, Xiao; Long, Shi; Jun-Wu, Yu; Anh, Vo

    2010-01-01

    Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation (CGR) of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems (RIFS) in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the D q curves, one sees that these functional protein sequences are not completely random. The D q of all linked functional proteins studied are multifractal-like and sufficiently smooth for the C q (analogous to specific heat) curves to be meaningful. Furthermore, the D q curves of the measure μ based on their CGRs for different orders to link the functional protein sequences are almost identical if q ≥ 0. Finally, the C q curves of all linked functional proteins resemble a classical phase transition at a critical point. (cross-disciplinary physics and related areas of science and technology)

  19. In Silico Characterization of Pectate Lyase Protein Sequences from Different Source Organisms

    Directory of Open Access Journals (Sweden)

    Amit Kumar Dubey

    2010-01-01

    Full Text Available A total of 121 protein sequences of pectate lyases were subjected to homology search, multiple sequence alignment, phylogenetic tree construction, and motif analysis. The phylogenetic tree constructed revealed different clusters based on different source organisms representing bacterial, fungal, plant, and nematode pectate lyases. The multiple accessions of bacterial, fungal, nematode, and plant pectate lyase protein sequences were placed closely revealing a sequence level similarity. The multiple sequence alignment of these pectate lyase protein sequences from different source organisms showed conserved regions at different stretches with maximum homology from amino acid residues 439–467, 715–816, and 829–910 which could be used for designing degenerate primers or probes specific for pectate lyases. The motif analysis revealed a conserved Pec_Lyase_C domain uniformly observed in all pectate lyases irrespective of variable sources suggesting its possible role in structural and enzymatic functions.

  20. Peptide Pattern Recognition for high-throughput protein sequence analysis and clustering

    DEFF Research Database (Denmark)

    Busk, Peter Kamp

    2017-01-01

    Large collections of protein sequences with divergent sequences are tedious to analyze for understanding their phylogenetic or structure-function relation. Peptide Pattern Recognition is an algorithm that was developed to facilitate this task but the previous version does only allow a limited...... number of sequences as input. I implemented Peptide Pattern Recognition as a multithread software designed to handle large numbers of sequences and perform analysis in a reasonable time frame. Benchmarking showed that the new implementation of Peptide Pattern Recognition is twenty times faster than...... the previous implementation on a small protein collection with 673 MAP kinase sequences. In addition, the new implementation could analyze a large protein collection with 48,570 Glycosyl Transferase family 20 sequences without reaching its upper limit on a desktop computer. Peptide Pattern Recognition...

  1. On the relationship between residue structural environment and sequence conservation in proteins.

    Science.gov (United States)

    Liu, Jen-Wei; Lin, Jau-Ji; Cheng, Chih-Wen; Lin, Yu-Feng; Hwang, Jenn-Kang; Huang, Tsun-Tsao

    2017-09-01

    Residues that are crucial to protein function or structure are usually evolutionarily conserved. To identify the important residues in protein, sequence conservation is estimated, and current methods rely upon the unbiased collection of homologous sequences. Surprisingly, our previous studies have shown that the sequence conservation is closely correlated with the weighted contact number (WCN), a measure of packing density for residue's structural environment, calculated only based on the C α positions of a protein structure. Moreover, studies have shown that sequence conservation is correlated with environment-related structural properties calculated based on different protein substructures, such as a protein's all atoms, backbone atoms, side-chain atoms, or side-chain centroid. To know whether the C α atomic positions are adequate to show the relationship between residue environment and sequence conservation or not, here we compared C α atoms with other substructures in their contributions to the sequence conservation. Our results show that C α positions are substantially equivalent to the other substructures in calculations of various measures of residue environment. As a result, the overlapping contributions between C α atoms and the other substructures are high, yielding similar structure-conservation relationship. Take the WCN as an example, the average overlapping contribution to sequence conservation is 87% between C α and all-atom substructures. These results indicate that only C α atoms of a protein structure could reflect sequence conservation at the residue level. © 2017 Wiley Periodicals, Inc.

  2. UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

    Science.gov (United States)

    Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

    2016-01-04

    The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence

    OpenAIRE

    Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

    2015-01-01

    Background: There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. Methods: All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinform...

  4. Fast computational methods for predicting protein structure from primary amino acid sequence

    Science.gov (United States)

    Agarwal, Pratul Kumar [Knoxville, TN

    2011-07-19

    The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.

  5. Seeing the trees through the forest : sequence-based homo- and heteromeric protein-protein interaction sites prediction using random forest

    NARCIS (Netherlands)

    Hou, Qingzhen; De Geest, Paul F.G.; Vranken, Wim F.; Heringa, Jaap; Feenstra, K. Anton

    2017-01-01

    Motivation: Genome sequencing is producing an ever-increasing amount of associated protein sequences. Few of these sequences have experimentally validated annotations, however, and computational predictions are becoming increasingly successful in producing such annotations. One key challenge remains

  6. Solving Classification Problems for Large Sets of Protein Sequences with the Example of Hox and ParaHox Proteins

    Directory of Open Access Journals (Sweden)

    Stefanie D. Hueber

    2016-02-01

    Full Text Available Phylogenetic methods are key to providing models for how a given protein family evolved. However, these methods run into difficulties when sequence divergence is either too low or too high. Here, we provide a case study of Hox and ParaHox proteins so that additional insights can be gained using a new computational approach to help solve old classification problems. For two (Gsx and Cdx out of three ParaHox proteins the assignments differ between the currently most established view and four alternative scenarios. We use a non-phylogenetic, pairwise-sequence-similarity-based method to assess which of the previous predictions, if any, are best supported by the sequence-similarity relationships between Hox and ParaHox proteins. The overall sequence-similarities show Gsx to be most similar to Hox2–3, and Cdx to be most similar to Hox4–8. The results indicate that a purely pairwise-sequence-similarity-based approach can provide additional information not only when phylogenetic inference methods have insufficient information to provide reliable classifications (as was shown previously for central Hox proteins, but also when the sequence variation is so high that the resulting phylogenetic reconstructions are likely plagued by long-branch-attraction artifacts.

  7. DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

    KAUST Repository

    Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert

    2017-01-01

    A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often

  8. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences

    Directory of Open Access Journals (Sweden)

    Ji-Yong An

    2016-01-01

    Full Text Available We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM model and Local Phase Quantization (LPQ to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

  9. CanisOme--The protein signatures of Canis lupus familiaris diseases.

    Science.gov (United States)

    Fernandes, Mónica; Rosa, Nuno; Esteves, Eduardo; Correia, Maria José; Arrais, Joel; Ribeiro, Paulo; Vala, Helena; Barros, Marlene

    2016-03-16

    Although the applications of Proteomics in Human Biomedicine have been explored for some time now, in animal and veterinary research, the potential of this resource has just started to be explored, especially when companion animal health is considered. In the last years, knowledge on the Canis lupus familiaris proteome has been accumulating in the literature and a resource compiling all this information and critically reviewing it was lacking. This article presents such a resource for the first time. CanisOme is a database of all proteins identified in Canis lupus familiaris tissues, either in health or in disease, annotated with information on the proteins present on the sample and on the donors. This database reunites information on 549 proteins, associated with 63 dog diseases and 33 dog breeds. Examples of how this information may be used to produce new hypothesis on disease mechanisms is presented both through the functional analysis of the proteins quantified in canine cutaneous mast cell tumors and through the study of the interactome of C. lupus familiaris and Leishmania infantum. Therefore, the usefulness of CanisOme for researchers looking for protein biomarkers in dogs and interested in a comprehensive analysis of disease mechanisms is demonstrated. This paper presents CanisOme, a database of proteomic studies with relevant protein annotation, allowing the enlightenment of disease mechanisms and the discovery of novel disease biomarkers for C. lupus familiaris. This knowledge is important not only for the improvement of animal health but also for the use of dogs as models for human health studies. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

    Science.gov (United States)

    Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

    1997-01-01

    SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.

  11. Analysis of long-range correlation in sequences data of proteins

    Directory of Open Access Journals (Sweden)

    ADRIANA ISVORAN

    2007-04-01

    Full Text Available The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment. For each series, the spectral coefficient, the scaling exponent and the Hurst coefficient were determined. The values obtained for these coefficients revealed non-randomness in the series of data.

  12. A novel amino acid and metabolomics signature in mice overexpressing muscle uncoupling protein 3

    Science.gov (United States)

    Uncoupling protein 3 (UCP3) is highly expressed in skeletal muscle and is known to lower mitochondrial reactive oxygen species and promote fatty acid oxidation; however, the global impact of UCP3 activity on skeletal muscle and whole body metabolism has not been extensively studied. We utilized unt...

  13. Signatures of RNA binding proteins globally coupled to effective microRNA target sites

    DEFF Research Database (Denmark)

    Jacobsen, Anders; Wen, Jiayu; Marks, Debora S

    2010-01-01

    MicroRNAs (miRNAs) and small interfering RNAs (siRNAs), bound to Argonaute proteins (RISC), destabilize mRNAs through base-pairing with the mRNA. However, the gene expression changes after perturbations of these small RNAs are only partially explained by predicted miRNA/siRNA targeting. Targeting...

  14. Small RNA sequencing reveals a comprehensive miRNA signature of BRCA1-associated high-grade serous ovarian cancer

    NARCIS (Netherlands)

    Brouwer, Jan; Kluiver, Joost; de Almeida, Rodrigo C.; Modderman, Rutger; Terpstra, Martijn; Kok, Klaas; Withoff, Sebo; Hollema, Harry; Reitsma, Welmoed; de Bock, Geertruida H.; Mourits, Marian J. E.; van den Berg, Anke

    2016-01-01

    AimsBRCA1 mutation carriers are at increased risk of developing high-grade serous ovarian cancer (HGSOC), a malignancy that originates from fallopian tube epithelium. We aimed to identify differentially expressed known and novel miRNAs in BRCA1-associated HGSOC. Methods Small RNA sequencing was

  15. A method for partitioning the information contained in a protein sequence between its structure and function.

    Science.gov (United States)

    Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

    2018-05-23

    Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

  16. PANTHER version 6: protein sequence and function evolution data with expanded representation of biological pathways

    OpenAIRE

    Mi, Huaiyu; Guo, Nan; Kejariwal, Anish; Thomas, Paul D.

    2006-01-01

    PANTHER is a freely available, comprehensive software system for relating protein sequence evolution to the evolution of specific protein functions and biological roles. Since 2005, there have been three main improvements to PANTHER. First, the sequences used to create evolutionary trees are carefully selected to provide coverage of phylogenetic as well as functional information. Second, PANTHER is now a member of the InterPro Consortium, and the PANTHER hidden markov Models (HMMs) are distri...

  17. 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

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

    KAUST Repository

    Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

    2015-01-01

    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

  19. 3D representations of amino acids—applications to protein sequence comparison and classification

    Directory of Open Access Journals (Sweden)

    Jie Li

    2014-08-01

    Full Text Available The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the representation of such a protein sequence facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D space derived from amino acid substitution matrices provides an adequate representation that can be used for direct comparison of protein sequences based on geometry. We measure the performance of such a representation in the context of the protein structural fold prediction problem. We compare the results of classifying different sets of proteins belonging to distinct structural folds against classifications of the same proteins obtained from sequence alone or directly from structural information. We find that sequence alone performs poorly as a structure classifier. We show in contrast that the use of the three dimensional representation of the sequences significantly improves the classification accuracy. We conclude with a discussion of the current limitations of such a representation and with a description of potential improvements.

  20. Structural insights and ab initio sequencing within the DING proteins family

    International Nuclear Information System (INIS)

    Elias, Mikael; Liebschner, Dorothee; Gotthard, Guillaume; Chabriere, Eric

    2011-01-01

    DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated

  1. Structural insights and ab initio sequencing within the DING proteins family

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Mikael, E-mail: mikael.elias@weizmann.ac.il [Weizmann Institute of Science, Rehovot (Israel); Liebschner, Dorothee [CRM2, Nancy Université (France); Gotthard, Guillaume; Chabriere, Eric [AFMB, Université Aix-Marseille II (France)

    2011-01-01

    DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated.

  2. DNA immunoprecipitation semiconductor sequencing (DIP-SC-seq) as a rapid method to generate genome wide epigenetic signatures

    OpenAIRE

    Thomson, John P.; Fawkes, Angie; Ottaviano, Raffaele; Hunter, Jennifer M.; Shukla, Ruchi; Mjoseng, Heidi K.; Clark, Richard; Coutts, Audrey; Murphy, Lee; Meehan, Richard R.

    2015-01-01

    Modification of DNA resulting in 5-methylcytosine (5 mC) or 5-hydroxymethylcytosine (5hmC) has been shown to influence the local chromatin environment and affect transcription. Although recent advances in next generation sequencing technology allow researchers to map epigenetic modifications across the genome, such experiments are often time-consuming and cost prohibitive. Here we present a rapid and cost effective method of generating genome wide DNA modification maps utilising commercially ...

  3. Feasibilty of zein proteins, simple sequence repeats and phenotypic ...

    African Journals Online (AJOL)

    Widespread adoption of quality protein maize (QPM), especially among tropical farming systems has been slow mainly due to the slow process of generating varieties with acceptable kernel quality and adaptability to different agroecological contexts. A molecular based foreground selection system for opaque 2 (o2), the ...

  4. Variation in the prion protein sequence in Dutch goat breeds

    NARCIS (Netherlands)

    Windig, J.J.; Hoving, R.A.H.; Priem, J.; Bossers, A.; Keulen, van L.J.M.; Langeveld, J.P.M.

    2016-01-01

    Scrapie is a neurodegenerative disease occurring in goats and sheep. Several haplotypes of the prion protein increase resistance to scrapie infection and may be used in selective breeding to help eradicate scrapie. In this study, frequencies of the allelic variants of the PrP gene are determined

  5. Sequence-based feature prediction and annotation of proteins

    DEFF Research Database (Denmark)

    Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea

    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....

  6. Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

    Directory of Open Access Journals (Sweden)

    Holly J Atkinson

    Full Text Available The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

  7. Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

    Science.gov (United States)

    Atkinson, Holly J; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C

    2009-01-01

    The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

  8. Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

    Directory of Open Access Journals (Sweden)

    Borodovsky Mark

    2006-03-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

  9. Towards radiological diagnosis of abdominal adhesions based on motion signatures derived from sequences of cine-MRI images.

    Science.gov (United States)

    Fenner, John; Wright, Benjamin; Emberey, Jonathan; Spencer, Paul; Gillott, Richard; Summers, Angela; Hutchinson, Charles; Lawford, Pat; Brenchley, Paul; Bardhan, Karna Dev

    2014-06-01

    This paper reports novel development and preliminary application of an image registration technique for diagnosis of abdominal adhesions imaged with cine-MRI (cMRI). Adhesions can severely compromise the movement and physiological function of the abdominal contents, and their presence is difficult to detect. The image registration approach presented here is designed to expose anomalies in movement of the abdominal organs, providing a movement signature that is indicative of underlying structural abnormalities. Validation of the technique was performed using structurally based in vitro and in silico models, supported with Receiver Operating Characteristic (ROC) methods. For the more challenging cases presented to the small cohort of 4 observers, the AUC (area under curve) improved from a mean value of 0.67 ± 0.02 (without image registration assistance) to a value of 0.87 ± 0.02 when image registration support was included. Also, in these cases, a reduction in time to diagnosis was observed, decreasing by between 20% and 50%. These results provided sufficient confidence to apply the image registration diagnostic protocol to sample magnetic resonance imaging data from healthy volunteers as well as a patient suffering from encapsulating peritoneal sclerosis (an extreme form of adhesions) where immobilization of the gut by cocooning of the small bowel is observed. The results as a whole support the hypothesis that movement analysis using image registration offers a possible method for detecting underlying structural anomalies and encourages further investigation. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  10. Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

    Science.gov (United States)

    Neuwald, Andrew F

    2009-08-01

    The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.

  11. Adhesive proteins of stalked and acorn barnacles display homology with low sequence similarities.

    Directory of Open Access Journals (Sweden)

    Jaimie-Leigh Jonker

    Full Text Available Barnacle adhesion underwater is an important phenomenon to understand for the prevention of biofouling and potential biotechnological innovations, yet so far, identifying what makes barnacle glue proteins 'sticky' has proved elusive. Examination of a broad range of species within the barnacles may be instructive to identify conserved adhesive domains. We add to extensive information from the acorn barnacles (order Sessilia by providing the first protein analysis of a stalked barnacle adhesive, Lepas anatifera (order Lepadiformes. It was possible to separate the L. anatifera adhesive into at least 10 protein bands using SDS-PAGE. Intense bands were present at approximately 30, 70, 90 and 110 kilodaltons (kDa. Mass spectrometry for protein identification was followed by de novo sequencing which detected 52 peptides of 7-16 amino acids in length. None of the peptides matched published or unpublished transcriptome sequences, but some amino acid sequence similarity was apparent between L. anatifera and closely-related Dosima fascicularis. Antibodies against two acorn barnacle proteins (ab-cp-52k and ab-cp-68k showed cross-reactivity in the adhesive glands of L. anatifera. We also analysed the similarity of adhesive proteins across several barnacle taxa, including Pollicipes pollicipes (a stalked barnacle in the order Scalpelliformes. Sequence alignment of published expressed sequence tags clearly indicated that P. pollicipes possesses homologues for the 19 kDa and 100 kDa proteins in acorn barnacles. Homology aside, sequence similarity in amino acid and gene sequences tended to decline as taxonomic distance increased, with minimum similarities of 18-26%, depending on the gene. The results indicate that some adhesive proteins (e.g. 100 kDa are more conserved within barnacles than others (20 kDa.

  12. ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

    International Nuclear Information System (INIS)

    Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

    2007-01-01

    The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

  13. MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

    Directory of Open Access Journals (Sweden)

    Kuczmarski Thomas A

    2006-10-01

    Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein

  14. Cloning and sequence analysis of cDNA coding for rat nucleolar protein C23

    International Nuclear Information System (INIS)

    Ghaffari, S.H.; Olson, M.O.J.

    1986-01-01

    Using synthetic oligonucleotides as primers and probes, the authors have isolated and sequenced cDNA clones encoding protein C23, a putative nucleolus organizer protein. Poly(A + ) RNA was isolated from rat Novikoff hepatoma cells and enriched in C23 mRNA by sucrose density gradient ultracentrifugation. Two deoxyoligonuleotides, a 48- and a 27-mer, were synthesized on the basis of amino acid sequence from the C-terminal half of protein C23 and cDNA sequence data from CHO cell protein. The 48-mer was used a primer for synthesis of cDNA which was then inserted into plasmid pUC9. Transformed bacterial colonies were screened by hybridization with 32 P labeled 27-mer. Two clones among 5000 gave a strong positive signal. Plasmid DNAs from these clones were purified and characterized by blotting and nucleotide sequence analysis. The length of C23 mRNA was estimated to be 3200 bases in a northern blot analysis. The sequence of a 267 b.p. insert shows high homology with the CHO cDNA with only 9 nucleotide differences and an identical amino acid sequence. These studies indicate that this region of the protein is highly conserved

  15. Application of native signal sequences for recombinant proteins secretion in Pichia pastoris

    DEFF Research Database (Denmark)

    Borodina, Irina; Do, Duy Duc; Eriksen, Jens C.

    Background Methylotrophic yeast Pichia pastoris is widely used for recombinant protein production, largely due to its ability to secrete correctly folded heterologous proteins to the fermentation medium. Secretion is usually achieved by cloning the recombinant gene after a leader sequence, where...... alpha‐mating factor (MF) prepropeptide from Saccharomyces cerevisiae is most commonly used. Our aim was to test whether signal peptides from P. pastoris native secreted proteins could be used to direct secretion of recombinant proteins. Results Eleven native signal peptides from P. pastoris were tested...... by optimization of expression of three different proteins in P. pastoris. Conclusions Native signal peptides from P. pastoris can be used to direct secretion of recombinant proteins. A novel USER‐based P. pastoris system allows easy cloning of protein‐coding gene with the promoter and leader sequence of choice....

  16. Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

    Science.gov (United States)

    Garrido-Martín, Diego; Pazos, Florencio

    2018-02-27

    The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.

  17. Interactions of rat repetitive sequence MspI8 with nuclear matrix proteins during spermatogenesis

    International Nuclear Information System (INIS)

    Rogolinski, J.; Widlak, P.; Rzeszowska-Wolny, J.

    1996-01-01

    Using the Southwestern blot analysis we have studied the interactions between rat repetitive sequence MspI8 and the nuclear matrix proteins of rats testis cells. Starting from 2 weeks the young to adult animal showed differences in type of testis nuclear matrix proteins recognizing the MspI8 sequence. The same sets of nuclear matrix proteins were detected in some enriched in spermatocytes and spermatids and obtained after fractionation of cells of adult animal by the velocity sedimentation technique. (author). 21 refs, 5 figs

  18. GenProBiS: web server for mapping of sequence variants to protein binding sites.

    Science.gov (United States)

    Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

    2017-07-03

    Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. Prediction of protein hydration sites from sequence by modular neural networks

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik

    1998-01-01

    The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

  20. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

    Directory of Open Access Journals (Sweden)

    Huilin Wang

    Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

  1. Exploring sequence characteristics related to high-level production of secreted proteins in Aspergillus niger.

    Directory of Open Access Journals (Sweden)

    Bastiaan A van den Berg

    Full Text Available Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.

  2. Protein sequences clustering of herpes virus by using Tribe Markov clustering (Tribe-MCL)

    Science.gov (United States)

    Bustamam, A.; Siswantining, T.; Febriyani, N. L.; Novitasari, I. D.; Cahyaningrum, R. D.

    2017-07-01

    The herpes virus can be found anywhere and one of the important characteristics is its ability to cause acute and chronic infection at certain times so as a result of the infection allows severe complications occurred. The herpes virus is composed of DNA containing protein and wrapped by glycoproteins. In this work, the Herpes viruses family is classified and analyzed by clustering their protein-sequence using Tribe Markov Clustering (Tribe-MCL) algorithm. Tribe-MCL is an efficient clustering method based on the theory of Markov chains, to classify protein families from protein sequences using pre-computed sequence similarity information. We implement the Tribe-MCL algorithm using an open source program of R. We select 24 protein sequences of Herpes virus obtained from NCBI database. The dataset consists of three types of glycoprotein B, F, and H. Each type has eight herpes virus that infected humans. Based on our simulation using different inflation factor r=1.5, 2, 3 we find a various number of the clusters results. The greater the inflation factor the greater the number of their clusters. Each protein will grouped together in the same type of protein.

  3. Coilin, the signature protein of Cajal bodies, differentially modulates the interactions of plants with viruses in widely different taxa.

    Science.gov (United States)

    Shaw, Jane; Love, Andrew J; Makarova, Svetlana S; Kalinina, Natalia O; Harrison, Bryan D; Taliansky, Michael E

    2014-01-01

    Cajal bodies (CBs) are distinct nuclear bodies physically and functionally associated with the nucleolus. In addition to their traditional function in coordinating maturation of certain nuclear RNAs, CBs participate in cell cycle regulation, development, and regulation of stress responses. A key "signature" component of CBs is coilin, the scaffolding protein essential for CB formation and function. Using an RNA silencing (loss-of-function) approach, we describe here new phenomena whereby coilin also affects, directly or indirectly, a variety of interactions between host plants and viruses that have RNA or DNA genomes. Moreover, the effects of coilin on these interactions are manifested differently: coilin contributes to plant defense against tobacco rattle virus (tobravirus), tomato black ring virus (nepovirus), barley stripe mosaic virus (hordeivirus), and tomato golden mosaic virus (begomovirus). In contrast, with potato virus Y (potyvirus) and turnip vein clearing virus (tobamovirus), coilin serves to increase virus pathogenicity. These findings show that interactions with coilin (or CBs) may involve diverse mechanisms with different viruses and that these mechanisms act at different phases of virus infection. Thus, coilin (CBs) has novel, unexpected natural functions that may be recruited or subverted by plant viruses for their own needs or, in contrast, are involved in plant defense mechanisms that suppress host susceptibility to the viruses.

  4. The N-terminal sequence of ribosomal protein L10 from the archaebacterium Halobacterium marismortui and its relationship to eubacterial protein L6 and other ribosomal proteins.

    Science.gov (United States)

    Dijk, J; van den Broek, R; Nasiulas, G; Beck, A; Reinhardt, R; Wittmann-Liebold, B

    1987-08-01

    The amino-terminal sequence of ribosomal protein L10 from Halobacterium marismortui has been determined up to residue 54, using both a liquid- and a gas-phase sequenator. The two sequences are in good agreement. The protein is clearly homologous to protein HcuL10 from the related strain Halobacterium cutirubrum. Furthermore, a weaker but distinct homology to ribosomal protein L6 from Escherichia coli and Bacillus stearothermophilus can be detected. In addition to 7 identical amino acids in the first 36 residues in all four sequences a number of conservative replacements occurs, of mainly hydrophobic amino acids. In this common region the pattern of conserved amino acids suggests the presence of a beta-alpha fold as it occurs in ribosomal proteins L12 and L30. Furthermore, several potential cases of homology to other ribosomal components of the three ur-kingdoms have been found.

  5. Nucleotide sequence of the coat protein gene of the Skierniewice isolate of plum pox virus (PPV)

    International Nuclear Information System (INIS)

    Wypijewski, K.; Musial, W.; Augustyniak, J.; Malinowski, T.

    1994-01-01

    The coat protein (CP) gene of the Skierniewice isolate of plum pox virus (PPV-S) has been amplified using the reverse transcription - polymerase chain reaction (RT-PCR), cloned and sequenced. The nucleotide sequence of the gene and the deduced amino-acid sequences of PPV-S CP were compared with those of other PPV strains. The nucleotide sequence showed very high homology to most of the published sequences. The motif: Asp-Ala-Gly (DAG), important for the aphid transmissibility, was present in the amino-acid sequence. Our isolate did not react in ELISA with monoclonal antibodies MAb06 supposed to be specific for PPV-D. (author). 32 refs, 1 fig., 2 tabs

  6. Predicting protein amidation sites by orchestrating amino acid sequence features

    Science.gov (United States)

    Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

    2017-08-01

    Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

  7. Revised Mimivirus major capsid protein sequence reveals intron-containing gene structure and extra domain

    Directory of Open Access Journals (Sweden)

    Suzan-Monti Marie

    2009-05-01

    Full Text Available Abstract Background Acanthamoebae polyphaga Mimivirus (APM is the largest known dsDNA virus. The viral particle has a nearly icosahedral structure with an internal capsid shell surrounded with a dense layer of fibrils. A Capsid protein sequence, D13L, was deduced from the APM L425 coding gene and was shown to be the most abundant protein found within the viral particle. However this protein remained poorly characterised until now. A revised protein sequence deposited in a database suggested an additional N-terminal stretch of 142 amino acids missing from the original deduced sequence. This result led us to investigate the L425 gene structure and the biochemical properties of the complete APM major Capsid protein. Results This study describes the full length 3430 bp Capsid coding gene and characterises the 593 amino acids long corresponding Capsid protein 1. The recombinant full length protein allowed the production of a specific monoclonal antibody able to detect the Capsid protein 1 within the viral particle. This protein appeared to be post-translationnally modified by glycosylation and phosphorylation. We proposed a secondary structure prediction of APM Capsid protein 1 compared to the Capsid protein structure of Paramecium Bursaria Chlorella Virus 1, another member of the Nucleo-Cytoplasmic Large DNA virus family. Conclusion The characterisation of the full length L425 Capsid coding gene of Acanthamoebae polyphaga Mimivirus provides new insights into the structure of the main Capsid protein. The production of a full length recombinant protein will be useful for further structural studies.

  8. EST-PAC a web package for EST annotation and protein sequence prediction

    Directory of Open Access Journals (Sweden)

    Strahm Yvan

    2006-10-01

    Full Text Available Abstract With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1 searching local or remote biological databases for sequence similarities using Blast services, 2 predicting protein coding sequence from EST data and, 3 annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

  9. Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

    Science.gov (United States)

    Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

    2016-09-01

    S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.

  10. Extreme sequence divergence but conserved ligand-binding specificity in Streptococcus pyogenes M protein.

    Directory of Open Access Journals (Sweden)

    2006-05-01

    Full Text Available Many pathogenic microorganisms evade host immunity through extensive sequence variability in a protein region targeted by protective antibodies. In spite of the sequence variability, a variable region commonly retains an important ligand-binding function, reflected in the presence of a highly conserved sequence motif. Here, we analyze the limits of sequence divergence in a ligand-binding region by characterizing the hypervariable region (HVR of Streptococcus pyogenes M protein. Our studies were focused on HVRs that bind the human complement regulator C4b-binding protein (C4BP, a ligand that confers phagocytosis resistance. A previous comparison of C4BP-binding HVRs identified residue identities that could be part of a binding motif, but the extended analysis reported here shows that no residue identities remain when additional C4BP-binding HVRs are included. Characterization of the HVR in the M22 protein indicated that two relatively conserved Leu residues are essential for C4BP binding, but these residues are probably core residues in a coiled-coil, implying that they do not directly contribute to binding. In contrast, substitution of either of two relatively conserved Glu residues, predicted to be solvent-exposed, had no effect on C4BP binding, although each of these changes had a major effect on the antigenic properties of the HVR. Together, these findings show that HVRs of M proteins have an extraordinary capacity for sequence divergence and antigenic variability while retaining a specific ligand-binding function.

  11. Identification of Molecular Tumor Markers in Renal Cell Carcinomas with TFE3 Protein Expression by RNA Sequencing

    Directory of Open Access Journals (Sweden)

    Dorothee Pflueger

    2013-11-01

    Full Text Available TFE3 translocation renal cell carcinoma (tRCC is defined by chromosomal translocations involving the TFE3 transcription factor at chromosome Xp11.2. Genetically proven TFE3 tRCCs have a broad histologic spectrum with overlapping features to other renal tumor subtypes. In this study,we aimed for characterizing RCC with TFE3 protein expression. Using next-generation whole transcriptome sequencing (RNA-Seq as a discovery tool, we analyzed fusion transcripts, gene expression profile, and somatic mutations in frozen tissue of one TFE3 tRCC. By applying a computational analysis developed to call chimeric RNA molecules from paired-end RNA-Seq data, we confirmed the known TFE3 translocation. Its fusion partner SFPQ has already been described as fusion partner in tRCCs. In addition, an RNAread-through chimera between TMED6 and COG8 as well as MET and KDR (VEGFR2 point mutations were identified. An EGFR mutation, but no chromosomal rearrangements, was identified in a control group of five clear cell RCCs (ccRCCs. The TFE3 tRCC could be clearly distinguished from the ccRCCs by RNA-Seq gene expression measurements using a previously reported tRCC gene signature. In validation experiments using reverse transcription-PCR, TMED6-COG8 chimera expression was significantly higher in nine TFE3 translocated and six TFE3-expressing/non-translocated RCCs than in 24 ccRCCs (P<.001 and 22 papillaryRCCs (P<.05-.07. Immunohistochemical analysis of selected genes from the tRCC gene signature showed significantly higher eukaryotic translation elongation factor 1 alpha 2 (EEF1A2 and Contactin 3 (CNTN3 expression in 16 TFE3 translocated and six TFE3-expressing/non-translocated RCCs than in over 200 ccRCCs (P < .0001, both.

  12. Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening.

    Science.gov (United States)

    Han, Guangchun; Zhao, Wei; Song, Xiaofeng; Kwok-Shing Ng, Patrick; Karam, Jose A; Jonasch, Eric; Mills, Gordon B; Zhao, Zhongming; Ding, Zhiyong; Jia, Peilin

    2017-10-03

    In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC's prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients' survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These

  13. Rapid detection and purification of sequence specific DNA binding proteins using magnetic separation

    Directory of Open Access Journals (Sweden)

    TIJANA SAVIC

    2006-02-01

    Full Text Available In this paper, a method for the rapid identification and purification of sequence specific DNA binding proteins based on magnetic separation is presented. This method was applied to confirm the binding of the human recombinant USF1 protein to its putative binding site (E-box within the human SOX3 protomer. It has been shown that biotinylated DNA attached to streptavidin magnetic particles specifically binds the USF1 protein in the presence of competitor DNA. It has also been demonstrated that the protein could be successfully eluted from the beads, in high yield and with restored DNA binding activity. The advantage of these procedures is that they could be applied for the identification and purification of any high-affinity sequence-specific DNA binding protein with only minor modifications.

  14. Isolation and N-terminal sequencing of a novel cadmium-binding protein from Boletus edulis

    Science.gov (United States)

    Collin-Hansen, C.; Andersen, R. A.; Steinnes, E.

    2003-05-01

    A Cd-binding protein was isolated from the popular edible mushroom Boletus edulis, which is a hyperaccumulator of both Cd and Hg. Wild-growing samples of B. edulis were collected from soils rich in Cd. Cd radiotracer was added to the crude protein preparation obtained from ethanol precipitation of heat-treated cytosol. Proteins were then further separated in two consecutive steps; gel filtration and anion exchange chromatography. In both steps the Cd radiotracer profile showed only one distinct peak, which corresponded well with the profiles of endogenous Cd obtained by atomic absorption spectrophotometry (AAS). Concentrations of the essential elements Cu and Zn were low in the protein fractions high in Cd. N-terminal sequencing performed on the Cd-binding protein fractions revealed a protein with a novel amino acid sequence, which contained aromatic amino acids as well as proline. Both the N-terminal sequencing and spectrofluorimetric analysis with EDTA and ABD-F (4-aminosulfonyl-7-fluoro-2, 1, 3-benzoxadiazole) failed to detect cysteine in the Cd-binding fractions. These findings conclude that the novel protein does not belong to the metallothionein family. The results suggest a role for the protein in Cd transport and storage, and they are of importance in view of toxicology and food chemistry, but also for environmental protection.

  15. Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

    Science.gov (United States)

    Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

    2018-01-01

    Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

  16. Signature Balancing

    NARCIS (Netherlands)

    Noordkamp, H.W.; Brink, M. van den

    2006-01-01

    Signatures are an important part of the design of a ship. In an ideal situation, signatures must be as low as possible. However, due to budget constraints it is most unlikely to reach this ideal situation. The arising question is which levels of signatures are optimal given the different scenarios

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

    Directory of Open Access Journals (Sweden)

    Sainudiin Raazesh

    2006-03-01

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

  18. Rapid evolution of the sequences and gene repertoires of secreted proteins in bacteria.

    Directory of Open Access Journals (Sweden)

    Teresa Nogueira

    Full Text Available Proteins secreted to the extracellular environment or to the periphery of the cell envelope, the secretome, play essential roles in foraging, antagonistic and mutualistic interactions. We hypothesize that arms races, genetic conflicts and varying selective pressures should lead to the rapid change of sequences and gene repertoires of the secretome. The analysis of 42 bacterial pan-genomes shows that secreted, and especially extracellular proteins, are predominantly encoded in the accessory genome, i.e. among genes not ubiquitous within the clade. Genes encoding outer membrane proteins might engage more frequently in intra-chromosomal gene conversion because they are more often in multi-genic families. The gene sequences encoding the secretome evolve faster than the rest of the genome and in particular at non-synonymous positions. Cell wall proteins in Firmicutes evolve particularly fast when compared with outer membrane proteins of Proteobacteria. Virulence factors are over-represented in the secretome, notably in outer membrane proteins, but cell localization explains more of the variance in substitution rates and gene repertoires than sequence homology to known virulence factors. Accordingly, the repertoires and sequences of the genes encoding the secretome change fast in the clades of obligatory and facultative pathogens and also in the clades of mutualists and free-living bacteria. Our study shows that cell localization shapes genome evolution. In agreement with our hypothesis, the repertoires and the sequences of genes encoding secreted proteins evolve fast. The particularly rapid change of extracellular proteins suggests that these public goods are key players in bacterial adaptation.

  19. Variation in the prion protein sequence in Dutch goat breeds.

    Science.gov (United States)

    Windig, J J; Hoving, R A H; Priem, J; Bossers, A; van Keulen, L J M; Langeveld, J P M

    2016-10-01

    Scrapie is a neurodegenerative disease occurring in goats and sheep. Several haplotypes of the prion protein increase resistance to scrapie infection and may be used in selective breeding to help eradicate scrapie. In this study, frequencies of the allelic variants of the PrP gene are determined for six goat breeds in the Netherlands. Overall frequencies in Dutch goats were determined from 768 brain tissue samples in 2005, 766 in 2008 and 300 in 2012, derived from random sampling for the national scrapie surveillance without knowledge of the breed. Breed specific frequencies were determined in the winter 2013/2014 by sampling 300 breeding animals from the main breeders of the different breeds. Detailed analysis of the scrapie-resistant K222 haplotype was carried out in 2014 for 220 Dutch Toggenburger goats and in 2015 for 942 goats from the Saanen derived White Goat breed. Nine haplotypes were identified in the Dutch breeds. Frequencies for non-wild type haplotypes were generally low. Exception was the K222 haplotype in the Dutch Toggenburger (29%) and the S146 haplotype in the Nubian and Boer breeds (respectively 7 and 31%). The frequency of the K222 haplotype in the Toggenburger was higher than for any other breed reported in literature, while for the White Goat breed it was with 3.1% similar to frequencies of other Saanen or Saanen derived breeds. Further evidence was found for the existence of two M142 haplotypes, M142 /S240 and M142 /P240 . Breeds vary in haplotype frequencies but frequencies of resistant genotypes are generally low and consequently selective breeding for scrapie resistance can only be slow but will benefit from animals identified in this study. The unexpectedly high frequency of the K222 haplotype in the Dutch Toggenburger underlines the need for conservation of rare breeds in order to conserve genetic diversity rare or absent in other breeds. © 2016 Blackwell Verlag GmbH.

  20. Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

    Directory of Open Access Journals (Sweden)

    Ruan Jishou

    2007-04-01

    Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are

  1. A two-step recognition of signal sequences determines the translocation efficiency of proteins.

    OpenAIRE

    Belin, D; Bost, S; Vassalli, J D; Strub, K

    1996-01-01

    The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated...

  2. DIALIGN: multiple DNA and protein sequence alignment at BiBiServ.

    OpenAIRE

    Morgenstern, Burkhard

    2004-01-01

    DIALIGN is a widely used software tool for multiple DNA and protein sequence alignment. The program combines local and global alignment features and can therefore be applied to sequence data that cannot be correctly aligned by more traditional approaches. DIALIGN is available online through Bielefeld Bioinformatics Server (BiBiServ). The downloadable version of the program offers several new program features. To compare the output of different alignment programs, we developed the program AltA...

  3. TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

    Science.gov (United States)

    Richard, François D; Kajava, Andrey V

    2014-06-01

    The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

    Science.gov (United States)

    Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

    2016-12-01

    Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures. © 2016 The Protein Society.

  5. RSARF: Prediction of residue solvent accessibility from protein sequence using random forest method

    KAUST Repository

    Ganesan, Pugalenthi; Kandaswamy, Krishna Kumar Umar; Chou -, Kuochen; Vivekanandan, Saravanan; Kolatkar, Prasanna R.

    2012-01-01

    Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/. - See more at: http://www.eurekaselect.com/89216/article#sthash.pwVGFUjq.dpuf

  6. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

    Science.gov (United States)

    Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-09-07

    Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Sequence preservation of osteocalcin protein and mitochondrial DNA in bison bones older than 55 ka

    Science.gov (United States)

    Nielsen-Marsh, Christina M.; Ostrom, Peggy H.; Gandhi, Hasand; Shapiro, Beth; Cooper, Alan; Hauschka, Peter V.; Collins, Matthew J.

    2002-12-01

    We report the first complete sequences of the protein osteocalcin from small amounts (20 mg) of two bison bone (Bison priscus) dated to older than 55.6 ka and older than 58.9 ka. Osteocalcin was purified using new gravity columns (never exposed to protein) followed by microbore reversed-phase high-performance liquid chromatography. Sequencing of osteocalcin employed two methods of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS): peptide mass mapping (PMM) and post-source decay (PSD). The PMM shows that ancient and modern bison osteocalcin have the same mass to charge (m/z) distribution, indicating an identical protein sequence and absence of diagenetic products. This was confirmed by PSD of the m/z 2066 tryptic peptide (residues 1 19); the mass spectra from ancient and modern peptides were identical. The 129 mass unit difference in the molecular ion between cow (Bos taurus) and bison is caused by a single amino-acid substitution between the taxa (Trp in cow is replaced by Gly in bison at residue 5). Bison mitochondrial control region DNA sequences were obtained from the older than 55.6 ka fossil. These results suggest that DNA and protein sequences can be used to directly investigate molecular phylogenies over a considerable time period, the absolute limit of which is yet to be determined.

  8. Efficient use of unlabeled data for protein sequence classification: a comparative study.

    Science.gov (United States)

    Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

    2009-04-29

    Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.

  9. RNA-Sequencing Reveals Unique Transcriptional Signatures of Running and Running-Independent Environmental Enrichment in the Adult Mouse Dentate Gyrus

    Directory of Open Access Journals (Sweden)

    Catherine-Alexandra Grégoire

    2018-04-01

    Full Text Available Environmental enrichment (EE is a powerful stimulus of brain plasticity and is among the most accessible treatment options for brain disease. In rodents, EE is modeled using multi-factorial environments that include running, social interactions, and/or complex surroundings. Here, we show that running and running-independent EE differentially affect the hippocampal dentate gyrus (DG, a brain region critical for learning and memory. Outbred male CD1 mice housed individually with a voluntary running disk showed improved spatial memory in the radial arm maze compared to individually- or socially-housed mice with a locked disk. We therefore used RNA sequencing to perform an unbiased interrogation of DG gene expression in mice exposed to either a voluntary running disk (RUN, a locked disk (LD, or a locked disk plus social enrichment and tunnels [i.e., a running-independent complex environment (CE]. RNA sequencing revealed that RUN and CE mice showed distinct, non-overlapping patterns of transcriptomic changes versus the LD control. Bio-informatics uncovered that the RUN and CE environments modulate separate transcriptional networks, biological processes, cellular compartments and molecular pathways, with RUN preferentially regulating synaptic and growth-related pathways and CE altering extracellular matrix-related functions. Within the RUN group, high-distance runners also showed selective stress pathway alterations that correlated with a drastic decline in overall transcriptional changes, suggesting that excess running causes a stress-induced suppression of running’s genetic effects. Our findings reveal stimulus-dependent transcriptional signatures of EE on the DG, and provide a resource for generating unbiased, data-driven hypotheses for novel mediators of EE-induced cognitive changes.

  10. RNA-Sequencing Reveals Unique Transcriptional Signatures of Running and Running-Independent Environmental Enrichment in the Adult Mouse Dentate Gyrus.

    Science.gov (United States)

    Grégoire, Catherine-Alexandra; Tobin, Stephanie; Goldenstein, Brianna L; Samarut, Éric; Leclerc, Andréanne; Aumont, Anne; Drapeau, Pierre; Fulton, Stephanie; Fernandes, Karl J L

    2018-01-01

    Environmental enrichment (EE) is a powerful stimulus of brain plasticity and is among the most accessible treatment options for brain disease. In rodents, EE is modeled using multi-factorial environments that include running, social interactions, and/or complex surroundings. Here, we show that running and running-independent EE differentially affect the hippocampal dentate gyrus (DG), a brain region critical for learning and memory. Outbred male CD1 mice housed individually with a voluntary running disk showed improved spatial memory in the radial arm maze compared to individually- or socially-housed mice with a locked disk. We therefore used RNA sequencing to perform an unbiased interrogation of DG gene expression in mice exposed to either a voluntary running disk (RUN), a locked disk (LD), or a locked disk plus social enrichment and tunnels [i.e., a running-independent complex environment (CE)]. RNA sequencing revealed that RUN and CE mice showed distinct, non-overlapping patterns of transcriptomic changes versus the LD control. Bio-informatics uncovered that the RUN and CE environments modulate separate transcriptional networks, biological processes, cellular compartments and molecular pathways, with RUN preferentially regulating synaptic and growth-related pathways and CE altering extracellular matrix-related functions. Within the RUN group, high-distance runners also showed selective stress pathway alterations that correlated with a drastic decline in overall transcriptional changes, suggesting that excess running causes a stress-induced suppression of running's genetic effects. Our findings reveal stimulus-dependent transcriptional signatures of EE on the DG, and provide a resource for generating unbiased, data-driven hypotheses for novel mediators of EE-induced cognitive changes.

  11. The nucleotide sequence of human transition protein 1 cDNA

    Energy Technology Data Exchange (ETDEWEB)

    Luerssen, H; Hoyer-Fender, S; Engel, W [Universitaet Goettingen (West Germany)

    1988-08-11

    The authors have screened a human testis cDNA library with an oligonucleotide of 81 mer prepared according to a part of the published nucleotide sequence of the rat transition protein TP 1. They have isolated a cDNA clone with the length of 441 bp containing the coding region of 162 bp for human transition protein 1. There is about 84% homology in the coding region of the sequence compared to rat. The human cDNA-clone encodes a polypeptide of 54 amino acids of which 7 are different to that of rat.

  12. Unraveling the sequence and structure of the protein osteocalcin from a 42 ka fossil horse

    Science.gov (United States)

    Ostrom, Peggy H.; Gandhi, Hasand; Strahler, John R.; Walker, Angela K.; Andrews, Philip C.; Leykam, Joseph; Stafford, Thomas W.; Kelly, Robert L.; Walker, Danny N.; Buckley, Mike; Humpula, James

    2006-04-01

    We report the first complete amino acid sequence and evidence of secondary structure for osteocalcin from a temperate fossil. The osteocalcin derives from a 42 ka equid bone excavated from Juniper Cave, Wyoming. Results were determined by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-MS) and Edman sequencing with independent confirmation of the sequence in two laboratories. The ancient sequence was compared to that of three modern taxa: horse ( Equus caballus), zebra ( Equus grevyi), and donkey ( Equus asinus). Although there was no difference in sequence among modern taxa, MALDI-MS and Edman sequencing show that residues 48 and 49 of our modern horse are Thr, Ala rather than Pro, Val as previously reported (Carstanjen B., Wattiez, R., Armory, H., Lepage, O.M., Remy, B., 2002. Isolation and characterization of equine osteocalcin. Ann. Med. Vet.146(1), 31-38). MALDI-MS and Edman sequencing data indicate that the osteocalcin sequence of the 42 ka fossil is similar to that of modern horse. Previously inaccessible structural attributes for ancient osteocalcin were observed. Glu 39 rather than Gln 39 is consistent with deamidation, a process known to occur during fossilization and aging. Two post-translational modifications were documented: Hyp 9 and a disulfide bridge. The latter suggests at least partial retention of secondary structure. As has been done for ancient DNA research, we recommend standards for preparation and criteria for authenticating results of ancient protein sequencing.

  13. High dimensional and high resolution pulse sequences for backbone resonance assignment of intrinsically disordered proteins

    Energy Technology Data Exchange (ETDEWEB)

    Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor, E-mail: kozmin@chem.uw.edu.pl [University of Warsaw, Faculty of Chemistry (Poland); Sanderova, Hana; Krasny, Libor [Institute of Microbiology, Academy of Sciences of the Czech Republic, Laboratory of Molecular Genetics of Bacteria, Department of Bacteriology (Czech Republic)

    2012-04-15

    Four novel 5D (HACA(N)CONH, HNCOCACB, (HACA)CON(CA)CONH, (H)NCO(NCA)CONH), and one 6D ((H)NCO(N)CACONH) NMR pulse sequences are proposed. The new experiments employ non-uniform sampling that enables achieving high resolution in indirectly detected dimensions. The experiments facilitate resonance assignment of intrinsically disordered proteins. The novel pulse sequences were successfully tested using {delta} subunit (20 kDa) of Bacillus subtilis RNA polymerase that has an 81-amino acid disordered part containing various repetitive sequences.

  14. Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein.

    Science.gov (United States)

    Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

    2015-10-01

    The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  15. Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein

    Science.gov (United States)

    Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

    2015-01-01

    The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. PMID:26175306

  16. Protein backbone angle restraints from searching a database for chemical shift and sequence homology

    Energy Technology Data Exchange (ETDEWEB)

    Cornilescu, Gabriel; Delaglio, Frank; Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

    1999-03-15

    Chemical shifts of backbone atoms in proteins are exquisitely sensitive to local conformation, and homologous proteins show quite similar patterns of secondary chemical shifts. The inverse of this relation is used to search a database for triplets of adjacent residues with secondary chemical shifts and sequence similarity which provide the best match to the query triplet of interest. The database contains 13C{alpha}, 13C{beta}, 13C', 1H{alpha} and 15N chemical shifts for 20 proteins for which a high resolution X-ray structure is available. The computer program TALOS was developed to search this database for strings of residues with chemical shift and residue type homology. The relative importance of the weighting factors attached to the secondary chemical shifts of the five types of resonances relative to that of sequence similarity was optimized empirically. TALOS yields the 10 triplets which have the closest similarity in secondary chemical shift and amino acid sequence to those of the query sequence. If the central residues in these 10 triplets exhibit similar {phi} and {psi} backbone angles, their averages can reliably be used as angular restraints for the protein whose structure is being studied. Tests carried out for proteins of known structure indicate that the root-mean-square difference (rmsd) between the output of TALOS and the X-ray derived backbone angles is about 15 deg. Approximately 3% of the predictions made by TALOS are found to be in error.

  17. Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

    Science.gov (United States)

    De Groote, Mary A; Sterling, David G; Hraha, Thomas; Russell, Theresa M; Green, Louis S; Wall, Kirsten; Kraemer, Stephan; Ostroff, Rachel; Janjic, Nebojsa; Ochsner, Urs A

    2017-10-01

    New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant ( P CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform. Copyright © 2017 De Groote et al.

  18. UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

    Science.gov (United States)

    Meinicke, Peter

    2009-09-02

    Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

  19. Directed evolution and in silico analysis of reaction centre proteins reveal molecular signatures of photosynthesis adaptation to radiation pressure.

    Directory of Open Access Journals (Sweden)

    Giuseppina Rea

    2011-01-01

    Full Text Available Evolutionary mechanisms adopted by the photosynthetic apparatus to modifications in the Earth's atmosphere on a geological time-scale remain a focus of intense research. The photosynthetic machinery has had to cope with continuously changing environmental conditions and particularly with the complex ionizing radiation emitted by solar flares. The photosynthetic D1 protein, being the site of electron tunneling-mediated charge separation and solar energy transduction, is a hot spot for the generation of radiation-induced radical injuries. We explored the possibility to produce D1 variants tolerant to ionizing radiation in Chlamydomonas reinhardtii and clarified the effect of radiation-induced oxidative damage on the photosynthetic proteins evolution. In vitro directed evolution strategies targeted at the D1 protein were adopted to create libraries of chlamydomonas random mutants, subsequently selected by exposures to radical-generating proton or neutron sources. The common trend observed in the D1 aminoacidic substitutions was the replacement of less polar by more polar amino acids. The applied selection pressure forced replacement of residues more sensitive to oxidative damage with less sensitive ones, suggesting that ionizing radiation may have been one of the driving forces in the evolution of the eukaryotic photosynthetic apparatus. A set of the identified aminoacidic substitutions, close to the secondary plastoquinone binding niche and oxygen evolving complex, were introduced by site-directed mutagenesis in un-transformed strains, and their sensitivity to free radicals attack analyzed. Mutants displayed reduced electron transport efficiency in physiological conditions, and increased photosynthetic performance stability and oxygen evolution capacity in stressful high-light conditions. Finally, comparative in silico analyses of D1 aminoacidic sequences of organisms differently located in the evolution chain, revealed a higher ratio of residues

  20. Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

    Directory of Open Access Journals (Sweden)

    Li Weizhong

    2008-04-01

    Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

  1. Automatic discovery of cross-family sequence features associated with protein function

    Directory of Open Access Journals (Sweden)

    Krings Andrea

    2006-01-01

    Full Text Available Abstract Background Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. Results We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. Conclusion We have developed a novel and useful approach for

  2. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    Science.gov (United States)

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

  3. Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins.

    Science.gov (United States)

    Firman, Taylor; Ghosh, Kingshuk

    2018-03-28

    We present an analytical theory to compute conformations of heteropolymers-applicable to describe disordered proteins-as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence-while maintaining the same charge composition-can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high

  4. Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

    Science.gov (United States)

    Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

    2015-03-26

    Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

  5. A protein-tyrosine phosphatase with sequence similarity to the SH2 domain of the protein-tyrosine kinases.

    Science.gov (United States)

    Shen, S H; Bastien, L; Posner, B I; Chrétien, P

    1991-08-22

    The phosphorylation of proteins at tyrosine residues is critical in cellular signal transduction, neoplastic transformation and control of the mitotic cycle. These mechanisms are regulated by the activities of both protein-tyrosine kinases (PTKs) and protein-tyrosine phosphatases (PTPases). As in the PTKs, there are two classes of PTPases: membrane associated, receptor-like enzymes and soluble proteins. Here we report the isolation of a complementary DNA clone encoding a new form of soluble PTPase, PTP1C. The enzyme possesses a large noncatalytic region at the N terminus which unexpectedly contains two adjacent copies of the Src homology region 2 (the SH2 domain) found in various nonreceptor PTKs and other cytoplasmic signalling proteins. As with other SH2 sequences, the SH2 domains of PTP1C formed high-affinity complexes with the activated epidermal growth factor receptor and other phosphotyrosine-containing proteins. These results suggest that the SH2 regions in PTP1C may interact with other cellular components to modulate its own phosphatase activity against interacting substrates. PTPase activity may thus directly link growth factor receptors and other signalling proteins through protein-tyrosine phosphorylation.

  6. Evolutionary rates at codon sites may be used to align sequences and infer protein domain function

    Directory of Open Access Journals (Sweden)

    Hazelhurst Scott

    2010-03-01

    Full Text Available Abstract Background Sequence alignments form part of many investigations in molecular biology, including the determination of phylogenetic relationships, the prediction of protein structure and function, and the measurement of evolutionary rates. However, to obtain meaningful results, a significant degree of sequence similarity is required to ensure that the alignments are accurate and the inferences correct. Limitations arise when sequence similarity is low, which is particularly problematic when working with fast-evolving genes, evolutionary distant taxa, genomes with nucleotide biases, and cases of convergent evolution. Results A novel approach was conceptualized to address the "low sequence similarity" alignment problem. We developed an alignment algorithm termed FIRE (Functional Inference using the Rates of Evolution, which aligns sequences using the evolutionary rate at codon sites, as measured by the dN/dS ratio, rather than nucleotide or amino acid residues. FIRE was used to test the hypotheses that evolutionary rates can be used to align sequences and that the alignments may be used to infer protein domain function. Using a range of test data, we found that aligning domains based on evolutionary rates was possible even when sequence similarity was very low (for example, antibody variable regions. Furthermore, the alignment has the potential to infer protein domain function, indicating that domains with similar functions are subject to similar evolutionary constraints. These data suggest that an evolutionary rate-based approach to sequence analysis (particularly when combined with structural data may be used to study cases of convergent evolution or when sequences have very low similarity. However, when aligning homologous gene sets with sequence similarity, FIRE did not perform as well as the best traditional alignment algorithms indicating that the conventional approach of aligning residues as opposed to evolutionary rates remains the

  7. Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

    Science.gov (United States)

    Camproux, A C; Tufféry, P

    2005-08-05

    Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

  8. Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices

    OpenAIRE

    Munteanu, Cristian Robert

    2014-01-01

    Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices, German Conference on Bioinformatics (GCB), Potsdam, Germany (September, 2007)

  9. Fast and simple protein-alignment-guided assembly of orthologous gene families from microbiome sequencing reads.

    Science.gov (United States)

    Huson, Daniel H; Tappu, Rewati; Bazinet, Adam L; Xie, Chao; Cummings, Michael P; Nieselt, Kay; Williams, Rohan

    2017-01-25

    Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.

  10. MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

    KAUST Repository

    Kosinski, Jan

    2013-02-08

    SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

  11. Cloning, sequencing, and expression of dnaK-operon proteins from the thermophilic bacterium Thermus thermophilus.

    Science.gov (United States)

    Osipiuk, J; Joachimiak, A

    1997-09-12

    We propose that the dnaK operon of Thermus thermophilus HB8 is composed of three functionally linked genes: dnaK, grpE, and dnaJ. The dnaK and dnaJ gene products are most closely related to their cyanobacterial homologs. The DnaK protein sequence places T. thermophilus in the plastid Hsp70 subfamily. In contrast, the grpE translated sequence is most similar to GrpE from Clostridium acetobutylicum, a Gram-positive anaerobic bacterium. A single promoter region, with homology to the Escherichia coli consensus promoter sequences recognized by the sigma70 and sigma32 transcription factors, precedes the postulated operon. This promoter is heat-shock inducible. The dnaK mRNA level increased more than 30 times upon 10 min of heat shock (from 70 degrees C to 85 degrees C). A strong transcription terminating sequence was found between the dnaK and grpE genes. The individual genes were cloned into pET expression vectors and the thermophilic proteins were overproduced at high levels in E. coli and purified to homogeneity. The recombinant T. thermophilus DnaK protein was shown to have a weak ATP-hydrolytic activity, with an optimum at 90 degrees C. The ATPase was stimulated by the presence of GrpE and DnaJ. Another open reading frame, coding for ClpB heat-shock protein, was found downstream of the dnaK operon.

  12. Classification of Dutch and German avian reoviruses by sequencing the sigma-C protein.

    NARCIS (Netherlands)

    Kant, A.; Balk, F.R.M.; Born, L.; Roozelaar, van D.; Heijmans, J.; Gielkens, A.; Huurne, ter A.A.H.M.

    2003-01-01

    We have amplified, cloned and sequenced (part of) the open reading frame of the S1 segment encoding the ¿ C protein of avian reoviruses isolated from chickens with different disease conditions in Germany and The Netherlands during 1980 up to 2000. These avian reoviruses were analysed

  13. MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

    KAUST Repository

    Kosinski, Jan; Barbato, Alessandro; Tramontano, Anna

    2013-01-01

    SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

  14. Comment on "Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry".

    Science.gov (United States)

    Pevzner, Pavel A; Kim, Sangtae; Ng, Julio

    2008-08-22

    Asara et al. (Reports, 13 April 2007, p. 280) reported sequencing of Tyrannosaurus rex proteins and used them to establish the evolutionary relationships between birds and dinosaurs. We argue that the reported T. rex peptides may represent statistical artifacts and call for complete data release to enable experimental and computational verification of their findings.

  15. Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

    Science.gov (United States)

    Dong, Zheng; Zhou, Hongyu; Tao, Peng

    2018-02-01

    PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

  16. Sequence of a cDNA encoding turtle high mobility group 1 protein.

    Science.gov (United States)

    Zheng, Jifang; Hu, Bi; Wu, Duansheng

    2005-07-01

    In order to understand sequence information about turtle HMG1 gene, a cDNA encoding HMG1 protein of the Chinese soft-shell turtle (Pelodiscus sinensis) was amplified by RT-PCR from kidney total RNA, and was cloned, sequenced and analyzed. The results revealed that the open reading frame (ORF) of turtle HMG1 cDNA is 606 bp long. The ORF codifies 202 amino acid residues, from which two DNA-binding domains and one polyacidic region are derived. The DNA-binding domains share higher amino acid identity with homologues sequences of chicken (96.5%) and mammalian (74%) than homologues sequence of rainbow trout (67%). The polyacidic region shows 84.6% amino acid homology with the equivalent region of chicken HMG1 cDNA. Turtle HMG1 protein contains 3 Cys residues located at completely conserved positions. Conservation in sequence and structure suggests that the functions of turtle HMG1 cDNA may be highly conserved during evolution. To our knowledge, this is the first report of HMG1 cDNA sequence in any reptilian.

  17. Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.

    Science.gov (United States)

    Kinjo, Akira R

    2017-01-01

    A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated.

  18. On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

    DEFF Research Database (Denmark)

    Wiwie, Christian; Röttger, Richard

    2017-01-01

    Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally...... important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...

  19. Alternative splicing affects the targeting sequence of peroxisome proteins in Arabidopsis.

    Science.gov (United States)

    An, Chuanjing; Gao, Yuefang; Li, Jinyu; Liu, Xiaomin; Gao, Fuli; Gao, Hongbo

    2017-07-01

    A systematic analysis of the Arabidopsis genome in combination with localization experiments indicates that alternative splicing affects the peroxisomal targeting sequence of at least 71 genes in Arabidopsis. Peroxisomes are ubiquitous eukaryotic cellular organelles that play a key role in diverse metabolic functions. All peroxisome proteins are encoded by nuclear genes and target to peroxisomes mainly through two types of targeting signals: peroxisomal targeting signal type 1 (PTS1) and PTS2. Alternative splicing (AS) is a process occurring in all eukaryotes by which a single pre-mRNA can generate multiple mRNA variants, often encoding proteins with functional differences. However, the effects of AS on the PTS1 or PTS2 and the targeting of the protein were rarely studied, especially in plants. Here, we systematically analyzed the genome of Arabidopsis, and found that the C-terminal targeting sequence PTS1 of 66 genes and the N-terminal targeting sequence PTS2 of 5 genes are affected by AS. Experimental determination of the targeting of selected protein isoforms further demonstrated that AS at both the 5' and 3' region of a gene can affect the inclusion of PTS2 and PTS1, respectively. This work underscores the importance of AS on the global regulation of peroxisome protein targeting.

  20. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

    Science.gov (United States)

    Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

    2014-01-01

    Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

  1. Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

    Science.gov (United States)

    Truong, Kevin; Ikura, Mitsuhiko

    2003-05-06

    Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

  2. Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.

    Directory of Open Access Journals (Sweden)

    Andreas Martin Lisewski

    2008-09-01

    Full Text Available The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions and in structure (structural defects trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a sensitive to random errors and (b restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.

  3. Dinoflagellate phylogeny as inferred from heat shock protein 90 and ribosomal gene sequences.

    Directory of Open Access Journals (Sweden)

    Mona Hoppenrath

    2010-10-01

    Full Text Available Interrelationships among dinoflagellates in molecular phylogenies are largely unresolved, especially in the deepest branches. Ribosomal DNA (rDNA sequences provide phylogenetic signals only at the tips of the dinoflagellate tree. Two reasons for the poor resolution of deep dinoflagellate relationships using rDNA sequences are (1 most sites are relatively conserved and (2 there are different evolutionary rates among sites in different lineages. Therefore, alternative molecular markers are required to address the deeper phylogenetic relationships among dinoflagellates. Preliminary evidence indicates that the heat shock protein 90 gene (Hsp90 will provide an informative marker, mainly because this gene is relatively long and appears to have relatively uniform rates of evolution in different lineages.We more than doubled the previous dataset of Hsp90 sequences from dinoflagellates by generating additional sequences from 17 different species, representing seven different orders. In order to concatenate the Hsp90 data with rDNA sequences, we supplemented the Hsp90 sequences with three new SSU rDNA sequences and five new LSU rDNA sequences. The new Hsp90 sequences were generated, in part, from four additional heterotrophic dinoflagellates and the type species for six different genera. Molecular phylogenetic analyses resulted in a paraphyletic assemblage near the base of the dinoflagellate tree consisting of only athecate species. However, Noctiluca was never part of this assemblage and branched in a position that was nested within other lineages of dinokaryotes. The phylogenetic trees inferred from Hsp90 sequences were consistent with trees inferred from rDNA sequences in that the backbone of the dinoflagellate clade was largely unresolved.The sequence conservation in both Hsp90 and rDNA sequences and the poor resolution of the deepest nodes suggests that dinoflagellates reflect an explosive radiation in morphological diversity in their recent

  4. MIToS.jl: mutual information tools for protein sequence analysis in the Julia language

    DEFF Research Database (Denmark)

    Zea, Diego J.; Anfossi, Diego; Nielsen, Morten

    2017-01-01

    Motivation: MIToS is an environment for mutual information analysis and a framework for protein multiple sequence alignments (MSAs) and protein structures (PDB) management in Julia language. It integrates sequence and structural information through SIFTS, making Pfam MSAs analysis straightforward....... MIToS streamlines the implementation of any measure calculated from residue contingency tables and its optimization and testing in terms of protein contact prediction. As an example, we implemented and tested a BLOSUM62-based pseudo-count strategy in mutual information analysis. Availability...... and Implementation: The software is totally implemented in Julia and supported for Linux, OS X and Windows. It’s freely available on GitHub under MIT license: http://mitos.leloir.org.ar. Contacts:diegozea@gmail.com or cmb@leloir.org.ar Supplementary information: Supplementary data are available at Bioinformatics...

  5. Prediction of Carbohydrate-Binding Proteins from Sequences Using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Seizi Someya

    2010-01-01

    Full Text Available Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs. We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.

  6. Improving pairwise comparison of protein sequences with domain co-occurrence

    Science.gov (United States)

    Gascuel, Olivier

    2018-01-01

    Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence PMID:29293498

  7. Length and sequence dependence in the association of Huntingtin protein with lipid membranes

    Science.gov (United States)

    Jawahery, Sudi; Nagarajan, Anu; Matysiak, Silvina

    2013-03-01

    There is a fundamental gap in our understanding of how aggregates of mutant Huntingtin protein (htt) with overextended polyglutamine (polyQ) sequences gain the toxic properties that cause Huntington's disease (HD). Experimental studies have shown that the most important step associated with toxicity is the binding of mutant htt aggregates to lipid membranes. Studies have also shown that flanking amino acid sequences around the polyQ sequence directly affect interactions with the lipid bilayer, and that polyQ sequences of greater than 35 glutamine repeats in htt are a characteristic of HD. The key steps that determine how flanking sequences and polyQ length affect the structure of lipid bilayers remain unknown. In this study, we use atomistic molecular dynamics simulations to study the interactions between lipid membranes of varying compositions and polyQ peptides of varying lengths and flanking sequences. We find that overextended polyQ interactions do cause deformation in model membranes, and that the flanking sequences do play a role in intensifying this deformation by altering the shape of the affected regions.

  8. Amino acid sequences of ribosomal proteins S11 from Bacillus stearothermophilus and S19 from Halobacterium marismortui. Comparison of the ribosomal protein S11 family.

    Science.gov (United States)

    Kimura, M; Kimura, J; Hatakeyama, T

    1988-11-21

    The complete amino acid sequences of ribosomal proteins S11 from the Gram-positive eubacterium Bacillus stearothermophilus and of S19 from the archaebacterium Halobacterium marismortui have been determined. A search for homologous sequences of these proteins revealed that they belong to the ribosomal protein S11 family. Homologous proteins have previously been sequenced from Escherichia coli as well as from chloroplast, yeast and mammalian ribosomes. A pairwise comparison of the amino acid sequences showed that Bacillus protein S11 shares 68% identical residues with S11 from Escherichia coli and a slightly lower homology (52%) with the homologous chloroplast protein. The halophilic protein S19 is more related to the eukaryotic (45-49%) than to the eubacterial counterparts (35%).

  9. Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

    Science.gov (United States)

    Currin, Andrew; Swainston, Neil; Day, Philip J.

    2015-01-01

    The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the ‘search space’ of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (K d) and catalytic (k cat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving k cat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the ‘best’ amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole

  10. The two capsid proteins of maize rayado fino virus contain common peptide sequences.

    Science.gov (United States)

    Falk, B W; Tsai, J H

    1986-01-01

    Virions of maize rayado fino virus (MRFV) were purified and two major capsid proteins (ca. Mr 29,000 and 22,000) were resolved by SDS-PAGE. When the two major capsid proteins were isolated from gels and compared by one-dimensional peptide mapping after digestion with Staphylococcus aureus V-8 protease, indistinguishable peptide maps were obtained, suggesting that these two proteins contain common peptide sequences. Some preparations also showed minor protein components that were intermediate between the Mr 22,000 and Mr 29,000 capsid proteins. One of the minor proteins, ca. Mr 27,000, gave a peptide map indistinguishable from the major capsid proteins. In vitro ageing of partially purified preparations or virion treatment with proteolytic enzymes failed to show conversion of the Mr 29,000 protein to a Mr 22,000. Protease inhibitors added to the buffers used for virion purification did not affect the apparent 1:3 ratio of 29,000 to 22,000 proteins in the purified preparations.

  11. Implication of the cause of differences in 3D structures of proteins with high sequence identity based on analyses of amino acid sequences and 3D structures.

    Science.gov (United States)

    Matsuoka, Masanari; Sugita, Masatake; Kikuchi, Takeshi

    2014-09-18

    Proteins that share a high sequence homology while exhibiting drastically different 3D structures are investigated in this study. Recently, artificial proteins related to the sequences of the GA and IgG binding GB domains of human serum albumin have been designed. These artificial proteins, referred to as GA and GB, share 98% amino acid sequence identity but exhibit different 3D structures, namely, a 3α bundle versus a 4β + α structure. Discriminating between their 3D structures based on their amino acid sequences is a very difficult problem. In the present work, in addition to using bioinformatics techniques, an analysis based on inter-residue average distance statistics is used to address this problem. It was hard to distinguish which structure a given sequence would take only with the results of ordinary analyses like BLAST and conservation analyses. However, in addition to these analyses, with the analysis based on the inter-residue average distance statistics and our sequence tendency analysis, we could infer which part would play an important role in its structural formation. The results suggest possible determinants of the different 3D structures for sequences with high sequence identity. The possibility of discriminating between the 3D structures based on the given sequences is also discussed.

  12. Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

    Science.gov (United States)

    Raghav, Sunil Kumar; Deplancke, Bart

    2012-01-01

    Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

  13. Amyloid fibril formation from sequences of a natural beta-structured fibrous protein, the adenovirus fiber.

    Science.gov (United States)

    Papanikolopoulou, Katerina; Schoehn, Guy; Forge, Vincent; Forsyth, V Trevor; Riekel, Christian; Hernandez, Jean-François; Ruigrok, Rob W H; Mitraki, Anna

    2005-01-28

    Amyloid fibrils are fibrous beta-structures that derive from abnormal folding and assembly of peptides and proteins. Despite a wealth of structural studies on amyloids, the nature of the amyloid structure remains elusive; possible connections to natural, beta-structured fibrous motifs have been suggested. In this work we focus on understanding amyloid structure and formation from sequences of a natural, beta-structured fibrous protein. We show that short peptides (25 to 6 amino acids) corresponding to repetitive sequences from the adenovirus fiber shaft have an intrinsic capacity to form amyloid fibrils as judged by electron microscopy, Congo Red binding, infrared spectroscopy, and x-ray fiber diffraction. In the presence of the globular C-terminal domain of the protein that acts as a trimerization motif, the shaft sequences adopt a triple-stranded, beta-fibrous motif. We discuss the possible structure and arrangement of these sequences within the amyloid fibril, as compared with the one adopted within the native structure. A 6-amino acid peptide, corresponding to the last beta-strand of the shaft, was found to be sufficient to form amyloid fibrils. Structural analysis of these amyloid fibrils suggests that perpendicular stacking of beta-strand repeat units is an underlying common feature of amyloid formation.

  14. An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

    Science.gov (United States)

    Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

    2007-03-15

    Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

  15. Analyses of the Sequence and Structural Properties Corresponding to Pentapeptide and Large Palindromes in Proteins.

    Directory of Open Access Journals (Sweden)

    Settu Sridhar

    Full Text Available The analyses of 3967 representative proteins selected from the Protein Data Bank revealed the presence of 2803 pentapeptide and large palindrome sequences with known secondary structure conformation. These represent 2014 unique palindrome sequences. 60% palindromes are not associated with any regular secondary structure and 28% are in helix conformation, 11% in strand conformation and 1% in the coil conformation. The average solvent accessibility values are in the range between 0-155.28 Å2 suggesting that the palindromes in proteins can be either buried, exposed to the solvent or share an intermittent property. The number of residue neighborhood contacts defined by interactions ≤ 3.2 Ǻ is in the range between 0-29 residues. Palindromes of the same length in helix, strand and coil conformation are associated with different amino acid residue preferences at the individual positions. Nearly, 20% palindromes interact with catalytic/active site residues, ligand or metal ions in proteins and may therefore be important for function in the corresponding protein. The average hydrophobicity values for the pentapeptide and large palindromes range between -4.3 to +4.32 and the number of palindromes is almost equally distributed between the negative and positive hydrophobicity values. The palindromes represent 107 different protein families and the hydrolases, transferases, oxidoreductases and lyases contain relatively large number of palindromes.

  16. FASTERp: A Feature Array Search Tool for Estimating Resemblance of Protein Sequences

    Energy Technology Data Exchange (ETDEWEB)

    Macklin, Derek; Egan, Rob; Wang, Zhong

    2014-03-14

    Metagenome sequencing efforts have provided a large pool of billions of genes for identifying enzymes with desirable biochemical traits. However, homology search with billions of genes in a rapidly growing database has become increasingly computationally impractical. Here we present our pilot efforts to develop a novel alignment-free algorithm for homology search. Specifically, we represent individual proteins as feature vectors that denote the presence or absence of short kmers in the protein sequence. Similarity between feature vectors is then computed using the Tanimoto score, a distance metric that can be rapidly computed on bit string representations of feature vectors. Preliminary results indicate good correlation with optimal alignment algorithms (Spearman r of 0.87, ~;;1,000,000 proteins from Pfam), as well as with heuristic algorithms such as BLAST (Spearman r of 0.86, ~;;1,000,000 proteins). Furthermore, a prototype of FASTERp implemented in Python runs approximately four times faster than BLAST on a small scale dataset (~;;1000 proteins). We are optimizing and scaling to improve FASTERp to enable rapid homology searches against billion-protein databases, thereby enabling more comprehensive gene annotation efforts.

  17. Structural and sequence analysis of imelysin-like proteins implicated in bacterial iron uptake.

    Directory of Open Access Journals (Sweden)

    Qingping Xu

    Full Text Available Imelysin-like proteins define a superfamily of bacterial proteins that are likely involved in iron uptake. Members of this superfamily were previously thought to be peptidases and were included in the MEROPS family M75. We determined the first crystal structures of two remotely related, imelysin-like proteins. The Psychrobacter arcticus structure was determined at 2.15 Å resolution and contains the canonical imelysin fold, while higher resolution structures from the gut bacteria Bacteroides ovatus, in two crystal forms (at 1.25 Å and 1.44 Å resolution, have a circularly permuted topology. Both structures are highly similar to each other despite low sequence similarity and circular permutation. The all-helical structure can be divided into two similar four-helix bundle domains. The overall structure and the GxHxxE motif region differ from known HxxE metallopeptidases, suggesting that imelysin-like proteins are not peptidases. A putative functional site is located at the domain interface. We have now organized the known homologous proteins into a superfamily, which can be separated into four families. These families share a similar functional site, but each has family-specific structural and sequence features. These results indicate that imelysin-like proteins have evolved from a common ancestor, and likely have a conserved function.

  18. The YPLGVG sequence of the Nipah virus matrix protein is required for budding

    Directory of Open Access Journals (Sweden)

    Yan Lianying

    2008-11-01

    Full Text Available Abstract Background Nipah virus (NiV is a recently emerged paramyxovirus capable of causing fatal disease in a broad range of mammalian hosts, including humans. Together with Hendra virus (HeV, they comprise the genus Henipavirus in the family Paramyxoviridae. Recombinant expression systems have played a crucial role in studying the cell biology of these Biosafety Level-4 restricted viruses. Henipavirus assembly and budding occurs at the plasma membrane, although the details of this process remain poorly understood. Multivesicular body (MVB proteins have been found to play a role in the budding of several enveloped viruses, including some paramyxoviruses, and the recruitment of MVB proteins by viral proteins possessing late budding domains (L-domains has become an important concept in the viral budding process. Previously we developed a system for producing NiV virus-like particles (VLPs and demonstrated that the matrix (M protein possessed an intrinsic budding ability and played a major role in assembly. Here, we have used this system to further explore the budding process by analyzing elements within the M protein that are critical for particle release. Results Using rationally targeted site-directed mutagenesis we show that a NiV M sequence YPLGVG is required for M budding and that mutation or deletion of the sequence abrogates budding ability. Replacement of the native and overlapping Ebola VP40 L-domains with the NiV sequence failed to rescue VP40 budding; however, it did induce the cellular morphology of extensive filamentous projection consistent with wild-type VP40-expressing cells. Cells expressing wild-type NiV M also displayed this morphology, which was dependent on the YPLGVG sequence, and deletion of the sequence also resulted in nuclear localization of M. Dominant-negative VPS4 proteins had no effect on NiV M budding, suggesting that unlike other viruses such as Ebola, NiV M accomplishes budding independent of MVB cellular proteins

  19. A two-step recognition of signal sequences determines the translocation efficiency of proteins.

    Science.gov (United States)

    Belin, D; Bost, S; Vassalli, J D; Strub, K

    1996-02-01

    The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated derivatives thereof, ovalbumin and preprolactin) were found to have the differential activities in the two events. For example, the mPAI-2 signal sequence first binds SRP with moderate efficiency and secondly promotes the vectorial transport of only a fraction of the SRP-bound nascent chains. Our results provide evidence that the translocation efficiency of proteins can be controlled by the recognition of their signal sequences at two steps: during SRP-mediated targeting and during formation of a committed translocation complex. This second recognition may occur at several time points during the insertion/translocation step. In conclusion, signal sequences have a more complex structure than previously anticipated, allowing for multiple and independent interactions with the translocation machinery.

  20. Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

    KAUST Repository

    Wong, Ka Chun

    2011-02-05

    Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

  1. RNA2 of grapevine fanleaf virus: sequence analysis and coat protein cistron location.

    Science.gov (United States)

    Serghini, M A; Fuchs, M; Pinck, M; Reinbolt, J; Walter, B; Pinck, L

    1990-07-01

    The nucleotide sequence of the genomic RNA2 (3774 nucleotides) of grapevine fanleaf virus strain F13 was determined from overlapping cDNA clones and its genetic organization was deduced. Two rapid and efficient methods were used for cDNA cloning of the 5' region of RNA2. The complete sequence contained only one long open reading frame of 3555 nucleotides (1184 codons, 131K product). The analysis of the N-terminal sequence of purified coat protein (CP) and identification of its C-terminal residue have allowed the CP cistron to be precisely positioned within the polyprotein. The CP produced by proteolytic cleavage at the Arg/Gly site between residues 680 and 681 contains 504 amino acids (Mr 56019) and has hydrophobic properties. The Arg/Gly cleavage site deduced by N-terminal amino acid sequence analysis is the first for a nepovirus coat protein and for plant viruses expressing their genomic RNAs by polyprotein synthesis. Comparison of GFLV RNA2 with M RNA of cowpea mosaic comovirus and with RNA2 of two closely related nepoviruses, tomato black ring virus and Hungarian grapevine chrome mosaic virus, showed strong similarities among the 3' non-coding regions but less similarity among the 5' end non-coding sequences than reported among other nepovirus RNAs.

  2. Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

    KAUST Repository

    Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak

    2011-01-01

    Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

  3. A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences.

    Science.gov (United States)

    Groussin, M; Boussau, B; Gouy, M

    2013-07-01

    Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor.

  4. Molecular signatures for the Crenarchaeota and the Thaumarchaeota.

    Science.gov (United States)

    Gupta, Radhey S; Shami, Ali

    2011-02-01

    Crenarchaeotes found in mesophilic marine environments were recently placed into a new phylum of Archaea called the Thaumarchaeota. However, very few molecular characteristics of this new phylum are currently known which can be used to distinguish them from the Crenarchaeota. In addition, their relationships to deep-branching archaeal lineages are unclear. We report here detailed analyses of protein sequences from Crenarchaeota and Thaumarchaeota that have identified many conserved signature indels (CSIs) and signature proteins (SPs) (i.e., proteins for which all significant blast hits are from these groups) that are specific for these archaeal groups. Of the identified signatures 6 CSIs and 13 SPs are specific for the Crenarchaeota phylum; 6 CSIs and >250 SPs are uniquely found in various Thaumarchaeota (viz. Cenarchaeum symbiosum, Nitrosopumilus maritimus and a number of uncultured marine crenarchaeotes) and 3 CSIs and ~10 SPs are found in both Thaumarchaeota and Crenarchaeota species. Some of the molecular signatures are also present in Korarchaeum cryptofilum, which forms the independent phylum Korarchaeota. Although some of these molecular signatures suggest a distant shared ancestry between Thaumarchaeota and Crenarchaeota, our identification of large numbers of Thaumarchaeota-specific proteins and their deep branching between the Crenarchaeota and Euryarchaeota phyla in phylogenetic trees shows that they are distinct from both Crenarchaeota and Euryarchaeota in both genetic and phylogenetic terms. These observations support the placement of marine mesophilic archaea into the separate phylum Thaumarchaeota. Additionally, many CSIs and SPs have been found that are specific for different orders within Crenarchaeota (viz. Sulfolobales-3 CSIs and 169 SPs, Thermoproteales-5 CSIs and 25 SPs, Desulfurococcales-4 SPs, and Sulfolobales and Desulfurococcales-2 CSIs and 18 SPs). The signatures described here provide novel means for distinguishing the Crenarchaeota and

  5. Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins

    Science.gov (United States)

    Firman, Taylor; Ghosh, Kingshuk

    2018-03-01

    We present an analytical theory to compute conformations of heteropolymers—applicable to describe disordered proteins—as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence—while maintaining the same charge composition—can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at

  6. Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

    Science.gov (United States)

    Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

    2015-08-03

    Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Evolutionary conservation of nuclear and nucleolar targeting sequences in yeast ribosomal protein S6A

    International Nuclear Information System (INIS)

    Lipsius, Edgar; Walter, Korden; Leicher, Torsten; Phlippen, Wolfgang; Bisotti, Marc-Angelo; Kruppa, Joachim

    2005-01-01

    Over 1 billion years ago, the animal kingdom diverged from the fungi. Nevertheless, a high sequence homology of 62% exists between human ribosomal protein S6 and S6A of Saccharomyces cerevisiae. To investigate whether this similarity in primary structure is mirrored in corresponding functional protein domains, the nuclear and nucleolar targeting signals were delineated in yeast S6A and compared to the known human S6 signals. The complete sequence of S6A and cDNA fragments was fused to the 5'-end of the LacZ gene, the constructs were transiently expressed in COS cells, and the subcellular localization of the fusion proteins was detected by indirect immunofluorescence. One bipartite and two monopartite nuclear localization signals as well as two nucleolar binding domains were identified in yeast S6A, which are located at homologous regions in human S6 protein. Remarkably, the number, nature, and position of these targeting signals have been conserved, albeit their amino acid sequences have presumably undergone a process of co-evolution with their corresponding rRNAs

  8. Milk protein-gum tragacanth mixed gels: effect of heat-treatment sequence.

    Science.gov (United States)

    Hatami, Masoud; Nejatian, Mohammad; Mohammadifar, Mohammad Amin; Pourmand, Hanieh

    2014-01-30

    The aim of this study was to investigate the role of the heat-treatment sequence of biopolymer mixtures as a formulation parameter on the acid-induced gelation of tri-polymeric systems composed of sodium caseinate (Na-caseinate), whey protein concentrate (WPC), and gum tragacanth (GT). This was studied by applying four sequences of heat treatment: (A) co-heating all three biopolymers; (B) heating the milk-protein dispersion and the GT dispersion separately; (C) heating the dispersion containing Na-caseinate and GT together and heating whey protein alone; and (D) co-heating whey protein with GT and heating Na-caseinate alone. According to small-deformation rheological measurements, the strength of the mixed-gel network decreased in the order: C>B>D>A samples. SEM micrographs show that the network of sample C is much more homogenous, coarse and dense than sample A, while the networks of samples B and D are of intermediate density. The heat-treatment sequence of the biopolymer mixtures as a formulation parameter thus offers an opportunity to control the microstructure and rheological properties of mixed gels. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. RTA, a candidate G protein-coupled receptor: Cloning, sequencing, and tissue distribution

    International Nuclear Information System (INIS)

    Ross, P.C.; Figler, R.A.; Corjay, M.H.; Barber, C.M.; Adam, N.; Harcus, D.R.; Lynch, K.R.

    1990-01-01

    Genomic and cDNA clones, encoding a protein that is a member of the guanine nucleotide-binding regulatory protein (G protein)-coupled receptor superfamily, were isolated by screening rat genomic and thoracic aorta cDNA libraries with an oligonucleotide encoding a highly conserved region of the M 1 muscarinic acetylcholine receptor. Sequence analyses of these clones showed that they encode a 343-amino acid protein (named RTA). The RTA gene is single copy, as demonstrated by restriction mapping and Southern blotting of genomic clones and rat genomic DNA. RTA RNA sequences are relatively abundant throughout the gut, vas deferens, uterus, and aorta but are only barely detectable (on Northern blots) in liver, kidney, lung, and salivary gland. In the rat brain, RTA sequences are markedly abundant in the cerebellum. TRA is most closely related to the mas oncogene (34% identity), which has been suggested to be a forebrain angiotensin receptor. They conclude that RTA is not an angiotensin receptor; to date, they have been unable to identify its ligand

  10. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

    Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  11. Large scale identification and categorization of protein sequences using structured logistic regression

    DEFF Research Database (Denmark)

    Pedersen, Bjørn Panella; Ifrim, Georgiana; Liboriussen, Poul

    2014-01-01

    Abstract Background Structured Logistic Regression (SLR) is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well...... problem. Results Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known...... for further biochemical characterization and structural analysis....

  12. Visualization of protein sequence features using JavaScript and SVG with pViz.js.

    Science.gov (United States)

    Mukhyala, Kiran; Masselot, Alexandre

    2014-12-01

    pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. UFO: a web server for ultra-fast functional profiling of whole genome protein sequences

    Directory of Open Access Journals (Sweden)

    Meinicke Peter

    2009-09-01

    Full Text Available Abstract Background Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Description Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. Conclusion For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

  14. Protein sequence analysis by incorporating modified chaos game and physicochemical properties into Chou's general pseudo amino acid composition.

    Science.gov (United States)

    Xu, Chunrui; Sun, Dandan; Liu, Shenghui; Zhang, Yusen

    2016-10-07

    In this contribution we introduced a novel graphical method to compare protein sequences. By mapping a protein sequence into 3D space based on codons and physicochemical properties of 20 amino acids, we are able to get a unique P-vector from the 3D curve. This approach is consistent with wobble theory of amino acids. We compute the distance between sequences by their P-vectors to measure similarities/dissimilarities among protein sequences. Finally, we use our method to analyze four datasets and get better results compared with previous approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Identification of similar regions of protein structures using integrated sequence and structure analysis tools

    Directory of Open Access Journals (Sweden)

    Heiland Randy

    2006-03-01

    Full Text Available Abstract Background Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. Results Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. Conclusion With structural genomics initiatives determining structures with little, if any, functional characterization

  16. Transcriptome response signatures associated with the overexpression of a mitochondrial uncoupling protein (AtUCP1 in tobacco.

    Directory of Open Access Journals (Sweden)

    Alessandra Vasconcellos Nunes Laitz

    Full Text Available Mitochondrial inner membrane uncoupling proteins (UCP dissipate the proton electrochemical gradient established by the respiratory chain, thus affecting the yield of ATP synthesis. UCP overexpression in plants has been correlated with oxidative stress tolerance, improved photosynthetic efficiency and increased mitochondrial biogenesis. This study reports the main transcriptomic responses associated with the overexpression of an UCP (AtUCP1 in tobacco seedlings. Compared to wild-type (WT, AtUCP1 transgenic seedlings showed unaltered ATP levels and higher accumulation of serine. By using RNA-sequencing, a total of 816 differentially expressed genes between the investigated overexpressor lines and the untransformed WT control were identified. Among them, 239 were up-regulated and 577 were down-regulated. As a general response to AtUCP1 overexpression, noticeable changes in the expression of genes involved in energy metabolism and redox homeostasis were detected. A substantial set of differentially expressed genes code for products targeted to the chloroplast and mainly involved in photosynthesis. The overall results demonstrate that the alterations in mitochondrial function provoked by AtUCP1 overexpression require important transcriptomic adjustments to maintain cell homeostasis. Moreover, the occurrence of an important cross-talk between chloroplast and mitochondria, which culminates in the transcriptional regulation of several genes involved in different pathways, was evidenced.

  17. Spike protein assembly into the coronavirion: exploring the limits of its sequence requirements

    International Nuclear Information System (INIS)

    Bosch, Berend Jan; Haan, Cornelis A.M. de; Smits, Saskia L.; Rottier, Peter J.M.

    2005-01-01

    The coronavirus spike (S) protein, required for receptor binding and membrane fusion, is incorporated into the assembling virion by interactions with the viral membrane (M) protein. Earlier we showed that the ectodomain of the S protein is not involved in this process. Here we further defined the requirements of the S protein for virion incorporation. We show that the cytoplasmic domain, not the transmembrane domain, determines the association with the M protein and suffices to effect the incorporation into viral particles of chimeric spikes as well as of foreign viral glycoproteins. The essential sequence was mapped to the membrane-proximal region of the cytoplasmic domain, which is also known to be of critical importance for the fusion function of the S protein. Consistently, only short C-terminal truncations of the S protein were tolerated when introduced into the virus by targeted recombination. The important role of the about 38-residues cytoplasmic domain in the assembly of and membrane fusion by this approximately 1300 amino acids long protein is discussed

  18. Variability of the protein sequences of lcrV between epidemic and atypical rhamnose-positive strains of Yersinia pestis.

    Science.gov (United States)

    Anisimov, Andrey P; Panfertsev, Evgeniy A; Svetoch, Tat'yana E; Dentovskaya, Svetlana V

    2007-01-01

    Sequencing of lcrV genes and comparison of the deduced amino acid sequences from ten Y. pestis strains belonging mostly to the group of atypical rhamnose-positive isolates (non-pestis subspecies or pestoides group) showed that the LcrV proteins analyzed could be classified into five sequence types. This classification was based on major amino acid polymorphisms among LcrV proteins in the four "hot points" of the protein sequences. Some additional minor polymorphisms were found throughout these sequence types. The "hot points" corresponded to amino acids 18 (Lys --> Asn), 72 (Lys --> Arg), 273 (Cys --> Ser), and 324-326 (Ser-Gly-Lys --> Arg) in the LcrV sequence of the reference Y. pestis strain CO92. One possible explanation for polymorphism in amino acid sequences of LcrV among different strains is that strain-specific variation resulted from adaptation of the plague pathogen to different rodent and lagomorph hosts.

  19. Preparative Protein Production from Inclusion Bodies and Crystallization: A Seven-Week Biochemistry Sequence

    Science.gov (United States)

    Peterson, Megan J.; Snyder, W. Kalani; Westerman, Shelley; McFarland, Benjamin J.

    2011-01-01

    We describe how to produce and purify proteins from E. coli inclusion bodies by adapting versatile, preparative-scale techniques to the undergraduate laboratory schedule. This seven-week sequence of experiments fits into an annual cycle of research activity in biochemistry courses. Recombinant proteins are expressed as inclusion bodies, which are collected, washed, then solubilized in urea. Stepwise dialysis to dilute urea over the course of a week produces refolded protein. Column chromatography is used to purify protein into fractions, which are then analyzed with gel electrophoresis and concentration assays. Students culminate the project by designing crystallization trials in sitting-drop trays. Student evaluation of the experience has been positive, listing 5–12 new techniques learned, which are transferrable to graduate research in academia and industry. PMID:21691428

  20. Statistical distributions of optimal global alignment scores of random protein sequences

    Directory of Open Access Journals (Sweden)

    Tang Jiaowei

    2005-10-01

    Full Text Available Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. Conclusion We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.

  1. Sequence variation of koala retrovirus transmembrane protein p15E among koalas from different geographic regions

    Science.gov (United States)

    Ishida, Yasuko; McCallister, Chelsea; Nikolaidis, Nikolas; Tsangaras, Kyriakos; Helgen, Kristofer M.; Greenwood, Alex D.; Roca, Alfred L.

    2014-01-01

    The koala retrovirus (KoRV), which is transitioning from an exogenous to an endogenous form, has been associated with high mortality in koalas. For other retroviruses, the envelope protein p15E has been considered a candidate for vaccine development. We therefore examined proviral sequence variation of KoRV p15E in a captive Queensland and three wild southern Australian koalas. We generated 163 sequences with intact open reading frames, which grouped into 39 distinct haplotypes. Sixteen distinct haplotypes comprising 139 of the sequences (85%) coded for the same polypeptide. Among the remaining 23 haplotypes, 22 were detected only once among the sequences, and each had 1 or 2 non-synonymous differences from the majority sequence. Several analyses suggested that p15E was under purifying selection. Important epitopes and domains were highly conserved across the p15E sequences and in previously reported exogenous KoRVs. Overall, these results support the potential use of p15E for KoRV vaccine development. PMID:25462343

  2. Simplifying complex sequence information: a PCP-consensus protein binds antibodies against all four Dengue serotypes.

    Science.gov (United States)

    Bowen, David M; Lewis, Jessica A; Lu, Wenzhe; Schein, Catherine H

    2012-09-14

    Designing proteins that reflect the natural variability of a pathogen is essential for developing novel vaccines and drugs. Flaviviruses, including Dengue (DENV) and West Nile (WNV), evolve rapidly and can "escape" neutralizing monoclonal antibodies by mutation. Designing antigens that represent many distinct strains is important for DENV, where infection with a strain from one of the four serotypes may lead to severe hemorrhagic disease on subsequent infection with a strain from another serotype. Here, a DENV physicochemical property (PCP)-consensus sequence was derived from 671 unique sequences from the Flavitrack database. PCP-consensus proteins for domain 3 of the envelope protein (EdomIII) were expressed from synthetic genes in Escherichia coli. The ability of the purified consensus proteins to bind polyclonal antibodies generated in response to infection with strains from each of the four DENV serotypes was determined. The initial consensus protein bound antibodies from DENV-1-3 in ELISA and Western blot assays. This sequence was altered in 3 steps to incorporate regions of maximum variability, identified as significant changes in the PCPs, characteristic of DENV-4 strains. The final protein was recognized by antibodies against all four serotypes. Two amino acids essential for efficient binding to all DENV antibodies are part of a discontinuous epitope previously defined for a neutralizing monoclonal antibody. The PCP-consensus method can significantly reduce the number of experiments required to define a multivalent antigen, which is particularly important when dealing with pathogens that must be tested at higher biosafety levels. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Aberrant chimeric RNA GOLM1-MAK10 encoding a secreted fusion protein as a molecular signature for human esophageal squamous cell carcinoma

    Science.gov (United States)

    Zhang, Hao; Lin, Wan; Kannan, Kalpana; Luo, Liming; Li, Jing; Chao, Pei-Wen; Wang, Yan; Chen, Yu-Ping; Gu, Jiang; Yen, Laising

    2013-01-01

    It is increasingly recognized that chimeric RNAs may exert a novel layer of cellular complexity that contributes to oncogenesis and cancer progression, and could be utilized as molecular biomarkers and therapeutic targets. To date yet no fusion chimeric RNAs have been identified in esophageal cancer, the 6th most frequent cause of cancer death in the world. While analyzing the expression of 32 recurrent cancer chimeric RNAs in esophageal squamous cell carcinoma (ESCC) from patients and cancer cell lines, we identified GOLM1-MAK10, as a highly cancer-enriched chimeric RNA in ESCC. In situ hybridization revealed that the expression of the chimera is largely restricted to cancer cells in patient tumors, and nearly undetectable in non-neoplastic esophageal tissue from normal subjects. The aberrant chimera closely correlated with histologic differentiation and lymph node metastasis. Furthermore, we demonstrate that chimera GOLM1-MAK10 encodes a secreted fusion protein. Mechanistic studies reveal that GOLM1-MAK10 is likely derived from transcription read-through/splicing rather than being generated from a fusion gene. Collectively, these findings provide novel insights into the molecular mechanism involved in ESCC and provide a novel potential target for future therapies. The secreted fusion protein translated from GOLM1-MAK10 could also serve as a unique protein signature detectable by standard non-invasive assays. These observations are critical as there is no clinically useful molecular signature available for detecting this deadly disease or monitoring the treatment response. PMID:24243830

  4. A novel approach to sequence validating protein expression clones with automated decision making

    Directory of Open Access Journals (Sweden)

    Mohr Stephanie E

    2007-06-01

    Full Text Available Abstract Background Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation. Results We have developed an Automated Clone Evaluation (ACE system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set. Conclusion ACE was designed to facilitate high throughput clone sequence

  5. Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation

    Science.gov (United States)

    Riley, Nicholas M.; Westphall, Michael S.; Coon, Joshua J.

    2018-01-01

    The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. [Figure not available: see fulltext.

  6. Accessible surface area of proteins from purely sequence information and the importance of global features

    Science.gov (United States)

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-03-01

    We present a new approach for predicting the accessible surface area of proteins. The novelty of this approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Rather, sequential window information and the global monomer and dimer compositions of the chain are used. We find that much of the lost accuracy due to the elimination of evolutionary information is recouped by the use of global features. Furthermore, this new predictor produces similar results for proteins with or without sequence homologs deposited in the Protein Data Bank, and hence shows generalizability. Finally, these predictions are obtained in a small fraction (1/1000) of the time required to run mutation profile based prediction. All these factors indicate the possible usability of this work in de-novo protein structure prediction and in de-novo protein design using iterative searches. Funded in part by the financial support of the National Institutes of Health through Grants R01GM072014 and R01GM073095, and the National Science Foundation through Grant NSF MCB 1071785.

  7. Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

    Science.gov (United States)

    Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

    2011-10-01

    The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.

  8. Mapping a nucleolar targeting sequence of an RNA binding nucleolar protein, Nop25

    International Nuclear Information System (INIS)

    Fujiwara, Takashi; Suzuki, Shunji; Kanno, Motoko; Sugiyama, Hironobu; Takahashi, Hisaaki; Tanaka, Junya

    2006-01-01

    Nop25 is a putative RNA binding nucleolar protein associated with rRNA transcription. The present study was undertaken to determine the mechanism of Nop25 localization in the nucleolus. Deletion experiments of Nop25 amino acid sequence showed Nop25 to contain a nuclear targeting sequence in the N-terminal and a nucleolar targeting sequence in the C-terminal. By expressing derivative peptides from the C-terminal as GFP-fusion proteins in the cells, a lysine and arginine residue-enriched peptide (KRKHPRRAQDSTKKPPSATRTSKTQRRRR) allowed a GFP-fusion protein to be transported and fully retained in the nucleolus. When the peptide was fused with cMyc epitope and expressed in the cells, a cMyc epitope was then detected in the nucleolus. Nop25 did not localize in the nucleolus by deletion of the peptide from Nop25. Furthermore, deletion of a subdomain (KRKHPRRAQ) in the peptide or amino acid substitution of lysine and arginine residues in the subdomain resulted in the loss of Nop25 nucleolar localization. These results suggest that the lysine and arginine residue-enriched peptide is the most prominent nucleolar targeting sequence of Nop25 and that the long stretch of basic residues might play an important role in the nucleolar localization of Nop25. Although Nop25 contained putative SUMOylation, phosphorylation and glycosylation sites, the amino acid substitution in these sites had no effect on the nucleolar localization, thus suggesting that these post-translational modifications did not contribute to the localization of Nop25 in the nucleolus. The treatment of the cells, which expressed a GFP-fusion protein with a nucleolar targeting sequence of Nop25, with RNase A resulted in a complete dislocation of the protein from the nucleolus. These data suggested that the nucleolar targeting sequence might therefore play an important role in the binding of Nop25 to RNA molecules and that the RNA binding of Nop25 might be essential for the nucleolar localization of Nop25

  9. Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding.

    Directory of Open Access Journals (Sweden)

    Yoojin Hong

    2010-10-01

    Full Text Available A major computational challenge in the genomic era is annotating structure/function to the vast quantities of sequence information that is now available. This problem is illustrated by the fact that most proteins lack comprehensive annotations, even when experimental evidence exists. We previously theorized that embedded-alignment profiles (simply "alignment profiles" hereafter provide a quantitative method that is capable of relating the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of alignment profiles lies in the interoperability of data format (e.g., alignment information, physio-chemical information, genomic information, etc.. Indeed, we have demonstrated that the Position Specific Scoring Matrices (PSSMs are an informative M-dimension that is scored by quantitatively measuring the embedded or unmodified sequence alignments. Moreover, the information obtained from these alignments is informative, and remains so even in the "twilight zone" of sequence similarity (<25% identity. Although our previous embedding strategy was powerful, it suffered from contaminating alignments (embedded AND unmodified and high computational costs. Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." Adaptive GDDA-BLAST is, on average, up to 19 times faster than, but has similar sensitivity to our previous method. Further, data are provided to demonstrate the benefits of embedded-alignment measurements in terms of detecting structural homology in highly divergent protein sequences and isolating secondary structural elements of transmembrane and ankyrin-repeat domains. Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences. We show that sequence embedding could serve as one of the vehicles for measurement of low

  10. Sequence of a cloned cDNA encoding human ribosomal protein S11

    Energy Technology Data Exchange (ETDEWEB)

    Lott, J B; Mackie, G A

    1988-02-11

    The authors have isolated a cloned cDNA that encodes human ribosomal protein (rp) S11 by screening a human fibroblast cDNA library with a labelled 204 bp DNA fragment encompassing residues 212-416 of pRS11, a rat rp Sll cDNA clone. The human rp S11 cloned cDNA consists of 15 residues of the 5' leader, the entire coding sequence and all 51 residues of the 3' untranslated region. The predicted amino acid sequence of 158 residues is identical to rat rpS11. The nucleotide sequence in the coding region differs, however, from that in rat in the first position in two codons and in the third position in 44 codons.

  11. OPAL: prediction of MoRF regions in intrinsically disordered protein sequences.

    Science.gov (United States)

    Sharma, Ronesh; Raicar, Gaurav; Tsunoda, Tatsuhiko; Patil, Ashwini; Sharma, Alok

    2018-06-01

    Intrinsically disordered proteins lack stable 3-dimensional structure and play a crucial role in performing various biological functions. Key to their biological function are the molecular recognition features (MoRFs) located within long disordered regions. Computationally identifying these MoRFs from disordered protein sequences is a challenging task. In this study, we present a new MoRF predictor, OPAL, to identify MoRFs in disordered protein sequences. OPAL utilizes two independent sources of information computed using different component predictors. The scores are processed and combined using common averaging method. The first score is computed using a component MoRF predictor which utilizes composition and sequence similarity of MoRF and non-MoRF regions to detect MoRFs. The second score is calculated using half-sphere exposure (HSE), solvent accessible surface area (ASA) and backbone angle information of the disordered protein sequence, using information from the amino acid properties of flanks surrounding the MoRFs to distinguish MoRF and non-MoRF residues. OPAL is evaluated using test sets that were previously used to evaluate MoRF predictors, MoRFpred, MoRFchibi and MoRFchibi-web. The results demonstrate that OPAL outperforms all the available MoRF predictors and is the most accurate predictor available for MoRF prediction. It is available at http://www.alok-ai-lab.com/tools/opal/. ashwini@hgc.jp or alok.sharma@griffith.edu.au. Supplementary data are available at Bioinformatics online.

  12. Neutral evolution of proteins: The superfunnel in sequence space and its relation to mutational robustness

    Science.gov (United States)

    Noirel, Josselin; Simonson, Thomas

    2008-11-01

    Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate μ and the population size N, the biological population can evolve purely randomly (μN ≪1) or it can evolve in such a way as to select for sequences of higher mutational robustness (μN ≫1). The stringency of the selection depends not only on the product μN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular

  13. Oral treponeme major surface protein: Sequence diversity and distributions within periodontal niches.

    Science.gov (United States)

    You, M; Chan, Y; Lacap-Bugler, D C; Huo, Y-B; Gao, W; Leung, W K; Watt, R M

    2017-12-01

    Treponema denticola and other species (phylotypes) of oral spirochetes are widely considered to play important etiological roles in periodontitis and other oral infections. The major surface protein (Msp) of T. denticola is directly implicated in several pathological mechanisms. Here, we have analyzed msp sequence diversity across 68 strains of oral phylogroup 1 and 2 treponemes; including reference strains of T. denticola, Treponema putidum, Treponema medium, 'Treponema vincentii', and 'Treponema sinensis'. All encoded Msp proteins contained highly conserved, taxon-specific signal peptides, and shared a predicted 'three-domain' structure. A clone-based strategy employing 'msp-specific' polymerase chain reaction primers was used to analyze msp gene sequence diversity present in subgingival plaque samples collected from a group of individuals with chronic periodontitis (n=10), vs periodontitis-free controls (n=10). We obtained 626 clinical msp gene sequences, which were assigned to 21 distinct 'clinical msp genotypes' (95% sequence identity cut-off). The most frequently detected clinical msp genotype corresponded to T. denticola ATCC 35405 T , but this was not correlated to disease status. UniFrac and libshuff analysis revealed that individuals with periodontitis and periodontitis-free controls harbored significantly different communities of treponeme clinical msp genotypes (Pdiversity than periodontitis-free controls (Mann-Whitney U-test, Pdiversity of Treponema clinical msp genotypes within their subgingival niches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Nucleotide sequence analysis of the Legionella micdadei mip gene, encoding a 30-kilodalton analog of the Legionella pneumophila Mip protein

    DEFF Research Database (Denmark)

    Bangsborg, Jette Marie; Cianciotto, N P; Hindersson, P

    1991-01-01

    After the demonstration of analogs of the Legionella pneumophila macrophage infectivity potentiator (Mip) protein in other Legionella species, the Legionella micdadei mip gene was cloned and expressed in Escherichia coli. DNA sequence analysis of the L. micdadei mip gene contained in the plasmid p...... homology with the mip-like genes of several Legionella species. Furthermore, amino acid sequence comparisons revealed significant homology to two eukaryotic proteins with isomerase activity (FK506-binding proteins)....

  15. Identification of a novel nuclear localization signal and speckle-targeting sequence of tuftelin-interacting protein 11, a splicing factor involved in spliceosome disassembly

    Energy Technology Data Exchange (ETDEWEB)

    Tannukit, Sissada [Center for Craniofacial Molecular Biology, University of Southern California, 2250 Alcazar Street, CSA Rm103, Los Angeles, CA 90033-1004 (United States); Crabb, Tara L.; Hertel, Klemens J. [Department of Microbiology and Molecular Genetics, University of California Irvine, Irvine, CA 92697-4025 (United States); Wen, Xin [Center for Craniofacial Molecular Biology, University of Southern California, 2250 Alcazar Street, CSA Rm103, Los Angeles, CA 90033-1004 (United States); Jans, David A. [Department of Biochemistry and Molecular Biology, Nuclear Signalling Laboratory, Monash University, Clayton, Victoria 3800 (Australia); Paine, Michael L., E-mail: paine@usc.edu [Center for Craniofacial Molecular Biology, University of Southern California, 2250 Alcazar Street, CSA Rm103, Los Angeles, CA 90033-1004 (United States)

    2009-12-18

    Tuftelin-interacting protein 11 (TFIP11) is a protein component of the spliceosome complex that promotes the release of the lariat-intron during late-stage splicing through a direct recruitment and interaction with DHX15/PRP43. Expression of TFIP11 is essential for cell and organismal survival. TFIP11 contains a G-patch domain, a signature motif of RNA-processing proteins that is responsible for TFIP11-DHX15 interactions. No other functional domains within TFIP11 have been described. TFIP11 is localized to distinct speckled regions within the cell nucleus, although excluded from the nucleolus. In this study sequential C-terminal deletions and mutational analyses have identified two novel protein elements in mouse TFIP11. The first domain covers amino acids 701-706 (VKDKFN) and is an atypical nuclear localization signal (NLS). The second domain is contained within amino acids 711-735 and defines TFIP11's distinct speckled nuclear localization. The identification of a novel TFIP11 nuclear speckle-targeting sequence (TFIP11-STS) suggests that this domain directly interacts with additional spliceosomal components. These data help define the mechanism of nuclear/nuclear speckle localization of the splicing factor TFIP11, with implications for it's function.

  16. SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

    Science.gov (United States)

    Suresh, V; Parthasarathy, S

    2014-01-01

    We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

  17. Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH

    International Nuclear Information System (INIS)

    Volk, Jochen; Herrmann, Torsten; Wuethrich, Kurt

    2008-01-01

    MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness

  18. Epitope Sequences in Dengue Virus NS1 Protein Identified by Monoclonal Antibodies

    Directory of Open Access Journals (Sweden)

    Leticia Barboza Rocha

    2017-10-01

    Full Text Available Dengue nonstructural protein 1 (NS1 is a multi-functional glycoprotein with essential functions both in viral replication and modulation of host innate immune responses. NS1 has been established as a good surrogate marker for infection. In the present study, we generated four anti-NS1 monoclonal antibodies against recombinant NS1 protein from dengue virus serotype 2 (DENV2, which were used to map three NS1 epitopes. The sequence 193AVHADMGYWIESALNDT209 was recognized by monoclonal antibodies 2H5 and 4H1BC, which also cross-reacted with Zika virus (ZIKV protein. On the other hand, the sequence 25VHTWTEQYKFQPES38 was recognized by mAb 4F6 that did not cross react with ZIKV. Lastly, a previously unidentified DENV2 NS1-specific epitope, represented by the sequence 127ELHNQTFLIDGPETAEC143, is described in the present study after reaction with mAb 4H2, which also did not cross react with ZIKV. The selection and characterization of the epitope, specificity of anti-NS1 mAbs, may contribute to the development of diagnostic tools able to differentiate DENV and ZIKV infections.

  19. Actin and ubiquitin protein sequences support a cercozoan/foraminiferan ancestry for the plasmodiophorid plant pathogens.

    Science.gov (United States)

    Archibald, John M; Keeling, Patrick J

    2004-01-01

    The plasmodiophorids are a group of eukaryotic intracellular parasites that cause disease in a variety of economically significant crops. Plasmodiophorids have traditionally been considered fungi but have more recently been suggested to be members of the Cercozoa, a morphologically diverse group of amoeboid, flagellate, and amoeboflagellate protists. The recognition that Cercozoa constitute a monophyletic lineage has come from phylogenetic analyses of small subunit ribosomal RNA genes. Protein sequence data have suggested that the closest relatives of Cercozoa are the Foraminifera. To further test a cercozoan origin for the plasmodiophorids, we isolated actin genes from Plasmodiophora brassicae, Sorosphaera veronicae, and Spongospora subterranea, and polyubiquitin gene fragments from P. brassicae and S. subterranea. We also isolated actin genes from the chlorarachniophyte Lotharella globosa. In protein phylogenies of actin, the plasmodiophorid sequences consistently branch with Cercozoa and Foraminifera, and weakly branch as the sister group to the foraminiferans. The plasmodiophorid polyubiquitin sequences contain a single amino acid residue insertion at the functionally important processing point between ubiquitin monomers, the same place in which an otherwise unique insertion exists in the cercozoan and foraminiferan proteins. Taken together, these results indicate that plasmodiophorids are indeed related to Cercozoa and Foraminifera, although the relationships amongst these groups remain unresolved.

  20. WebScipio: An online tool for the determination of gene structures using protein sequences

    Directory of Open Access Journals (Sweden)

    Waack Stephan

    2008-09-01

    Full Text Available Abstract Background Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches. Results WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs. Conclusion WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at http://www.webscipio.org.

  1. High fat diet-induced modifications in membrane lipid and mitochondrial-membrane protein signatures precede the development of hepatic insulin resistance in mice.

    Science.gov (United States)

    Kahle, M; Schäfer, A; Seelig, A; Schultheiß, J; Wu, M; Aichler, M; Leonhardt, J; Rathkolb, B; Rozman, J; Sarioglu, H; Hauck, S M; Ueffing, M; Wolf, E; Kastenmueller, G; Adamski, J; Walch, A; Hrabé de Angelis, M; Neschen, S

    2015-01-01

    Excess lipid intake has been implicated in the pathophysiology of hepatosteatosis and hepatic insulin resistance. Lipids constitute approximately 50% of the cell membrane mass, define membrane properties, and create microenvironments for membrane-proteins. In this study we aimed to resolve temporal alterations in membrane metabolite and protein signatures during high-fat diet (HF)-mediated development of hepatic insulin resistance. We induced hepatosteatosis by feeding C3HeB/FeJ male mice an HF enriched with long-chain polyunsaturated C18:2n6 fatty acids for 7, 14, or 21 days. Longitudinal changes in hepatic insulin sensitivity were assessed via the euglycemic-hyperinsulinemic clamp, in membrane lipids via t-metabolomics- and membrane proteins via quantitative proteomics-analyses, and in hepatocyte morphology via electron microscopy. Data were compared to those of age- and litter-matched controls maintained on a low-fat diet. Excess long-chain polyunsaturated C18:2n6 intake for 7 days did not compromise hepatic insulin sensitivity, however, induced hepatosteatosis and modified major membrane lipid constituent signatures in liver, e.g. increased total unsaturated, long-chain fatty acid-containing acyl-carnitine or membrane-associated diacylglycerol moieties and decreased total short-chain acyl-carnitines, glycerophosphocholines, lysophosphatidylcholines, or sphingolipids. Hepatic insulin sensitivity tended to decrease within 14 days HF-exposure. Overt hepatic insulin resistance developed until day 21 of HF-intervention and was accompanied by morphological mitochondrial abnormalities and indications for oxidative stress in liver. HF-feeding progressively decreased the abundance of protein-components of all mitochondrial respiratory chain complexes, inner and outer mitochondrial membrane substrate transporters independent from the hepatocellular mitochondrial volume in liver. We assume HF-induced modifications in membrane lipid- and protein-signatures prior to and

  2. Prediction of membrane transport proteins and their substrate specificities using primary sequence information.

    Directory of Open Access Journals (Sweden)

    Nitish K Mishra

    Full Text Available Membrane transport proteins (transporters move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.Support vector machine (SVM-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM, were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC of 0.49 and a receiver operating characteristic area under the curve (AUC of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.Our analyses suggest that evolutionary information (i.e., the PSSM and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions

  3. Influence of the Amino Acid Sequence on Protein-Mineral Interactions in Soil

    Science.gov (United States)

    Chacon, S. S.; Reardon, P. N.; Purvine, S.; Lipton, M. S.; Washton, N.; Kleber, M.

    2017-12-01

    The intimate associations between protein and mineral surfaces have profound impacts on nutrient cycling in soil. Proteins are an important source of organic C and N, and a subset of proteins, extracellular enzymes (EE), can catalyze the depolymerization of soil organic matter (SOM). Our goal was to determine how variation in the amino acid sequence could influence a protein's susceptibility to become chemically altered by mineral surfaces to infer the fate of adsorbed EE function in soil. We hypothesized that (1) addition of charged amino acids would enhance the adsorption onto oppositely charged mineral surfaces (2) addition of aromatic amino acids would increase adsorption onto zero charged surfaces (3) Increase adsorption of modified proteins would enhance their susceptibility to alterations by redox active minerals. To test these hypotheses, we generated three engineered proxies of a model protein Gb1 (IEP 4.0, 6.2 kDA) by inserting either negatively charged, positively charged or aromatic amino acids in the second loop. These modified proteins were allowed to interact with functionally different mineral surfaces (goethite, montmorillonite, kaolinite and birnessite) at pH 5 and 7. We used LC-MS/MS and solution-state Heteronuclear Single Quantum Coherence Spectroscopy NMR to observe modifications on engineered proteins as a consequence to mineral interactions. Preliminary results indicate that addition of any amino acids to a protein increase its susceptibility to fragmentation and oxidation by redox active mineral surfaces, and alter adsorption to the other mineral surfaces. This suggest that not all mineral surfaces in soil may act as sorbents for EEs and chemical modification of their structure should also be considered as an explanation for decrease in EE activity. Fragmentation of proteins by minerals can bypass the need to produce proteases, but microbial acquisition of other nutrients that require enzymes such as cellulases, ligninases or phosphatases

  4. Integrating genomic information with protein sequence and 3D atomic level structure at the RCSB protein data bank.

    Science.gov (United States)

    Prlic, Andreas; Kalro, Tara; Bhattacharya, Roshni; Christie, Cole; Burley, Stephen K; Rose, Peter W

    2016-12-15

    The Protein Data Bank (PDB) now contains more than 120,000 three-dimensional (3D) structures of biological macromolecules. To allow an interpretation of how PDB data relates to other publicly available annotations, we developed a novel data integration platform that maps 3D structural information across various datasets. This integration bridges from the human genome across protein sequence to 3D structure space. We developed novel software solutions for data management and visualization, while incorporating new libraries for web-based visualization using SVG graphics. The new views are available from http://www.rcsb.org and software is available from https://github.com/rcsb/. andreas.prlic@rcsb.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  5. Bidirectional gene sequences with similar homology to functional proteins of alkane degrading bacterium pseudomonas fredriksbergensis DNA

    International Nuclear Information System (INIS)

    Megeed, A.A.

    2011-01-01

    The potential for two overlapping fragments of DNA from a clone of newly isolated alkanes degrading bacterium Pseudomonas frederiksbergensis encoding sequences with similar homology to two parts of functional proteins is described. One strand contains a sequence with high homology to alkanes monooxygenase (alkB), a member of the alkanes hydroxylase family, and the other strand contains a sequence with some homology to alcohol dehydrogenase gene (alkJ). Overlapping of the genes on opposite strands has been reported in eukaryotic species, and is now reported in a bacterial species. The sequence comparisons and ORFS results revealed that the regulation and the genes organization involved in alkane oxidation represented in Pseudomonas frederiksberghensis varies among the different known alkane degrading bacteria. The alk gene cluster containing homologues to the known alkane monooxygenase (alkB), and rubredoxin (alkG) are oriented in the same direction, whereas alcohol dehydrogenase (alkJ) is oriented in the opposite direction. Such genomes encode messages on both strands of the DNA, or in an overlapping but different reading frames, of the same strand of DNA. The possibility of creating novel genes from pre-existing sequences, known as overprinting, which is a widespread phenomenon in small viruses. Here, the origin and evolution of the gene overlap to bacteriophages belonging to the family Microviridae have been investigated. Such a phenomenon is most widely described in extremely small genomes such as those of viruses or small plasmids, yet here is a unique phenomenon. (author)

  6. An intuitive graphical webserver for multiple-choice protein sequence search.

    Science.gov (United States)

    Banky, Daniel; Szalkai, Balazs; Grolmusz, Vince

    2014-04-10

    Every day tens of thousands of sequence searches and sequence alignment queries are submitted to webservers. The capitalized word "BLAST" becomes a verb, describing the act of performing sequence search and alignment. However, if one needs to search for sequences that contain, for example, two hydrophobic and three polar residues at five given positions, the query formation on the most frequently used webservers will be difficult. Some servers support the formation of queries with regular expressions, but most of the users are unfamiliar with their syntax. Here we present an intuitive, easily applicable webserver, the Protein Sequence Analysis server, that allows the formation of multiple choice queries by simply drawing the residues to their positions; if more than one residue are drawn to the same position, then they will be nicely stacked on the user interface, indicating the multiple choice at the given position. This computer-game-like interface is natural and intuitive, and the coloring of the residues makes possible to form queries requiring not just certain amino acids in the given positions, but also small nonpolar, negatively charged, hydrophobic, positively charged, or polar ones. The webserver is available at http://psa.pitgroup.org. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. An improved classification of G-protein-coupled receptors using sequence-derived features

    Directory of Open Access Journals (Sweden)

    Peng Zhen-Ling

    2010-08-01

    Full Text Available Abstract Background G-protein-coupled receptors (GPCRs play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structures of GPCRs are largely unavailable; however, a large number of GPCR primary sequences are known. To facilitate the identification and characterization of novel receptors, it is therefore very valuable to develop a computational method to accurately predict GPCRs from the protein primary sequences. Results We propose a new method called PCA-GPCR, to predict GPCRs using a comprehensive set of 1497 sequence-derived features. The principal component analysis is first employed to reduce the dimension of the feature space to 32. Then, the resulting 32-dimensional feature vectors are fed into a simple yet powerful classification algorithm, called intimate sorting, to predict GPCRs at five levels. The prediction at the first level determines whether a protein is a GPCR or a non-GPCR. If it is predicted to be a GPCR, then it will be further predicted into certain family, subfamily, sub-subfamily and subtype by the classifiers at the second, third, fourth, and fifth levels, respectively. To train the classifiers applied at five levels, a non-redundant dataset is carefully constructed, which contains 3178, 1589, 4772, 4924, and 2741 protein sequences at the respective levels. Jackknife tests on this training dataset show that the overall accuracies of PCA-GPCR at five levels (from the first to the fifth can achieve up to 99.5%, 88.8%, 80.47%, 80.3%, and 92.34%, respectively. We further perform predictions on a dataset of 1238 GPCRs at the second level, and on another two datasets of 167 and 566 GPCRs respectively at the fourth level. The overall prediction accuracies of our method are consistently higher than those of the existing methods to be compared. Conclusions The comprehensive set of 1497 features is believed to be capable of capturing information about amino acid

  8. Programming molecular self-assembly of intrinsically disordered proteins containing sequences of low complexity

    Science.gov (United States)

    Simon, Joseph R.; Carroll, Nick J.; Rubinstein, Michael; Chilkoti, Ashutosh; López, Gabriel P.

    2017-06-01

    Dynamic protein-rich intracellular structures that contain phase-separated intrinsically disordered proteins (IDPs) composed of sequences of low complexity (SLC) have been shown to serve a variety of important cellular functions, which include signalling, compartmentalization and stabilization. However, our understanding of these structures and our ability to synthesize models of them have been limited. We present design rules for IDPs possessing SLCs that phase separate into diverse assemblies within droplet microenvironments. Using theoretical analyses, we interpret the phase behaviour of archetypal IDP sequences and demonstrate the rational design of a vast library of multicomponent protein-rich structures that ranges from uniform nano-, meso- and microscale puncta (distinct protein droplets) to multilayered orthogonally phase-separated granular structures. The ability to predict and program IDP-rich assemblies in this fashion offers new insights into (1) genetic-to-molecular-to-macroscale relationships that encode hierarchical IDP assemblies, (2) design rules of such assemblies in cell biology and (3) molecular-level engineering of self-assembled recombinant IDP-rich materials.

  9. Insights into the role of protein molecule size and structure on interfacial properties using designed sequences

    Science.gov (United States)

    Dwyer, Mirjana Dimitrijev; He, Lizhong; James, Michael; Nelson, Andrew; Middelberg, Anton P. J.

    2013-01-01

    Mixtures of a large, structured protein with a smaller, unstructured component are inherently complex and hard to characterize at interfaces, leading to difficulties in understanding their interfacial behaviours and, therefore, formulation optimization. Here, we investigated interfacial properties of such a mixed system. Simplicity was achieved using designed sequences in which chemical differences had been eliminated to isolate the effect of molecular size and structure, namely a short unstructured peptide (DAMP1) and its longer structured protein concatamer (DAMP4). Interfacial tension measurements suggested that the size and bulk structuring of the larger molecule led to much slower adsorption kinetics. Neutron reflectometry at equilibrium revealed that both molecules adsorbed as a monolayer to the air–water interface (indicating unfolding of DAMP4 to give a chain of four connected DAMP1 molecules), with a concentration ratio equal to that in the bulk. This suggests the overall free energy of adsorption is equal despite differences in size and bulk structure. At small interfacial extensional strains, only molecule packing influenced the stress response. At larger strains, the effect of size became apparent, with DAMP4 registering a higher stress response and interfacial elasticity. When both components were present at the interface, most stress-dissipating movement was achieved by DAMP1. This work thus provides insights into the role of proteins' molecular size and structure on their interfacial properties, and the designed sequences introduced here can serve as effective tools for interfacial studies of proteins and polymers. PMID:23303222

  10. Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology

    International Nuclear Information System (INIS)

    Shen Yang; Bax, Ad

    2007-01-01

    Chemical shifts of nuclei in or attached to a protein backbone are exquisitely sensitive to their local environment. A computer program, SPARTA, is described that uses this correlation with local structure to predict protein backbone chemical shifts, given an input three-dimensional structure, by searching a newly generated database for triplets of adjacent residues that provide the best match in φ/ψ/χ 1 torsion angles and sequence similarity to the query triplet of interest. The database contains 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C' chemical shifts for 200 proteins for which a high resolution X-ray (≤2.4 A) structure is available. The relative importance of the weighting factors for the φ/ψ/χ 1 angles and sequence similarity was optimized empirically. The weighted, average secondary shifts of the central residues in the 20 best-matching triplets, after inclusion of nearest neighbor, ring current, and hydrogen bonding effects, are used to predict chemical shifts for the protein of known structure. Validation shows good agreement between the SPARTA-predicted and experimental shifts, with standard deviations of 2.52, 0.51, 0.27, 0.98, 1.07 and 1.08 ppm for 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C', respectively, including outliers

  11. Yeast prions and human prion-like proteins: sequence features and prediction methods.

    Science.gov (United States)

    Cascarina, Sean M; Ross, Eric D

    2014-06-01

    Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis. This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms.

  12. In silico characterization of boron transporter (BOR1 protein sequences in Poaceae species

    Directory of Open Access Journals (Sweden)

    Ertuğrul Filiz

    2013-01-01

    Full Text Available Boron (B is essential for the plant growth and development, and its primary function is connected with formation of the cell wall. Moreover, boron toxicity is a shared problem in semiarid and arid regions. In this study, boron transporter protein (BOR1 sequences from some Poaceae species (Hordeum vulgare subsp. vulgare, Zea mays, Brachypodium distachyon, Oryza sativa subsp. japonica, Oryza sativa subsp. indica, Sorghum bicolor, Triticum aestivum were evaluated by bioinformatics tools. Physicochemical analyses revealed that most of BOR1 proteins were basic character and had generally aliphatic amino acids. Analysis of the domains showed that transmembrane domains were identified constantly and three motifs were detected with 50 amino acids length. Also, the motif SPNPWEPGSYDHWTVAKDMFNVPPAYIFGAFIPATMVAGLYYFDHSVASQ was found most frequently with 25 repeats. The phylogenetic tree showed divergence into two main clusters. B. distachyon species were clustered separately. Finally, this study contributes to the new BOR1 protein characterization in grasses and create scientific base for in silico analysis in future.

  13. Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast

    DEFF Research Database (Denmark)

    Huang, Mingtao; Bai, Yunpeng; Sjostrom, Staffan L.

    2015-01-01

    There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing...... interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used high-throughput microfluidics for the screening of yeast libraries, generated by UV...... mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant a-amylase. Efficient secretion was genetically stable in the selected clones. We performed whole-genome sequencing of the eight clones and identified 330...

  14. From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

    Science.gov (United States)

    Forman-Kay, Julie D.; Mittag, Tanja

    2015-01-01

    Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

  15. Sequence and 3D structure based analysis of TNT degrading proteins in Arabidopsis thaliana.

    Science.gov (United States)

    Bhattacherjee, Amrita; Mandal, Rahul Shubhra; Das, Santasabuj; Kundu, Sudip

    2014-03-01

    TNT, accidentally released at several manufacturing sites, contaminates ground water and soil. It has a toxic effect to algae and invertebrate, and chronic exposure to TNT also causes harmful effects to human. On the other hand, many plants including Arabidopsis thaliana have the ability to metabolize TNT either completely or at least to a reduced less toxic form. In A. thaliana, the enzyme UDP glucosyltransferase (UDPGT) can further conjugate the reduced forms 2-HADNT and 4-HADNT (2-hydroxylamino-4, 6- dinitrotoluene and 4-hydroxylamino-2, 6- dinitrotoluene) of TNT. Based on the experimental analysis, existing literature and phylogenetic analysis, it is evident that among 107 UDPGT proteins only six are involved in the TNT degrading process. A total of 13 UDPGT proteins including five of these TNT degrading proteins fall within the same group of phylogeny. Thus, these 13 UDPGT proteins have been classified into two groups, TNT-degrading and TNT-non-degrading proteins. To understand the differences in TNT-degrading capacities; using homology modeling we first predicted two structures, taking one representative sequence from both the groups. Next, we performed molecular docking of the modeled structure and TNT reduced form 2-hydroxylamino-4, 6- dinitrotoluene (2-HADNT). We observed that while the Trp residue located within the active site region of the TNT- degrading protein showed π-Cation interaction; such type of interaction was absent in TNT-non-degrading protein, as the respective Trp residue lay outside of the pocket in this case. We observed the conservation of this π-Cation interaction during MD simulation of TNT-degrading protein. Thus, the position and the orientation of the active site residue Trp could explain the presence and absence of TNT-degrading capacity of the UDPGT proteins.

  16. Neisseria meningitidis antigen NMB0088: sequence variability, protein topology and vaccine potential.

    Science.gov (United States)

    Sardiñas, Gretel; Yero, Daniel; Climent, Yanet; Caballero, Evelin; Cobas, Karem; Niebla, Olivia

    2009-02-01

    The significance of Neisseria meningitidis serogroup B membrane proteins as vaccine candidates is continually growing. Here, we studied different aspects of antigen NMB0088, a protein that is abundant in outer-membrane vesicle preparations and is thought to be a surface protein. The gene encoding protein NMB0088 was sequenced in a panel of 34 different meningococcal strains with clinical and epidemiological relevance. After this analysis, four variants of NMB0088 were identified; the variability was confined to three specific segments, designated VR1, VR2 and VR3. Secondary structure predictions, refined with alignment analysis and homology modelling using FadL of Escherichia coli, revealed that almost all the variable regions were located in extracellular loop domains. In addition, the NMB0088 antigen was expressed in E. coli and a procedure for obtaining purified recombinant NMB0088 is described. The humoral immune response elicited in BALB/c mice was measured by ELISA and Western blotting, while the functional activity of these antibodies was determined in a serum bactericidal assay and an animal protection model. After immunization in mice, the recombinant protein was capable of inducing a protective response when it was administered inserted into liposomes. According to our results, the recombinant NMB0088 protein may represent a novel antigen for a vaccine against meningococcal disease. However, results from the variability study should be considered for designing a cross-protective formulation in future studies.

  17. Sequencing and Characterization of Novel PII Signaling Protein Gene in Microalga Haematococcus pluvialis

    Directory of Open Access Journals (Sweden)

    Ruijuan Ma

    2017-10-01

    Full Text Available The PII signaling protein is a key protein for controlling nitrogen assimilatory reactions in most organisms, but little information is reported on PII proteins of green microalga Haematococcus pluvialis. Since H. pluvialis cells can produce a large amount of astaxanthin upon nitrogen starvation, its PII protein may represent an important factor on elevated production of Haematococcus astaxanthin. This study identified and isolated the coding gene (HpGLB1 from this microalga. The full-length of HpGLB1 was 1222 bp, including 621 bp coding sequence (CDS, 103 bp 5′ untranslated region (5′ UTR, and 498 bp 3′ untranslated region (3′ UTR. The CDS could encode a protein with 206 amino acids (HpPII. Its calculated molecular weight (Mw was 22.4 kDa and the theoretical isoelectric point was 9.53. When H. pluvialis cells were exposed to nitrogen starvation, the HpGLB1 expression was increased 2.46 times in 48 h, concomitant with the raise of astaxanthin content. This study also used phylogenetic analysis to prove that HpPII was homogeneous to the PII proteins of other green microalgae. The results formed a fundamental basis for the future study on HpPII, for its potential physiological function in Haematococcus astaxanthin biosysthesis.

  18. Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

    International Nuclear Information System (INIS)

    Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank

    2013-01-01

    Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional

  19. Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank, E-mail: fkempken@bot.uni-kiel.de

    2013-08-30

    Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional

  20. muBLASTP: database-indexed protein sequence search on multicore CPUs.

    Science.gov (United States)

    Zhang, Jing; Misra, Sanchit; Wang, Hao; Feng, Wu-Chun

    2016-11-04

    The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.

  1. Purification and sequencing of radish seed calmodulin antagonists phosphorylated by calcium-dependent protein kinase.

    Science.gov (United States)

    Polya, G M; Chandra, S; Condron, R

    1993-02-01

    A family of radish (Raphanus sativus) calmodulin antagonists (RCAs) was purified from seeds by extraction, centrifugation, batch-wise elution from carboxymethyl-cellulose, and high performance liquid chromatography (HPLC) on an SP5PW cation-exchange column. This RCA fraction was further resolved into three calmodulin antagonist polypeptides (RCA1, RCA2, and RCA3) by denaturation in the presence of guanidinium HCl and mercaptoethanol and subsequent reverse-phase HPLC on a C8 column eluted with an acetonitrile gradient in the presence of 0.1% trifluoroacetic acid. The RCA preparation, RCA1, RCA2, RCA3, and other radish seed proteins are phosphorylated by wheat embryo Ca(2+)-dependent protein kinase (CDPK). The RCA preparation contains other CDPK substrates in addition to RCA1, RCA2, and RCA3. The RCA preparation, RCA1, RCA2, and RCA3 inhibit chicken gizzard calmodulin-dependent myosin light chain kinase assayed with a myosin-light chain-based synthetic peptide substrate (fifty percent inhibitory concentrations of RCA2 and RCA3 are about 7 and 2 microM, respectively). N-terminal sequencing by sequential Edman degradation of RCA1, RCA2, and RCA3 revealed sequences having a high homology with the small subunit of the storage protein napin from Brassica napus and with related proteins. The deduced amino acid sequences of RCA1, RCA2, RCA3, and RCA3' (a subform of RCA3) have agreement with average molecular masses from electrospray mass spectrometry of 4537, 4543, 4532, and 4560 kD, respectively. The only sites for serine phosphorylation are near or at the C termini and hence adjacent to the sites of proteolytic precursor cleavage.

  2. Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

    International Nuclear Information System (INIS)

    Keefe, L.J.; Lattman, E.E.; Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J.

    1992-01-01

    Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal α helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.)

  3. Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

    Energy Technology Data Exchange (ETDEWEB)

    Keefe, L.J.; Lattman, E.E. (Dept. of Biophysics and Biophysical Chemistry, Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)); Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J. (Middle Atlantic Mass Spectrometry Lab., Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States))

    1992-04-01

    Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal {alpha} helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.).

  4. Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource.

    Science.gov (United States)

    Sharpton, Thomas J; Jospin, Guillaume; Wu, Dongying; Langille, Morgan G I; Pollard, Katherine S; Eisen, Jonathan A

    2012-10-13

    New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as "Sifting Families," or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology-based analyses. We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/).

  5. Zucchini yellow mosaic virus: biological properties, detection procedures and comparison of coat protein gene sequences.

    Science.gov (United States)

    Coutts, B A; Kehoe, M A; Webster, C G; Wylie, S J; Jones, R A C

    2011-12-01

    Between 2006 and 2010, 5324 samples from at least 34 weed, two cultivated legume and 11 native species were collected from three cucurbit-growing areas in tropical or subtropical Western Australia. Two new alternative hosts of zucchini yellow mosaic virus (ZYMV) were identified, the Australian native cucurbit Cucumis maderaspatanus, and the naturalised legume species Rhyncosia minima. Low-level (0.7%) seed transmission of ZYMV was found in seedlings grown from seed collected from zucchini (Cucurbita pepo) fruit infected with isolate Cvn-1. Seed transmission was absent in >9500 pumpkin (C. maxima and C. moschata) seedlings from fruit infected with isolate Knx-1. Leaf samples from symptomatic cucurbit plants collected from fields in five cucurbit-growing areas in four Australian states were tested for the presence of ZYMV. When 42 complete coat protein (CP) nucleotide (nt) sequences from the new ZYMV isolates obtained were compared to those of 101 complete CP nt sequences from five other continents, phylogenetic analysis of the 143 ZYMV sequences revealed three distinct groups (A, B and C), with four subgroups in A (I-IV) and two in B (I-II). The new Australian sequences grouped according to collection location, fitting within A-I, A-II and B-II. The 16 new sequences from one isolated location in tropical northern Western Australia all grouped into subgroup B-II, which contained no other isolates. In contrast, the three sequences from the Northern Territory fitted into A-II with 94.6-99.0% nt identities with isolates from the United States, Iran, China and Japan. The 23 new sequences from the central west coast and two east coast locations all fitted into A-I, with 95.9-98.9% nt identities to sequences from Europe and Japan. These findings suggest that (i) there have been at least three separate ZYMV introductions into Australia and (ii) there are few changes to local isolate CP sequences following their establishment in remote growing areas. Isolates from A-I and B

  6. Bm86 midgut protein sequence variation in South Texas cattle fever ticks

    Directory of Open Access Journals (Sweden)

    Kammlah Diane M

    2010-11-01

    Full Text Available Abstract Background Cattle fever ticks, Rhipicephalus (Boophilus microplus and R. (B. annulatus, vector bovine and equine babesiosis, and have significantly expanded beyond the permanent quarantine zone established in South Texas. Currently, there are no vaccines approved for use within the United States for controlling these vectors. Vaccines developed in Australia and Cuba based on the midgut antigen Bm86 have variable efficacy against cattle fever ticks. A possible explanation for this variation in vaccine efficacy is amino acid sequence divergence between the recombinant Bm86 vaccine component and native Bm86 expressed in ticks from different geographical regions of the world. Results There was 91.8% amino acid sequence identity in Bm86 among R. microplus and R. annulatus sequenced from South Texas infestations. When South Texas isolates were compared to the Australian Yeerongpilly and Cuban Camcord vaccine strains, there was 89.8% and 90.0% identity, respectively. Most of the sequence divergence was focused in one region of the protein, amino acids 206-298. Hydrophilicity profiles revealed that two short regions of Bm86 (amino acids 206-210 and 560-570 appear to be more hydrophilic in South Texas isolates compared to vaccine strains. Only one amino acid difference was found between South Texas and vaccine strains within two previously described B-cell epitopes. A total of 4 amino acid differences were observed within three peptides previously shown to induce protective immune responses in cattle. Conclusions Sequence differences between South Texas isolates and Yeerongpilly and Camcord strains are spread throughout the entire Bm86 sequence, suggesting that geographic variation does exist. Differences within previously described B-cell epitopes between South Texas isolates and vaccine strains are minimal; however, short regions of hydrophilic amino acids found unique to South Texas isolates suggest that additional unique surface exposed

  7. Amino acid sequences mediating vascular cell adhesion molecule 1 binding to integrin alpha 4: homologous DSP sequence found for JC polyoma VP1 coat protein

    Directory of Open Access Journals (Sweden)

    Michael Andrew Meyer

    2013-07-01

    Full Text Available The JC polyoma viral coat protein VP1 was analyzed for amino acid sequences homologies to the IDSP sequence which mediates binding of VLA-4 (integrin alpha 4 to vascular cell adhesion molecule 1. Although the full sequence was not found, a DSP sequence was located near the critical arginine residue linked to infectivity of the virus and binding to sialic acid containing molecules such as integrins (3. For the JC polyoma virus, a DSP sequence was found at residues 70, 71 and 72 with homology also noted for the mouse polyoma virus and SV40 virus. Three dimensional modeling of the VP1 molecule suggests that the DSP loop has an accessible site for interaction from the external side of the assembled viral capsid pentamer.

  8. The use of orthologous sequences to predict the impact of amino acid substitutions on protein function.

    Directory of Open Access Journals (Sweden)

    Nicholas J Marini

    2010-05-01

    Full Text Available Computational predictions of the functional impact of genetic variation play a critical role in human genetics research. For nonsynonymous coding variants, most prediction algorithms make use of patterns of amino acid substitutions observed among homologous proteins at a given site. In particular, substitutions observed in orthologous proteins from other species are often assumed to be tolerated in the human protein as well. We examined this assumption by evaluating a panel of nonsynonymous mutants of a prototypical human enzyme, methylenetetrahydrofolate reductase (MTHFR, in a yeast cell-based functional assay. As expected, substitutions in human MTHFR at sites that are well-conserved across distant orthologs result in an impaired enzyme, while substitutions present in recently diverged sequences (including a 9-site mutant that "resurrects" the human-macaque ancestor result in a functional enzyme. We also interrogated 30 sites with varying degrees of conservation by creating substitutions in the human enzyme that are accepted in at least one ortholog of MTHFR. Quite surprisingly, most of these substitutions were deleterious to the human enzyme. The results suggest that selective constraints vary between phylogenetic lineages such that inclusion of distant orthologs to infer selective pressures on the human enzyme may be misleading. We propose that homologous proteins are best used to reconstruct ancestral sequences and infer amino acid conservation among only direct lineal ancestors of a particular protein. We show that such an "ancestral site preservation" measure outperforms other prediction methods, not only in our selected set for MTHFR, but also in an exhaustive set of E. coli LacI mutants.

  9. Discovering approximate-associated sequence patterns for protein-DNA interactions

    KAUST Repository

    Chan, Tak Ming

    2010-12-30

    Motivation: The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations. Results: A progressive approach is proposed to address the approximation to alleviate the computational requirements. Firstly, similar TFBSs are grouped from the available TF-TFBS data (TRANSFAC database). Secondly, approximate and highly conserved binding cores are discovered from TF sequences corresponding to each TFBS group. A customized algorithm is developed for the specific objective. We discover the approximate TF-TFBS rules by associating the grouped TFBS consensuses and TF cores. The rules discovered are evaluated by matching (verifying with) the actual protein-DNA binding pairs from Protein Data Bank (PDB) 3D structures. The approximate results exhibit many more verified rules and up to 300% better verification ratios than the exact ones. The customized algorithm achieves over 73% better verification ratios than traditional methods. Approximate rules (64-79%) are shown statistically significant. Detailed variation analysis and conservation verification on NCBI records demonstrate that the approximate rules reveal both the flexible and specific protein-DNA interactions accurately. The approximate TF-TFBS rules discovered show great generalized capability of exploring more informative binding rules. © The Author 2010. Published by Oxford University Press. All rights reserved.

  10. Molecular Simulations of Sequence-Specific Association of Transmembrane Proteins in Lipid Bilayers

    Science.gov (United States)

    Doxastakis, Manolis; Prakash, Anupam; Janosi, Lorant

    2011-03-01

    Association of membrane proteins is central in material and information flow across the cellular membranes. Amino-acid sequence and the membrane environment are two critical factors controlling association, however, quantitative knowledge on such contributions is limited. In this work, we study the dimerization of helices in lipid bilayers using extensive parallel Monte Carlo simulations with recently developed algorithms. The dimerization of Glycophorin A is examined employing a coarse-grain model that retains a level of amino-acid specificity, in three different phospholipid bilayers. Association is driven by a balance of protein-protein and lipid-induced interactions with the latter playing a major role at short separations. Following a different approach, the effect of amino-acid sequence is studied using the four transmembrane domains of the epidermal growth factor receptor family in identical lipid environments. Detailed characterization of dimer formation and estimates of the free energy of association reveal that these helices present significant affinity to self-associate with certain dimers forming non-specific interfaces.

  11. The Ising model for prediction of disordered residues from protein sequence alone

    International Nuclear Information System (INIS)

    Lobanov, Michail Yu; Galzitskaya, Oxana V

    2011-01-01

    Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered residues and disordered regions in protein chains using protein sequence alone. A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered. The model is an approximation of the Ising model in which the interaction term between neighbors has been replaced by a penalty for changing between states (the energy of border). The IsUnstruct has been compared with other available methods and found to perform well. The method correctly finds 77% of disordered residues as well as 87% of ordered residues in the CASP8 database, and 72% of disordered residues as well as 85% of ordered residues in the DisProt database

  12. A maize spermine synthase 1 PEST sequence fused to the GUS reporter protein facilitates proteolytic degradation.

    Science.gov (United States)

    Maruri-López, Israel; Rodríguez-Kessler, Margarita; Rodríguez-Hernández, Aída Araceli; Becerra-Flora, Alicia; Olivares-Grajales, Juan Elías; Jiménez-Bremont, Juan Francisco

    2014-05-01

    Polyamines are low molecular weight aliphatic compounds involved in various biochemical, cellular and physiological processes in all organisms. In plants, genes involved in polyamine biosynthesis and catabolism are regulated at transcriptional, translational, and posttranslational level. In this research, we focused on the characterization of a PEST sequence (rich in proline, glutamic acid, serine, and threonine) of the maize spermine synthase 1 (ZmSPMS1). To this aim, 123 bp encoding 40 amino acids of the C-terminal region of the ZmSPMS1 enzyme containing the PEST sequence were fused to the GUS reporter gene. This fusion was evaluated in Arabidopsis thaliana transgenic lines and onion monolayers transient expression system. The ZmSPMS1 PEST sequence leads to specific degradation of the GUS reporter protein. It is suggested that the 26S proteasome may be involved in GUS::PEST fusion degradation in both onion and Arabidopsis. The PEST sequences appear to be present in plant spermine synthases, mainly in monocots. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  13. Structural analysis of a repetitive protein sequence motif in strepsirrhine primate amelogenin.

    Directory of Open Access Journals (Sweden)

    Rodrigo S Lacruz

    2011-03-01

    Full Text Available Strepsirrhines are members of a primate suborder that has a distinctive set of features associated with the development of the dentition. Amelogenin (AMEL, the better known of the enamel matrix proteins, forms 90% of the secreted organic matrix during amelogenesis. Although AMEL has been sequenced in numerous mammalian lineages, the only reported strepsirrhine AMEL sequences are those of the ring-tailed lemur and galago, which contain a set of additional proline-rich tandem repeats absent in all other primates species analyzed to date, but present in some non-primate mammals. Here, we first determined that these repeats are present in AMEL from three additional lemur species and thus are likely to be widespread throughout this group. To evaluate the functional relevance of these repeats in strepsirrhines, we engineered a mutated murine amelogenin sequence containing a similar proline-rich sequence to that of Lemur catta. In the monomeric form, the MQP insertions had no influence on the secondary structure or refolding properties, whereas in the assembled form, the insertions increased the hydrodynamic radii. We speculate that increased AMEL nanosphere size may influence enamel formation in strepsirrhine primates.

  14. Prediction of the aggregation propensity of proteins from the primary sequence: aggregation properties of proteomes.

    Science.gov (United States)

    Castillo, Virginia; Graña-Montes, Ricardo; Sabate, Raimon; Ventura, Salvador

    2011-06-01

    In the cell, protein folding into stable globular conformations is in competition with aggregation into non-functional and usually toxic structures, since the biophysical properties that promote folding also tend to favor intermolecular contacts, leading to the formation of β-sheet-enriched insoluble assemblies. The formation of protein deposits is linked to at least 20 different human disorders, ranging from dementia to diabetes. Furthermore, protein deposition inside cells represents a major obstacle for the biotechnological production of polypeptides. Importantly, the aggregation behavior of polypeptides appears to be strongly influenced by the intrinsic properties encoded in their sequences and specifically by the presence of selective short regions with high aggregation propensity. This allows computational methods to be used to analyze the aggregation properties of proteins without the previous requirement for structural information. Applications range from the identification of individual amyloidogenic regions in disease-linked polypeptides to the analysis of the aggregation properties of complete proteomes. Herein, we review these theoretical approaches and illustrate how they have become important and useful tools in understanding the molecular mechanisms underlying protein aggregation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. High Performance Protein Sequence Database Scanning on the Cell Broadband Engine

    Directory of Open Access Journals (Sweden)

    Adrianto Wirawan

    2009-01-01

    Full Text Available The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.

  16. Structural protein descriptors in 1-dimension and their sequence-based predictions.

    Science.gov (United States)

    Kurgan, Lukasz; Disfani, Fatemeh Miri

    2011-09-01

    The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

  17. Complete amino acid sequences of the ribosomal proteins L25, L29 and L31 from the archaebacterium Halobacterium marismortui.

    Science.gov (United States)

    Hatakeyama, T; Kimura, M

    1988-03-15

    Ribosomal proteins were extracted from 50S ribosomal subunits of the archaebacterium Halobacterium marismortui by decreasing the concentration of Mg2+ and K+, and the proteins were separated and purified by ion-exchange column chromatography on DEAE-cellulose. Ten proteins were purified to homogeneity and three of these proteins were subjected to sequence analysis. The complete amino acid sequences of the ribosomal proteins L25, L29 and L31 were established by analyses of the peptides obtained by enzymatic digestion with trypsin, Staphylococcus aureus protease, chymotrypsin and lysylendopeptidase. Proteins L25, L29 and L31 consist of 84, 115 and 95 amino acid residues with the molecular masses of 9472 Da, 12293 Da and 10418 Da respectively. A comparison of their sequences with those of other large-ribosomal-subunit proteins from other organisms revealed that protein L25 from H. marismortui is homologous to protein L23 from Escherichia coli (34.6%), Bacillus stearothermophilus (41.8%), and tobacco chloroplasts (16.3%) as well as to protein L25 from yeast (38.0%). Proteins L29 and L31 do not appear to be homologous to any other ribosomal proteins whose structures are so far known.

  18. Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences

    NARCIS (Netherlands)

    Lentes, K.U.; Mathieu, E.; Bischoff, Rainer; Rasmussen, U.B.; Pavirani, A.

    1993-01-01

    Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%,

  19. A structural study for the optimisation of functional motifs encoded in protein sequences

    Directory of Open Access Journals (Sweden)

    Helmer-Citterich Manuela

    2004-04-01

    Full Text Available Abstract Background A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure. Results Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases, the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed. Conclusion Our method can be applied to any type of functional motif or pattern (not only PROSITE ones which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of

  20. Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

    Science.gov (United States)

    Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

    2017-04-15

    RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. A Novel Indirect Sequence Readout Component in the E. coli Cyclic AMP Receptor Protein Operator

    DEFF Research Database (Denmark)

    Lindemose, Søren; Nielsen, Peter Eigil; Valentin-Hansen, Poul

    2014-01-01

    binding sites in the E. coli genome, but the exact role of the N6 region in CRP interaction has not previously been systematic examined. Here we employ an in vitro selection system based on a randomized N6 spacer region to demonstrate that CRP binding to the lacP1 site may be enhanced up to 14-fold......The cyclic AMP receptor protein (CRP) from Escherichia coli has been extensively studied for several decades. In particular, a detailed characterization of CRP interaction with DNA has been obtained. The CRP dimer recognizes a consensus sequence AANTGTGANNNNNNTCACANTT through direct amino acid...

  2. Genepleio software for effective estimation of gene pleiotropy from protein sequences.

    Science.gov (United States)

    Chen, Wenhai; Chen, Dandan; Zhao, Ming; Zou, Yangyun; Zeng, Yanwu; Gu, Xun

    2015-01-01

    Though pleiotropy, which refers to the phenomenon of a gene affecting multiple traits, has long played a central role in genetics, development, and evolution, estimation of the number of pleiotropy components remains a hard mission to accomplish. In this paper, we report a newly developed software package, Genepleio, to estimate the effective gene pleiotropy from phylogenetic analysis of protein sequences. Since this estimate can be interpreted as the minimum pleiotropy of a gene, it is used to play a role of reference for many empirical pleiotropy measures. This work would facilitate our understanding of how gene pleiotropy affects the pattern of genotype-phenotype map and the consequence of organismal evolution.

  3. Biomolecular characterization and protein sequences of the Campanian hadrosaur B. canadensis.

    Science.gov (United States)

    Schweitzer, Mary H; Zheng, Wenxia; Organ, Chris L; Avci, Recep; Suo, Zhiyong; Freimark, Lisa M; Lebleu, Valerie S; Duncan, Michael B; Vander Heiden, Matthew G; Neveu, John M; Lane, William S; Cottrell, John S; Horner, John R; Cantley, Lewis C; Kalluri, Raghu; Asara, John M

    2009-05-01

    Molecular preservation in non-avian dinosaurs is controversial. We present multiple lines of evidence that endogenous proteinaceous material is preserved in bone fragments and soft tissues from an 80-million-year-old Campanian hadrosaur, Brachylophosaurus canadensis [Museum of the Rockies (MOR) 2598]. Microstructural and immunological data are consistent with preservation of multiple bone matrix and vessel proteins, and phylogenetic analyses of Brachylophosaurus collagen sequenced by mass spectrometry robustly support the bird-dinosaur clade, consistent with an endogenous source for these collagen peptides. These data complement earlier results from Tyrannosaurus rex (MOR 1125) and confirm that molecular preservation in Cretaceous dinosaurs is not a unique event.

  4. Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein

    DEFF Research Database (Denmark)

    Lannergård, Jonas; Kristensen, Bodil M.; Gustafsson, Mattias C. U.

    2015-01-01

    The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms...... fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant...

  5. Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

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    Madlung Johannes

    2010-05-01

    Full Text Available Abstract Background Often high-quality MS/MS spectra of tryptic peptides do not match to any database entry because of only partially sequenced genomes and therefore, protein identification requires de novo peptide sequencing. To achieve protein identification of the economically important but still unsequenced plant pathogenic oomycete Plasmopara halstedii, we first evaluated the performance of three different de novo peptide sequencing algorithms applied to a protein digests of standard proteins using a quadrupole TOF (QStar Pulsar i. Results The performance order of the algorithms was PEAKS online > PepNovo > CompNovo. In summary, PEAKS online correctly predicted 45% of measured peptides for a protein test data set. All three de novo peptide sequencing algorithms were used to identify MS/MS spectra of tryptic peptides of an unknown 57 kDa protein of P. halstedii. We found ten de novo sequenced peptides that showed homology to a Phytophthora infestans protein, a closely related organism of P. halstedii. Employing a second complementary approach, verification of peptide prediction and protein identification was performed by creation of degenerate primers for RACE-PCR and led to an ORF of 1,589 bp for a hypothetical phosphoenolpyruvate carboxykinase. Conclusions Our study demonstrated that identification of proteins within minute amounts of sample material improved significantly by combining sensitive LC-MS methods with different de novo peptide sequencing algorithms. In addition, this is the first study that verified protein prediction from MS data by also employing a second complementary approach, in which RACE-PCR led to identification of a novel elicitor protein in P. halstedii.

  6. Automation of C-terminal sequence analysis of 2D-PAGE separated proteins

    Directory of Open Access Journals (Sweden)

    P.P. Moerman

    2014-06-01

    Full Text Available Experimental assignment of the protein termini remains essential to define the functional protein structure. Here, we report on the improvement of a proteomic C-terminal sequence analysis method. The approach aims to discriminate the C-terminal peptide in a CNBr-digest where Met-Xxx peptide bonds are cleaved in internal peptides ending at a homoserine lactone (hsl-derivative. pH-dependent partial opening of the lactone ring results in the formation of doublets for all internal peptides. C-terminal peptides are distinguished as singlet peaks by MALDI-TOF MS and MS/MS is then used for their identification. We present a fully automated protocol established on a robotic liquid-handling station.

  7. Large-scale identification of odorant-binding proteins and chemosensory proteins from expressed sequence tags in insects

    Science.gov (United States)

    2009-01-01

    Background Insect odorant binding proteins (OBPs) and chemosensory proteins (CSPs) play an important role in chemical communication of insects. Gene discovery of these proteins is a time-consuming task. In recent years, expressed sequence tags (ESTs) of many insect species have accumulated, thus providing a useful resource for gene discovery. Results We have developed a computational pipeline to identify OBP and CSP genes from insect ESTs. In total, 752,841 insect ESTs were examined from 54 species covering eight Orders of Insecta. From these ESTs, 142 OBPs and 177 CSPs were identified, of which 117 OBPs and 129 CSPs are new. The complete open reading frames (ORFs) of 88 OBPs and 123 CSPs were obtained by electronic elongation. We randomly chose 26 OBPs from eight species of insects, and 21 CSPs from four species for RT-PCR validation. Twenty two OBPs and 16 CSPs were confirmed by RT-PCR, proving the efficiency and reliability of the algorithm. Together with all family members obtained from the NCBI (OBPs) or the UniProtKB (CSPs), 850 OBPs and 237 CSPs were analyzed for their structural characteristics and evolutionary relationship. Conclusions A large number of new OBPs and CSPs were found, providing the basis for deeper understanding of these proteins. In addition, the conserved motif and evolutionary analysis provide some new insights into the evolution of insect OBPs and CSPs. Motif pattern fine-tune the functions of OBPs and CSPs, leading to the minor difference in binding sex pheromone or plant volatiles in different insect Orders. PMID:20034407

  8. A stochastic context free grammar based framework for analysis of protein sequences

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    Nebel Jean-Christophe

    2009-10-01

    Full Text Available Abstract Background In the last decade, there have been many applications of formal language theory in bioinformatics such as RNA structure prediction and detection of patterns in DNA. However, in the field of proteomics, the size of the protein alphabet and the complexity of relationship between amino acids have mainly limited the application of formal language theory to the production of grammars whose expressive power is not higher than stochastic regular grammars. However, these grammars, like other state of the art methods, cannot cover any higher-order dependencies such as nested and crossing relationships that are common in proteins. In order to overcome some of these limitations, we propose a Stochastic Context Free Grammar based framework for the analysis of protein sequences where grammars are induced using a genetic algorithm. Results This framework was implemented in a system aiming at the production of binding site descriptors. These descriptors not only allow detection of protein regions that are involved in these sites, but also provide insight in their structure. Grammars were induced using quantitative properties of amino acids to deal with the size of the protein alphabet. Moreover, we imposed some structural constraints on grammars to reduce the extent of the rule search space. Finally, grammars based on different properties were combined to convey as much information as possible. Evaluation was performed on sites of various sizes and complexity described either by PROSITE patterns, domain profiles or a set of patterns. Results show the produced binding site descriptors are human-readable and, hence, highlight biologically meaningful features. Moreover, they achieve good accuracy in both annotation and detection. In addition, findings suggest that, unlike current state-of-the-art methods, our system may be particularly suited to deal with patterns shared by non-homologous proteins. Conclusion A new Stochastic Context Free

  9. Creation and structure determination of an artificial protein with three complete sequence repeats

    Energy Technology Data Exchange (ETDEWEB)

    Adachi, Motoyasu, E-mail: adachi.motoyasu@jaea.go.jp; Shimizu, Rumi; Kuroki, Ryota [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Blaber, Michael [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Florida State University, Tallahassee, FL 32306-4300 (United States)

    2013-11-01

    An artificial protein with three complete sequence repeats was created and the structure was determined by X-ray crystallography. The structure showed threefold symmetry even though there is an amino- and carboxy-terminal. The artificial protein with threefold symmetry may be useful as a scaffold to capture small materials with C3 symmetry. Symfoil-4P is a de novo protein exhibiting the threefold symmetrical β-trefoil fold designed based on the human acidic fibroblast growth factor. First three asparagine–glycine sequences of Symfoil-4P are replaced with glutamine–glycine (Symfoil-QG) or serine–glycine (Symfoil-SG) sequences protecting from deamidation, and His-Symfoil-II was prepared by introducing a protease digestion site into Symfoil-QG so that Symfoil-II has three complete repeats after removal of the N-terminal histidine tag. The Symfoil-QG and SG and His-Symfoil-II proteins were expressed in Eschericha coli as soluble protein, and purified by nickel affinity chromatography. Symfoil-II was further purified by anion-exchange chromatography after removing the HisTag by proteolysis. Both Symfoil-QG and Symfoil-II were crystallized in 0.1 M Tris-HCl buffer (pH 7.0) containing 1.8 M ammonium sulfate as precipitant at 293 K; several crystal forms were observed for Symfoil-QG and II. The maximum diffraction of Symfoil-QG and II crystals were 1.5 and 1.1 Å resolution, respectively. The Symfoil-II without histidine tag diffracted better than Symfoil-QG with N-terminal histidine tag. Although the crystal packing of Symfoil-II is slightly different from Symfoil-QG and other crystals of Symfoil derivatives having the N-terminal histidine tag, the refined crystal structure of Symfoil-II showed pseudo-threefold symmetry as expected from other Symfoils. Since the removal of the unstructured N-terminal histidine tag did not affect the threefold structure of Symfoil, the improvement of diffraction quality of Symfoil-II may be caused by molecular characteristics of

  10. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences

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    Ji-Yong An

    2016-05-01

    Full Text Available Protein-Protein Interactions (PPIs play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM model and Average Blocks (AB to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed

  11. An expressed sequence tag (EST) data mining strategy succeeding in the discovery of new G-protein coupled receptors.

    Science.gov (United States)

    Wittenberger, T; Schaller, H C; Hellebrand, S

    2001-03-30

    We have developed a comprehensive expressed sequence tag database search method and used it for the identification of new members of the G-protein coupled receptor superfamily. Our approach proved to be especially useful for the detection of expressed sequence tag sequences that do not encode conserved parts of a protein, making it an ideal tool for the identification of members of divergent protein families or of protein parts without conserved domain structures in the expressed sequence tag database. At least 14 of the expressed sequence tags found with this strategy are promising candidates for new putative G-protein coupled receptors. Here, we describe the sequence and expression analysis of five new members of this receptor superfamily, namely GPR84, GPR86, GPR87, GPR90 and GPR91. We also studied the genomic structure and chromosomal localization of the respective genes applying in silico methods. A cluster of six closely related G-protein coupled receptors was found on the human chromosome 3q24-3q25. It consists of four orphan receptors (GPR86, GPR87, GPR91, and H963), the purinergic receptor P2Y1, and the uridine 5'-diphosphoglucose receptor KIAA0001. It seems likely that these receptors evolved from a common ancestor and therefore might have related ligands. In conclusion, we describe a data mining procedure that proved to be useful for the identification and first characterization of new genes and is well applicable for other gene families. Copyright 2001 Academic Press.

  12. Radiation signatures

    International Nuclear Information System (INIS)

    McGlynn, S.P.; Varma, M.N.

    1992-01-01

    A new concept for modelling radiation risk is proposed. This concept is based on the proposal that the spectrum of molecular lesions, which we dub ''the radiation signature'', can be used to identify the quality of the causal radiation. If the proposal concerning radiation signatures can be established then, in principle, both prospective and retrospective risk determination can be assessed on an individual basis. A major goal of biophysical modelling is to relate physical events such as ionization, excitation, etc. to the production of radiation carcinogenesis. A description of the physical events is provided by track structure. The track structure is determined by radiation quality, and it can be considered to be the ''physical signature'' of the radiation. Unfortunately, the uniqueness characteristics of this signature are dissipated in biological systems in ∼10 -9 s. Nonetheless, it is our contention that this physical disturbance of the biological system eventuates later, at ∼10 0 s, in molecular lesion spectra which also characterize the causal radiation. (author)

  13. Nucleotide sequence of the coat protein gene of Lettuce big-vein virus.

    Science.gov (United States)

    Sasaya, T; Ishikawa, K; Koganezawa, H

    2001-06-01

    A sequence of 1425 nt was established that included the complete coat protein (CP) gene of Lettuce big-vein virus (LBVV). The LBVV CP gene encodes a 397 amino acid protein with a predicted M(r) of 44486. Antisera raised against synthetic peptides corresponding to N-terminal or C-terminal parts of the LBVV CP reacted in Western blot analysis with a protein with an M(r) of about 48000. RNA extracted from purified particles of LBVV by using proteinase K, SDS and phenol migrated in gels as two single-stranded RNA species of approximately 7.3 kb (ss-1) and 6.6 kb (ss-2). After denaturation by heat and annealing at room temperature, the RNA migrated as four species, ss-1, ss-2 and two additional double-stranded RNAs (ds-1 and ds-2). The Northern blot hybridization analysis using riboprobes from a full-length clone of the LBVV CP gene indicated that ss-2 has a negative-sense nature and contains the LBVV CP gene. Moreover, ds-2 is a double-stranded form of ss-2. Database searches showed that the LBVV CP most resembled the nucleocapsid proteins of rhabdoviruses. These results indicate that it would be appropriate to classify LBVV as a negative-sense single-stranded RNA virus rather than as a double-stranded RNA virus.

  14. Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

    Science.gov (United States)

    Tan, Yen Hock; Huang, He; Kihara, Daisuke

    2006-08-15

    Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

  15. Enhanced production of recombinant proteins with Corynebacterium glutamicum by deletion of insertion sequences (IS elements).

    Science.gov (United States)

    Choi, Jae Woong; Yim, Sung Sun; Kim, Min Jeong; Jeong, Ki Jun

    2015-12-29

    In most bacteria, various jumping genetic elements including insertion sequences elements (IS elements) cause a variety of genetic rearrangements resulting in harmful effects such as genome and recombinant plasmid instability. The genetic stability of a plasmid in a host is critical for high-level production of recombinant proteins, and in this regard, the development of an IS element-free strain could be a useful strategy for the enhanced production of recombinant proteins. Corynebacterium glutamicum, which is a workhorse in the industrial-scale production of various biomolecules including recombinant proteins, also has several IS elements, and it is necessary to identify the critical IS elements and to develop IS element deleted strain. From the cultivation of C. glutamicum harboring a plasmid for green fluorescent protein (GFP) gene expression, non-fluorescent clones were isolated by FACS (fluorescent activated cell sorting). All the isolated clones had insertions of IS elements in the GFP coding region, and two major IS elements (ISCg1 and ISCg2 families) were identified. By co-cultivating cells harboring either the isolated IS element-inserted plasmid or intact plasmid, it was clearly confirmed that cells harboring the IS element-inserted plasmids became dominant during the cultivation due to their growth advantage over cells containing intact plasmids, which can cause a significant reduction in recombinant protein production during cultivation. To minimize the harmful effects of IS elements on the expression of heterologous genes in C. glutamicum, two IS element free C. glutamicum strains were developed in which each major IS element was deleted, and enhanced productivity in the engineered C. glutamicum strain was successfully demonstrated with three models: GFP, poly(3-hydroxybutyrate) [P(3HB)] and γ-aminobutyrate (GABA). Our findings clearly indicate that the hopping of IS elements could be detrimental to the production of recombinant proteins in C

  16. Functional and Structural Overview of G-Protein-Coupled Receptors Comprehensively Obtained from Genome Sequences

    Directory of Open Access Journals (Sweden)

    Makiko Suwa

    2011-04-01

    Full Text Available An understanding of the functional mechanisms of G-protein-coupled receptors (GPCRs is very important for GPCR-related drug design. We have developed an integrated GPCR database (SEVENS http://sevens.cbrc.jp/ that includes 64,090 reliable GPCR genes comprehensively identified from 56 eukaryote genome sequences, and overviewed the sequences and structure spaces of the GPCRs. In vertebrates, the number of receptors for biological amines, peptides, etc. is conserved in most species, whereas the number of chemosensory receptors for odorant, pheromone, etc. significantly differs among species. The latter receptors tend to be single exon type or a few exon type and show a high ratio in the numbers of GPCRs, whereas some families, such as Class B and Class C receptors, have long lengths due to the presence of many exons. Statistical analyses of amino acid residues reveal that most of the conserved residues in Class A GPCRs are found in the cytoplasmic half regions of transmembrane (TM helices, while residues characteristic to each subfamily found on the extracellular half regions. The 69 of Protein Data Bank (PDB entries of complete or fragmentary structures could be mapped on the TM/loop regions of Class A GPCRs covering 14 subfamilies.

  17. Molecular identification based on coat protein sequences of the Barley yellow dwarf virus from Brazil

    Directory of Open Access Journals (Sweden)

    Talita Bernardon Mar

    2013-12-01

    Full Text Available Yellow dwarf disease, one of the most important diseases of cereal crops worldwide, is caused by virus species belonging to the Luteoviridae family. Forty-two virus isolates obtained from oat (Avena sativa L., wheat (Triticum aestivum L., barley (Hordeum vulgare L., corn (Zea mays L., and ryegrass (Lolium multiflorum Lam. collected between 2007 and 2008 from winter cereal crop regions in southern Brazil were screened by polymerase chain reaction (PCR with primers designed on ORF 3 (coat protein - CP for the presence of Barley yellow dwarf virus and Cereal yellow dwarf virus (B/CYDV. PCR products of expected size (~357 bp for subgroup II and (~831 bp for subgroup I were obtained for three and 39 samples, respectively. These products were cloned and sequenced. The subgroup II 3' partial CP amino acid deduced sequences were identified as BYDV-RMV (92 - 93 % of identity with "Illinois" Z14123 isolate. The complete CP amino acid deduced sequences of subgroup I isolates were confirmed as BYDV-PAV (94 - 99 % of identity and established a very homogeneous group (identity higher than 99 %. These results support the prevalence of BYDV-PAV in southern Brazil as previously diagnosed by Enzyme-Linked Immunosorbent Assay (ELISA and suggest that this population is very homogeneous. To our knowledge, this is the first report of BYDV-RMV in Brazil and the first genetic diversity study on B/CYDV in South America.

  18. Molecular Identification and Sequencing of Mannose Binding Protein (MBP Gene of Acanthamoeba palestinensis

    Directory of Open Access Journals (Sweden)

    M Rezaeian

    2010-02-01

    Full Text Available "nBackground: Acanthamoeba keratitis develops by pathogenic Acanthamoeba such as A. pal­es­tinen­sis. Indeed this species is one of the known causative agents of amoebic keratitis in Iran. Mannose Binding Protein (MBP is the main pathogenicity factors for developing this sight threatening disease. We aimed to characterize MBP gene in pathogenic Acanthamoeba isolates such as A. palestinensis."nMethods: This experimental research was performed in the School of Public Health, Tehran University of Medical Sciences, Tehran, Iran during 2007-2008.  A. palestinensis was grown on 2% non-nutrient agar overlaid with Escherichia coli. DNA extraction was performed using phenol-chloroform method. PCR reaction and amplification were done using specific primer pairs of MBP. The amplified fragment were purified and sequenced. Finally, the obtained fragment was deposited in the gene data bank."nResults: A 900 bp PCR-product was recovered after PCR reaction. Sequence analysis of the purified PCR product revealed a gene with 943 nucleotides. Homology analysis of the ob­tained sequence showed 81% similarity with the available MBP gene in the gene data bank. The fragment was deposited in the gene data bank under accession number EU678895"nConclusion: MBP is known as the most important factor in Acanthamoeba pathogenesis cas­cade. Therefore, characterization of this gene can aid in developing better therapeutic agents and even immunization of high-risk people.

  19. Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

    Science.gov (United States)

    2013-01-01

    Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction

  20. FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

    2006-01-01

    FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...

  1. DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

    Science.gov (United States)

    Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

    2018-02-15

    A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  2. Staggering in signature partners of A∼190 mass region of superdeformed rotational bands

    International Nuclear Information System (INIS)

    Uma, V.S.; Goel, Alpana; Yadav, Archana

    2014-01-01

    This paper discuss about ΔI=1 signature splitting in signature partner pairs of A∼190 mass region. Around twenty signature partner pairs (usually called as two bands, each with a fixed signature) have been reported in this mass region. For these signature pairs, band head moment of inertia (J 0 ) and intrinsic structure of each pair of signature partners have been found as almost identical. Also, these signature partner pairs showed large amplitude signature splitting. As each of the two signature partner forms a regular spin sequence and signature bands are not equivalent in terms of energies. This difference in energies results in signature splitting

  3. Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

    Directory of Open Access Journals (Sweden)

    Lees Jonathan G

    2008-01-01

    Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

  4. DNA-binding proteins from marine bacteria expand the known sequence diversity of TALE-like repeats.

    Science.gov (United States)

    de Lange, Orlando; Wolf, Christina; Thiel, Philipp; Krüger, Jens; Kleusch, Christian; Kohlbacher, Oliver; Lahaye, Thomas

    2015-11-16

    Transcription Activator-Like Effectors (TALEs) of Xanthomonas bacteria are programmable DNA binding proteins with unprecedented target specificity. Comparative studies into TALE repeat structure and function are hindered by the limited sequence variation among TALE repeats. More sequence-diverse TALE-like proteins are known from Ralstonia solanacearum (RipTALs) and Burkholderia rhizoxinica (Bats), but RipTAL and Bat repeats are conserved with those of TALEs around the DNA-binding residue. We study two novel marine-organism TALE-like proteins (MOrTL1 and MOrTL2), the first to date of non-terrestrial origin. We have assessed their DNA-binding properties and modelled repeat structures. We found that repeats from these proteins mediate sequence specific DNA binding conforming to the TALE code, despite low sequence similarity to TALE repeats, and with novel residues around the BSR. However, MOrTL1 repeats show greater sequence discriminating power than MOrTL2 repeats. Sequence alignments show that there are only three residues conserved between repeats of all TALE-like proteins including the two new additions. This conserved motif could prove useful as an identifier for future TALE-likes. Additionally, comparing MOrTL repeats with those of other TALE-likes suggests a common evolutionary origin for the TALEs, RipTALs and Bats. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Eukaryote-wide sequence analysis of mitochondrial β-barrel outer membrane proteins

    Directory of Open Access Journals (Sweden)

    Fujita Naoya

    2011-01-01

    Full Text Available Abstract Background The outer membranes of mitochondria are thought to be homologous to the outer membranes of Gram negative bacteria, which contain 100's of distinct families of β-barrel membrane proteins (BOMPs often forming channels for transport of nutrients or drugs. However, only four families of mitochondrial BOMPs (MBOMPs have been confirmed to date. Although estimates as high as 100 have been made in the past, the number of yet undiscovered MBOMPs is an open question. Fortunately, the recent discovery of a membrane integration signal (the β-signal for MBOMPs gave us an opportunity to look for undiscovered MBOMPs. Results We present the results of a comprehensive survey of eukaryotic protein sequences intended to identify new MBOMPs. Our search employs recent results on β-signals as well as structural information and a novel BOMP predictor trained on both bacterial and mitochondrial BOMPs. Our principal finding is circumstantial evidence suggesting that few MBOMPs remain to be discovered, if one assumes that, like known MBOMPs, novel MBOMPs will be monomeric and β-signal dependent. In addition to this, our analysis of MBOMP homologs reveals some exceptions to the current model of the β-signal, but confirms its consistent presence in the C-terminal region of MBOMP proteins. We also report a β-signal independent search for MBOMPs against the yeast and Arabidopsis proteomes. We find no good candidates MBOMPs in yeast but the Arabidopsis results are less conclusive. Conclusions Our results suggest there are no remaining MBOMPs left to discover in yeast; and if one assumes all MBOMPs are β-signal dependent, few MBOMP families remain undiscovered in any sequenced organism.

  6. Nucleotide sequence of cloned cDNA for human sphingolipid activator protein 1 precursor

    International Nuclear Information System (INIS)

    Dewji, N.N.; Wenger, D.A.; O'Brien, J.S.

    1987-01-01

    Two cDNA clones encoding prepro-sphingolipid activator protein 1 (SAP-1) were isolated from a λ gt11 human hepatoma expression library using polyclonal antibodies. These had inserts of ≅ 2 kilobases (λ-S-1.2 and λ-S-1.3) and both were both homologous with a previously isolated clone (λ-S-1.1) for mature SAP-1. The authors report here the nucleotide sequence of the longer two EcoRI fragments of S-1.2 and S-1.3 that were not the same and the derived amino acid sequences of mature SAP-1 and its prepro form. The open reading frame encodes 19 amino acids, which are colinear with the amino-terminal sequence of mature SAP-1, and extends far beyond the predicted carboxyl terminus of mature SAP-1, indicating extensive carboxyl-terminal processing. The nucleotide sequence of cDNA encoding prepro-SAP-1 includes 1449 bases from the assigned initiation codon ATG at base-pair 472 to the stop codon TGA at base-pair 1921. The first 23 amino acids coded after the initiation ATG are characteristic of a signal peptide. The calculated molecular mass for a polypeptide encoded by 1449 bases is ≅ 53 kDa, in keeping with the reported value for pro-SAP-1. The data indicate that after removal of the signal peptide mature SAP-1 is generated by removing an additional 7 amino acids from the amino terminus and ≅ 373 amino acids from the carboxyl terminus. One potential glycosylation site was previously found in mature SAP-1. Three additional potential glycosylation sites are present in the processed carboxyl-terminal polypeptide, which they designate as P-2

  7. Large scale identification and categorization of protein sequences using structured logistic regression.

    Directory of Open Access Journals (Sweden)

    Bjørn P Pedersen

    Full Text Available BACKGROUND: Structured Logistic Regression (SLR is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well-suited for this task. The classification of P-type ATPases, a large family of ATP-driven membrane pumps transporting essential cations, was selected as a test-case that would generate important biological information as well as provide a proof-of-concept for the application of SLR to a large scale bioinformatics problem. RESULTS: Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known sequences, we analysed 9.3 million sequences in the UniProtKB and attempted to classify a large number of P-type ATPases. To examine the distribution of pumps on organisms, we also applied SLR to 1,123 complete genomes from the Entrez genome database. Finally, we analysed the predicted membrane topology of the identified P-type ATPases. CONCLUSIONS: Using the SLR-based classification tool we are able to run a large scale study of P-type ATPases. This study provides proof-of-concept for the application of SLR to a bioinformatics problem and the analysis of P-type ATPases pinpoints new and interesting targets for further biochemical characterization and structural analysis.

  8. Proteomic analysis of an environmental isolate of Rhodotorula mucilaginosa after arsenic and cadmium challenge: Identification of a protein expression signature for heavy metal exposure.

    Science.gov (United States)

    Ilyas, Sidra; Rehman, Abdul; Coelho, Ana Varela; Sheehan, David

    2016-06-01

    A metal-resistant Rhodotorula mucilaginosa strain was isolated from an industrial wastewater. Effects on reduced/oxidized glutathione (GSSG/GSH), antioxidant enzymes and proteome were assessed on metal challenge (100mg/L). Increased GSH (mM/g) was found with CdCl2 (18.43±3.34), NaAsO2 (14.76±2.14), CuSO4 (14.73±2.49), and Pb(NO3)2 (15.74±5.3) versus control (7.67±0.95). GSH:GSSG ratio decreased with CdCl2, NaAsO2, and Pb(NO3)2 but not with CuSO4 and cysteine-containing protein levels increased with CdCl2 and NaAsO2. NaAsO2 exposure enhanced glutathione transferase activity but this decreased with CdCl2. Both metals significantly increased glutathione reductase and catalase activities. Metabolism-dependent uptake of Cd and As (12-day exposure) of approximately 65mg/g was observed in live cells with greater cell surface interaction for As compared to Cd. A particular role for arsenic oxidase in As resistance was identified. One dimensional electrophoresis revealed higher oxidation of protein thiols in response to NaAsO2 than to CdCl2. Two dimensional electrophoresis showed altered abundance of some proteins on metal treatment. Selected spots were excised for mass spectrometry and seven proteins identified. Under oxidative stress conditions, xylose reductase, putative chitin deacetylase, 20S proteasome subunit, eukaryotic translation elongation factor 2, valine-tRNA ligase and a metabolic enzyme F0F1 ATP synthase alpha subunit were all expressed as well as a unique hypothetical protein. These may comprise a protein expression signature for metal-induced oxidation in this yeast. Fungi are of widespread importance in agriculture, biodegradation and often show extensive tolerance to heavy metals. This makes them of interest from the perspective of bioremediation. In this study an environmental isolate of R. mucilaginosa showing extensive tolerance of a panel of heavy metals, in particular cadmium and arsenic, was studied. Several biochemical parameters such as

  9. Identification, sequence analysis, and characterization of serine/threonine protein kinase 17A from Clonorchis sinensis.

    Science.gov (United States)

    Huang, Lisi; Lv, Xiaoli; Huang, Yan; Hu, Yue; Yan, Haiyan; Zheng, Minghui; Zeng, Hua; Li, Xuerong; Liang, Chi; Wu, Zhongdao; Yu, Xinbing

    2014-05-01

    This is the first report of a novel protein from Clonorchis sinensis (C. sinensis), serine/threonine protein kinase 17A (CsSTK17A), which belongs to a member of the death-associated protein kinase (DAPK) family known to regulate diverse biological processes. The full-length sequence encoding CsSTK17A was isolated from C. sinensis adult cDNA plasmid library. Two transcribed isoforms of the gene were identified from the genome of C. sinensis. CsSTK17A contains a kinase domain at the N-terminus that shares a degree of conservation with the DAPK families. Besides, the catalytic domain contains 11 subdomains conserved among STKs and shares the highest identity with STK from Schistosoma mansoni (55.9%). Three-dimensional structure of CsSTK17A displays the canonical STK fold, including the helix C, P-loop, and the activation loop. We obtained recombinant CsSTK17A (rCsSTK17A) and anti-rCsSTK17A IgG. The rCsSTK17A could be probed by anti-rCsSTK17A rat serum, C. sinensis-infected rat serum and the sera from rats immunized with C. sinensis excretory-secretory products, indicating that it is a circulating antigen possessing a strong immunocompetence. Moreover, quantitative RT-PCR and western blotting analyses revealed that CsSTK17A exhibited the highest mRNA and protein expression level in eggs, followed by metacercariae and adult worms. Intriguingly, in the immunolocalization assay, CsSTK17A was intensively localized to the operculum region of eggs in uterus, as well as the vitelline gland of both adult worm and metacercaria, implying that the protein was associated with the reproduction and development of C. sinensis. Overall, these fundamental studies might contribute to further researches on signaling systems of the parasite.

  10. Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

    Science.gov (United States)

    Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

    2016-01-01

    3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

  11. Amino acid sequences of the ribosomal proteins HL30 and HmaL5 from the archaebacterium Halobacterium marismortui.

    Science.gov (United States)

    Hatakeyama, T; Hatakeyama, T

    1990-07-06

    The complete amino acid sequences of the ribosomal proteins HL30 and HmaL5 from the archaebacterium Halobacterium marismortui were determined. Protein HL30 was found to be acetylated at its N-terminal amino acid and shows homology to the eukaryotic ribosomal proteins YL34 from yeast and RL31 from rat. Protein HmaL5 was homologous to the protein L5 from Escherichia coli and Bacillus stearothermophilus as well as to YL16 from yeast. HmaL5 shows more similarities to its eukaryotic counterpart than to eubacterial ones.

  12. PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Balachandran Manavalan

    2018-03-01

    Full Text Available Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

  13. PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

    Science.gov (United States)

    Manavalan, Balachandran; Shin, Tae H; Lee, Gwang

    2018-01-01

    Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

  14. Cloning and Sequencing of Protein Kinase cDNA from Harbor Seal (Phoca vitulina Lymphocytes

    Directory of Open Access Journals (Sweden)

    Jennifer C. C. Neale

    2004-01-01

    Full Text Available Protein kinases (PKs play critical roles in signal transduction and activation of lymphocytes. The identification of PK genes provides a tool for understanding mechanisms of immunotoxic xenobiotics. As part of a larger study investigating persistent organic pollutants in the harbor seal and their possible immunomodulatory actions, we sequenced harbor seal cDNA fragments encoding PKs. The procedure, using degenerate primers based on conserved motifs of human protein tyrosine kinases (PTKs, successfully amplified nine phocid PK gene fragments with high homology to human and rodent orthologs. We identified eight PTKs and one dual (serine/threonine and tyrosine kinase. Among these were several PKs important in early signaling events through the B- and T-cell receptors (FYN, LYN, ITK and SYK and a MAP kinase involved in downstream signal transduction. V-FGR, RET and DDR2 were also expressed. Sequential activation of protein kinases ultimately induces gene transcription leading to the proliferation and differentiation of lymphocytes critical to adaptive immunity. PKs are potential targets of bioactive xenobiotics, including persistent organic pollutants of the marine environment; characterization of these molecules in the harbor seal provides a foundation for further research illuminating mechanisms of action of contaminants speculated to contribute to large-scale die-offs of marine mammals via immunosuppression.

  15. Comparative sequence analysis of acid sensitive/resistance proteins in Escherichia coli and Shigella flexneri

    Science.gov (United States)

    Manikandan, Selvaraj; Balaji, Seetharaaman; Kumar, Anil; Kumar, Rita

    2007-01-01

    The molecular basis for the survival of bacteria under extreme conditions in which growth is inhibited is a question of great current interest. A preliminary study was carried out to determine residue pattern conservation among the antiporters of enteric bacteria, responsible for extreme acid sensitivity especially in Escherichia coli and Shigella flexneri. Here we found the molecular evidence that proved the relationship between E. coli and S. flexneri. Multiple sequence alignment of the gadC coded acid sensitive antiporter showed many conserved residue patterns at regular intervals at the N-terminal region. It was observed that as the alignment approaches towards the C-terminal, the number of conserved residues decreases, indicating that the N-terminal region of this protein has much active role when compared to the carboxyl terminal. The motif, FHLVFFLLLGG, is well conserved within the entire gadC coded protein at the amino terminal. The motif is also partially conserved among other antiporters (which are not coded by gadC) but involved in acid sensitive/resistance mechanism. Phylogenetic cluster analysis proves the relationship of Escherichia coli and Shigella flexneri. The gadC coded proteins are converged as a clade and diverged from other antiporters belongs to the amino acid-polyamine-organocation (APC) superfamily. PMID:21670792

  16. Optimal protein library design using recombination or point mutations based on sequence-based scoring functions.

    Science.gov (United States)

    Pantazes, Robert J; Saraf, Manish C; Maranas, Costas D

    2007-08-01

    In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.

  17. BLAST screening of chlamydial genomes to identify signature proteins that are unique for the Chlamydiales, Chlamydiaceae, Chlamydophila and Chlamydia groups of species

    Directory of Open Access Journals (Sweden)

    Gupta Radhey S

    2006-01-01

    Full Text Available Abstract Background Chlamydiae species are of much importance from a clinical viewpoint. Their diversity both in terms of their numbers as well as clinical involvement are presently believed to be significantly underestimated. The obligate intracellular nature of chlamydiae has also limited their genetic and biochemical studies. Thus, it is of importance to develop additional means for their identification and characterization. Results We have carried out analyses of available chlamydiae genomes to identify sets of unique proteins that are either specific for all Chlamydiales genomes, or different Chlamydiaceae family members, or members of the Chlamydia and Chlamydophila genera, or those unique to Protochlamydia amoebophila, but which are not found in any other bacteria. In total, 59 Chlamydiales-specific proteins, 79 Chlamydiaceae-specific proteins, 20 proteins each that are specific for both Chlamydia and Chlamydophila and 445 ORFs that are Protochlamydia-specific were identified. Additionally, 33 cases of possible gene loss or lateral gene transfer were also detected. Conclusion The identified chlamydiae-lineage specific proteins, many of which are highly conserved, provide novel biomarkers that should prove of much value in the diagnosis of these bacteria and in exploration of their prevalence and diversity. These conserved protein sequences (CPSs also provide novel therapeutic targets for drugs that are specific for these bacteria. Lastly, functional studies on these chlamydiae or chlamydiae subgroup-specific proteins should lead to important insights into lineage-specific adaptations with regards to development, infectivity and pathogenicity.

  18. DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

    KAUST Repository

    Kulmanov, Maxat

    2017-09-27

    Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

  19. Amino acid sequence analysis of the annexin super-gene family of proteins.

    Science.gov (United States)

    Barton, G J; Newman, R H; Freemont, P S; Crumpton, M J

    1991-06-15

    The annexins are a widespread family of calcium-dependent membrane-binding proteins. No common function has been identified for the family and, until recently, no crystallographic data existed for an annexin. In this paper we draw together 22 available annexin sequences consisting of 88 similar repeat units, and apply the techniques of multiple sequence alignment, pattern matching, secondary structure prediction and conservation analysis to the characterisation of the molecules. The analysis clearly shows that the repeats cluster into four distinct families and that greatest variation occurs within the repeat 3 units. Multiple alignment of the 88 repeats shows amino acids with conserved physicochemical properties at 22 positions, with only Gly at position 23 being absolutely conserved in all repeats. Secondary structure prediction techniques identify five conserved helices in each repeat unit and patterns of conserved hydrophobic amino acids are consistent with one face of a helix packing against the protein core in predicted helices a, c, d, e. Helix b is generally hydrophobic in all repeats, but contains a striking pattern of repeat-specific residue conservation at position 31, with Arg in repeats 4 and Glu in repeats 2, but unconserved amino acids in repeats 1 and 3. This suggests repeats 2 and 4 may interact via a buried saltbridge. The loop between predicted helices a and b of repeat 3 shows features distinct from the equivalent loop in repeats 1, 2 and 4, suggesting an important structural and/or functional role for this region. No compelling evidence emerges from this study for uteroglobin and the annexins sharing similar tertiary structures, or for uteroglobin representing a derivative of a primordial one-repeat structure that underwent duplication to give the present day annexins. The analyses performed in this paper are re-evaluated in the Appendix, in the light of the recently published X-ray structure for human annexin V. The structure confirms most of

  20. Ginger and turmeric expressed sequence tags identify signature genes for rhizome identity and development and the biosynthesis of curcuminoids, gingerols and terpenoids

    Science.gov (United States)

    2013-01-01

    Background Ginger (Zingiber officinale) and turmeric (Curcuma longa) accumulate important pharmacologically active metabolites at high levels in their rhizomes. Despite their importance, relatively little is known regarding gene expression in the rhizomes of ginger and turmeric. Results In order to identify rhizome-enriched genes and genes encoding specialized metabolism enzymes and pathway regulators, we evaluated an assembled collection of expressed sequence tags (ESTs) from eight different ginger and turmeric tissues. Comparisons to publicly available sorghum rhizome ESTs revealed a total of 777 gene transcripts expressed in ginger/turmeric and sorghum rhizomes but apparently absent from other tissues. The list of rhizome-specific transcripts was enriched for genes associated with regulation of tissue growth, development, and transcription. In particular, transcripts for ethylene response factors and AUX/IAA proteins appeared to accumulate in patterns mirroring results from previous studies regarding rhizome growth responses to exogenous applications of auxin and ethylene. Thus, these genes may play important roles in defining rhizome growth and development. Additional associations were made for ginger and turmeric rhizome-enriched MADS box transcription factors, their putative rhizome-enriched homologs in sorghum, and rhizomatous QTLs in rice. Additionally, analysis of both primary and specialized metabolism genes indicates that ginger and turmeric rhizomes are primarily devoted to the utilization of leaf supplied sucrose for the production and/or storage of specialized metabolites associated with the phenylpropanoid pathway and putative type III polyketide synthase gene products. This finding reinforces earlier hypotheses predicting roles of this enzyme class in the production of curcuminoids and gingerols. Conclusion A significant set of genes were found to be exclusively or preferentially expressed in the rhizome of ginger and turmeric. Specific

  1. Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource

    Directory of Open Access Journals (Sweden)

    Sharpton Thomas J

    2012-10-01

    Full Text Available Abstract Background New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. Results We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as “Sifting Families,” or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology–based analyses. Conclusions We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/.

  2. Sequence characterization of heat shock protein gene of Cyclospora cayetanensis isolates from Nepal, Mexico, and Peru.

    Science.gov (United States)

    Sulaiman, Irshad M; Torres, Patricia; Simpson, Steven; Kerdahi, Khalil; Ortega, Ynes

    2013-04-01

    We have described the development of a 2-step nested PCR protocol based on the characterization of the 70-kDa heat shock protein (HSP70) gene for rapid detection of the human-pathogenic Cyclospora cayetanensis parasite. We tested and validated these newly designed primer sets by PCR amplification followed by nucleotide sequencing of PCR-amplified HSP70 fragments belonging to 16 human C. cayetanensis isolates from 3 different endemic regions that include Nepal, Mexico, and Peru. No genetic polymorphism was observed among the isolates at the characterized regions of the HSP70 locus. This newly developed HSP70 gene-based nested PCR protocol provides another useful genetic marker for the rapid detection of C. cayetanensis in the future.

  3. From the genome sequence to the protein inventory of Bacillus subtilis.

    Science.gov (United States)

    Becher, Dörte; Büttner, Knut; Moche, Martin; Hessling, Bernd; Hecker, Michael

    2011-08-01

    Owing to the low number of proteins necessary to render a bacterial cell viable, bacteria are extremely attractive model systems to understand how the genome sequence is translated into actual life processes. One of the most intensively investigated model organisms is Bacillus subtilis. It has attracted world-wide research interest, addressing cell differentiation and adaptation on a molecular scale as well as biotechnological production processes. Meanwhile, we are looking back on more than 25 years of B. subtilis proteomics. A wide range of methods have been developed during this period for the large-scale qualitative and quantitative proteome analysis. Currently, it is possible to identify and quantify more than 50% of the predicted proteome in different cellular subfractions. In this review, we summarize the development of B. subtilis proteomics during the past 25 years. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Genepleio Software for Effective Estimation of Gene Pleiotropy from Protein Sequences

    Directory of Open Access Journals (Sweden)

    Wenhai Chen

    2015-01-01

    Full Text Available Though pleiotropy, which refers to the phenomenon of a gene affecting multiple traits, has long played a central role in genetics, development, and evolution, estimation of the number of pleiotropy components remains a hard mission to accomplish. In this paper, we report a newly developed software package, Genepleio, to estimate the effective gene pleiotropy from phylogenetic analysis of protein sequences. Since this estimate can be interpreted as the minimum pleiotropy of a gene, it is used to play a role of reference for many empirical pleiotropy measures. This work would facilitate our understanding of how gene pleiotropy affects the pattern of genotype-phenotype map and the consequence of organismal evolution.

  5. Deep Sequencing Reveals Uncharted Isoform Heterogeneity of the Protein-Coding Transcriptome in Cerebral Ischemia.

    Science.gov (United States)

    Bhattarai, Sunil; Aly, Ahmed; Garcia, Kristy; Ruiz, Diandra; Pontarelli, Fabrizio; Dharap, Ashutosh

    2018-06-03

    Gene expression in cerebral ischemia has been a subject of intense investigations for several years. Studies utilizing probe-based high-throughput methodologies such as microarrays have contributed significantly to our existing knowledge but lacked the capacity to dissect the transcriptome in detail. Genome-wide RNA-sequencing (RNA-seq) enables comprehensive examinations of transcriptomes for attributes such as strandedness, alternative splicing, alternative transcription start/stop sites, and sequence composition, thus providing a very detailed account of gene expression. Leveraging this capability, we conducted an in-depth, genome-wide evaluation of the protein-coding transcriptome of the adult mouse cortex after transient focal ischemia at 6, 12, or 24 h of reperfusion using RNA-seq. We identified a total of 1007 transcripts at 6 h, 1878 transcripts at 12 h, and 1618 transcripts at 24 h of reperfusion that were significantly altered as compared to sham controls. With isoform-level resolution, we identified 23 splice variants arising from 23 genes that were novel mRNA isoforms. For a subset of genes, we detected reperfusion time-point-dependent splice isoform switching, indicating an expression and/or functional switch for these genes. Finally, for 286 genes across all three reperfusion time-points, we discovered multiple, distinct, simultaneously expressed and differentially altered isoforms per gene that were generated via alternative transcription start/stop sites. Of these, 165 isoforms derived from 109 genes were novel mRNAs. Together, our data unravel the protein-coding transcriptome of the cerebral cortex at an unprecedented depth to provide several new insights into the flexibility and complexity of stroke-related gene transcription and transcript organization.

  6. Uncovering Biological Network Function via Graphlet Degree Signatures

    Directory of Open Access Journals (Sweden)

    Nataša Pržulj

    2008-01-01

    Full Text Available Motivation: Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker’s yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the entire proteome based on protein-protein interaction (PPI networks. Since proteins interact to perform a certain function, analyzing structural properties of PPI networks may provide useful clues about the biological function of individual proteins, protein complexes they participate in, and even larger subcellular machines.Results: We design a sensitive graph theoretic method for comparing local structures of node neighborhoods that demonstrates that in PPI networks, biological function of a node and its local network structure are closely related. The method summarizes a protein’s local topology in a PPI network into the vector of graphlet degrees called the signature of the protein and computes the signature similarities between all protein pairs. We group topologically similar proteins under this measure in a PPI network and show that these protein groups belong to the same protein complexes, perform the same biological functions, are localized in the same subcellular compartments, and have the same tissue expressions. Moreover, we apply our technique on a proteome-scale network data and infer biological function of yet unclassified proteins demonstrating that our method can provide valuable guidelines for future experimental research such as disease protein prediction.Availability: Data is available upon request.

  7. Maternal protein restriction during lactation induces early and lasting plasma metabolomic and hepatic lipidomic signatures of the offspring in a rodent programming model.

    Science.gov (United States)

    Martin Agnoux, Aurore; El Ghaziri, Angélina; Moyon, Thomas; Pagniez, Anthony; David, Agnès; Simard, Gilles; Parnet, Patricia; Qannari, El Mostafa; Darmaun, Dominique; Antignac, Jean-Philippe; Alexandre-Gouabau, Marie-Cécile

    2018-05-01

    Perinatal undernutrition affects not only fetal and neonatal growth but also adult health outcome, as suggested by the metabolic imprinting concept. However, the exact mechanisms underlying offspring metabolic adaptations are not yet fully understood. Specifically, it remains unclear whether the gestation or the lactation is the more vulnerable period to modify offspring metabolic flexibility. We investigated in a rodent model of intrauterine growth restriction (IUGR) induced by maternal protein restriction (R) during gestation which time window of maternal undernutrition (gestation, lactation or gestation-lactation) has more impact on the male offspring metabolomics phenotype. Plasma metabolome and hepatic lipidome of offspring were characterized through suckling period and at adulthood using liquid chromatography-high-resolution mass spectrometry. Multivariate analysis of these fingerprints highlighted a persistent metabolomics signature in rats suckled by R dams, with a clear-cut discrimination from offspring fed by control (C) dams. Pups submitted to a nutritional switch at birth presented a metabolomics signature clearly distinct from that of pups nursed by dams maintained on a consistent perinatal diet. Control rats suckled by R dams presented transiently higher branched-chain amino acid (BCAA) oxidation during lactation besides increased fatty acid (FA) β-oxidation, associated with preserved insulin sensitivity and lesser fat accretion that persisted throughout their life. In contrast, IUGR rats displayed permanently impaired β-oxidation, associated to increased glucose or BCAA oxidation at adulthood, depending on the fact that pups experienced slow postnatal or catch-up growth, as suckled by R or C dams, respectively. Taken together, these findings provide evidence for a significant contribution of the lactation period in metabolic programming. Copyright © 2018 Elsevier Inc. All rights reserved.

  8. SATCHMO-JS: a webserver for simultaneous protein multiple sequence alignment and phylogenetic tree construction.

    Science.gov (United States)

    Hagopian, Raffi; Davidson, John R; Datta, Ruchira S; Samad, Bushra; Jarvis, Glen R; Sjölander, Kimmen

    2010-07-01

    We present the jump-start simultaneous alignment and tree construction using hidden Markov models (SATCHMO-JS) web server for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic trees. The server takes as input a set of sequences in FASTA format, and outputs a phylogenetic tree and MSA; these can be viewed online or downloaded from the website. SATCHMO-JS is an extension of the SATCHMO algorithm, and employs a divide-and-conquer strategy to jump-start SATCHMO at a higher point in the phylogenetic tree, reducing the computational complexity of the progressive all-versus-all HMM-HMM scoring and alignment. Results on a benchmark dataset of 983 structurally aligned pairs from the PREFAB benchmark dataset show that SATCHMO-JS provides a statistically significant improvement in alignment accuracy over MUSCLE, Multiple Alignment using Fast Fourier Transform (MAFFT), ClustalW and the original SATCHMO algorithm. The SATCHMO-JS webserver is available at http://phylogenomics.berkeley.edu/satchmo-js. The datasets used in these experiments are available for download at http://phylogenomics.berkeley.edu/satchmo-js/supplementary/.

  9. The master two-dimensional gel database of human AMA cell proteins: towards linking protein and genome sequence and mapping information (update 1991)

    DEFF Research Database (Denmark)

    Celis, J E; Leffers, H; Rasmussen, H H

    1991-01-01

    autoantigens" and "cDNAs". For convenience we have included an alphabetical list of all known proteins recorded in this database. In the long run, the main goal of this database is to link protein and DNA sequencing and mapping information (Human Genome Program) and to provide an integrated picture......The master two-dimensional gel database of human AMA cells currently lists 3801 cellular and secreted proteins, of which 371 cellular polypeptides (306 IEF; 65 NEPHGE) were added to the master images during the last 10 months. These include: (i) very basic and acidic proteins that do not focus...

  10. Oleosome-Associated Protein of the Oleaginous Diatom Fistulifera solaris Contains an Endoplasmic Reticulum-Targeting Signal Sequence

    Directory of Open Access Journals (Sweden)

    Yoshiaki Maeda

    2014-06-01

    Full Text Available Microalgae tend to accumulate lipids as an energy storage material in the specific organelle, oleosomes. Current studies have demonstrated that lipids derived from microalgal oleosomes are a promising source of biofuels, while the oleosome formation mechanism has not been fully elucidated. Oleosome-associated proteins have been identified from several microalgae to elucidate the fundamental mechanisms of oleosome formation, although understanding their functions is still in infancy. Recently, we discovered a diatom-oleosome-associated-protein 1 (DOAP1 from the oleaginous diatom, Fistulifera solaris JPCC DA0580. The DOAP1 sequence implied that this protein might be transported into the endoplasmic reticulum (ER due to the signal sequence. To ensure this, we fused the signal sequence to green fluorescence protein. The fusion protein distributed around the chloroplast as like a meshwork membrane structure, indicating the ER localization. This result suggests that DOAP1 could firstly localize at the ER, then move to the oleosomes. This study also demonstrated that the DOAP1 signal sequence allowed recombinant proteins to be specifically expressed in the ER of the oleaginous diatom. It would be a useful technique for engineering the lipid synthesis pathways existing in the ER, and finally controlling the biofuel quality.

  11. Protein domain analysis of genomic sequence data reveals regulation of LRR related domains in plant transpiration in Ficus.

    Science.gov (United States)

    Lang, Tiange; Yin, Kangquan; Liu, Jinyu; Cao, Kunfang; Cannon, Charles H; Du, Fang K

    2014-01-01

    Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.

  12. Sequence Variation in Rhoptry Neck Protein 10 Gene among Toxoplasma gondii Isolates from Different Hosts and Geographical Locations.

    Science.gov (United States)

    Zhao, Yu; Zhou, Donghui; Chen, Jia; Sun, Xiaolin

    2017-01-01

    Toxoplasma gondii, as a eukaryotic parasite of the phylum Apicomplexa, can infect almost all the warm-blooded animals and humans, causing toxoplasmosis. Rhoptry neck proteins (RONs) play a key role in the invasion process of T. gondii and are potential vaccine candidate molecules against toxoplasmosis. The present study examined sequence variation in the rhoptry neck protein 10 (TgRON10) gene among 10 T. gondii isolates from different hosts and geographical locations from Lanzhou province during 2014, and compared with the corresponding sequences of strains ME49 and VEG obtained from the ToxoDB database, using polymerase chain reaction (PCR) amplification, sequence analysis, and phylogenetic reconstruction by Bayesian inference (BI) and maximum parsimony (MP). Analysis of all the 12 TgRON10 genomic and cDNA sequences revealed 7 exons and 6 introns in the TgRON10 gDNA. The complete genomic sequence of the TgRON10 gene ranged from 4759 bp to 4763 bp, and sequence variation was 0-0.6% among the 12 T. gondii isolates, indicating a low sequence variation in TgRON10 gene. Phylogenetic analysis of TgRON10 sequences showed that the cluster of the 12 T. gondii isolates was not completely consistent with their respective genotypes. TgRON10 gene is not a suitable genetic marker for the differentiation of T. gondii isolates from different hosts and geographical locations, but may represent a potential vaccine candidate against toxoplasmosis, worth further studies.

  13. Parameters of proteome evolution from histograms of amino-acid sequence identities of paralogous proteins

    Directory of Open Access Journals (Sweden)

    Yan Koon-Kiu

    2007-11-01

    Full Text Available Abstract Background The evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins. Results We introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form ~ p-γ with the value of the exponent γ around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent α ≈ 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate. Conclusion We separately measure the short-term ("raw" duplication and deletion rates rdup∗ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaemOCai3aa0baaSqaaiabbsgaKjabbwha1jabbchaWbqaaiabgEHiQaaaaaa@3283@, rdel∗ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaemOCai3aa0baaSqaaiabbsga

  14. Cluster based on sequence comparison of homologous proteins of 95 organism species - Gclust Server | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Gclust Server Cluster based on sequence comparison of homologous proteins of 95 organism spe...cies Data detail Data name Cluster based on sequence comparison of homologous proteins of 95 organism specie...istory of This Database Site Policy | Contact Us Cluster based on sequence compariso

  15. Coilin, the signature protein of Cajal bodies, differentially modulates the interactions of plants with viruses in widely different taxa

    OpenAIRE

    Shaw, Jane; Love, Andrew J; Makarova, Svetlana S; Kalinina, Natalia O; Harrison, Bryan D; Taliansky, Michael E

    2014-01-01

    Cajal bodies (CBs) are distinct nuclear bodies physically and functionally associated with the nucleolus. In addition to their traditional function in coordinating maturation of certain nuclear RNAs, CBs participate in cell cycle regulation, development, and regulation of stress responses. A key “signature” component of CBs is coilin, the scaffolding protein essential for CB formation and function. Using an RNA silencing (loss-of-function) approach, we describe here new phenomena whereby coil...

  16. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.

    Science.gov (United States)

    Wang, Yanbin; You, Zhuhong; Li, Xiao; Chen, Xing; Jiang, Tonghai; Zhang, Jingting

    2017-05-11

    Protein-protein interactions (PPIs) are essential for most living organisms' process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori , the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.

  17. ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files.

    Science.gov (United States)

    Büssow, Konrad; Hoffmann, Steve; Sievert, Volker

    2002-12-19

    Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.

  18. The Number, Organization, and Size of Polymorphic Membrane Protein Coding Sequences as well as the Most Conserved Pmp Protein Differ within and across Chlamydia Species.

    Science.gov (United States)

    Van Lent, Sarah; Creasy, Heather Huot; Myers, Garry S A; Vanrompay, Daisy

    2016-01-01

    Variation is a central trait of the polymorphic membrane protein (Pmp) family. The number of pmp coding sequences differs between Chlamydia species, but it is unknown whether the number of pmp coding sequences is constant within a Chlamydia species. The level of conservation of the Pmp proteins has previously only been determined for Chlamydia trachomatis. As different Pmp proteins might be indispensible for the pathogenesis of different Chlamydia species, this study investigated the conservation of Pmp proteins both within and across C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci. The pmp coding sequences were annotated in 16 C. trachomatis, 6 C. pneumoniae, 2 C. abortus, and 16 C. psittaci genomes. The number and organization of polymorphic membrane coding sequences differed within and across the analyzed Chlamydia species. The length of coding sequences of pmpA,pmpB, and pmpH was conserved among all analyzed genomes, while the length of pmpE/F and pmpG, and remarkably also of the subtype pmpD, differed among the analyzed genomes. PmpD, PmpA, PmpH, and PmpA were the most conserved Pmp in C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci, respectively. PmpB was the most conserved Pmp across the 4 analyzed Chlamydia species. © 2016 S. Karger AG, Basel.

  19. Nucleotide sequence of a human cDNA encoding a ras-related protein (rap1B)

    Energy Technology Data Exchange (ETDEWEB)

    Pizon, V; Lerosey, I; Chardin, P; Tavitian, A [INSERM, Paris (France)

    1988-08-11

    The authors have previously characterized two human ras-related genes rap1 and rap2. Using the rap1 clone as probe they isolated and sequenced a new rap cDNA encoding the 184aa rap1B protein. The rap1B protein is 95% identical to rap1 and shares several properties with the ras protein suggesting that it could bind GTP/GDP and have a membrane location. As for rap1, the structural characteristics of rap1B suggest that the rap and ras proteins might interact on the same effector.

  20. Transduplication resulted in the incorporation of two protein-coding sequences into the Turmoil-1 transposable element of C. elegans

    Directory of Open Access Journals (Sweden)

    Pupko Tal

    2008-10-01

    Full Text Available Abstract Transposable elements may acquire unrelated gene fragments into their sequences in a process called transduplication. Transduplication of protein-coding genes is common in plants, but is unknown of in animals. Here, we report that the Turmoil-1 transposable element in C. elegans has incorporated two protein-coding sequences into its inverted terminal repeat (ITR sequences. The ITRs of Turmoil-1 contain a conserved RNA recognition motif (RRM that originated from the rsp-2 gene and a fragment from the protein-coding region of the cpg-3 gene. We further report that an open reading frame specific to C. elegans may have been created as a result of a Turmoil-1 insertion. Mutations at the 5' splice site of this open reading frame may have reactivated the transduplicated RRM motif. Reviewers This article was reviewed by Dan Graur and William Martin. For the full reviews, please go to the Reviewers' Reports section.

  1. OXBench: A benchmark for evaluation of protein multiple sequence alignment accuracy

    Directory of Open Access Journals (Sweden)

    Searle Stephen MJ

    2003-10-01

    Full Text Available Abstract Background The alignment of two or more protein sequences provides a powerful guide in the prediction of the protein structure and in identifying key functional residues, however, the utility of any prediction is completely dependent on the accuracy of the alignment. In this paper we describe a suite of reference alignments derived from the comparison of protein three-dimensional structures together with evaluation measures and software that allow automatically generated alignments to be benchmarked. We test the OXBench benchmark suite on alignments generated by the AMPS multiple alignment method, then apply the suite to compare eight different multiple alignment algorithms. The benchmark shows the current state-of-the art for alignment accuracy and provides a baseline against which new alignment algorithms may be judged. Results The simple hierarchical multiple alignment algorithm, AMPS, performed as well as or better than more modern methods such as CLUSTALW once the PAM250 pair-score matrix was replaced by a BLOSUM series matrix. AMPS gave an accuracy in Structurally Conserved Regions (SCRs of 89.9% over a set of 672 alignments. The T-COFFEE method on a data set of families with http://www.compbio.dundee.ac.uk. Conclusions The OXBench suite of reference alignments, evaluation software and results database provide a convenient method to assess progress in sequence alignment techniques. Evaluation measures that were dependent on comparison to a reference alignment were found to give good discrimination between methods. The STAMP Sc Score which is independent of a reference alignment also gave good discrimination. Application of OXBench in this paper shows that with the exception of T-COFFEE, the majority of the improvement in alignment accuracy seen since 1985 stems from improved pair-score matrices rather than algorithmic refinements. The maximum theoretical alignment accuracy obtained by pooling results over all methods was 94

  2. AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

    Science.gov (United States)

    Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

    2012-08-01

    We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The

  3. Complete genome sequence of Klebsiella pneumoniae J1, a protein-based microbial flocculant-producing bacterium.

    Science.gov (United States)

    Pang, Changlong; Li, Ang; Cui, Di; Yang, Jixian; Ma, Fang; Guo, Haijuan

    2016-02-20

    Klebsiella pneumoniae J1 is a Gram-negative strain, which belongs to a protein-based microbial flocculant-producing bacterium. However, little genetic information is known about this species. Here we carried out a whole-genome sequence analysis of this strain and report the complete genome sequence of this organism and its genetic basis for carbohydrate metabolism, capsule biosynthesis and transport system. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

    Directory of Open Access Journals (Sweden)

    Kari A Dilley

    Full Text Available Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV, and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV. Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR activation.

  5. The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

    Science.gov (United States)

    Dilley, Kari A; Voorhies, Alexander A; Luthra, Priya; Puri, Vinita; Stockwell, Timothy B; Lorenzi, Hernan; Basler, Christopher F; Shabman, Reed S

    2017-01-01

    Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation.

  6. Signatures of Mechanosensitive Gating.

    Science.gov (United States)

    Morris, Richard G

    2017-01-10

    The question of how mechanically gated membrane channels open and close is notoriously difficult to address, especially if the protein structure is not available. This perspective highlights the relevance of micropipette-aspirated single-particle tracking-used to obtain a channel's diffusion coefficient, D, as a function of applied membrane tension, σ-as an indirect assay for determining functional behavior in mechanosensitive channels. While ensuring that the protein remains integral to the membrane, such methods can be used to identify not only the gating mechanism of a protein, but also associated physical moduli, such as torsional and dilational rigidity, which correspond to the protein's effective shape change. As an example, three distinct D-versus-σ "signatures" are calculated, corresponding to gating by dilation, gating by tilt, and gating by a combination of both dilation and tilt. Both advantages and disadvantages of the approach are discussed. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  7. Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

    Science.gov (United States)

    Gerlt, John A

    2017-08-22

    The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

  8. SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments

    DEFF Research Database (Denmark)

    Jessen, Leon Ivar; Hoof, Ilka; Lund, Ole

    2013-01-01

    Site does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set......) using a set of human immunodeficiency virus protease-inhibitor genotype–phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found...

  9. Recognition of secretory proteins in Escherichia coli requires signals in addition to the signal sequence and slow folding

    Directory of Open Access Journals (Sweden)

    Flower Ann M

    2002-11-01

    Full Text Available Abstract Background The Sec-dependent protein export apparatus of Escherichia coli is very efficient at correctly identifying proteins to be exported from the cytoplasm. Even bacterial strains that carry prl mutations, which allow export of signal sequence-defective precursors, accurately differentiate between cytoplasmic and mutant secretory proteins. It was proposed previously that the basis for this precise discrimination is the slow folding rate of secretory proteins, resulting in binding by the secretory chaperone, SecB, and subsequent targeting to translocase. Based on this proposal, we hypothesized that a cytoplasmic protein containing a mutation that slows its rate of folding would be recognized by SecB and therefore targeted to the Sec pathway. In a Prl suppressor strain the mutant protein would be exported to the periplasm due to loss of ability to reject non-secretory proteins from the pathway. Results In the current work, we tested this hypothesis using a mutant form of λ repressor that folds slowly. No export of the mutant protein was observed, even in a prl strain. We then examined binding of the mutant λ repressor to SecB. We did not observe interaction by either of two assays, indicating that slow folding is not sufficient for SecB binding and targeting to translocase. Conclusions These results strongly suggest that to be targeted to the export pathway, secretory proteins contain signals in addition to the canonical signal sequence and the rate of folding.

  10. Sequence Identification, Recombinant Production, and Analysis of the Self-Assembly of Egg Stalk Silk Proteins from Lacewing Chrysoperla carnea.

    Science.gov (United States)

    Neuenfeldt, Martin; Scheibel, Thomas

    2017-06-13

    Egg stalk silks of the common green lacewing Chrysoperla carnea likely comprise at least three different silk proteins. Based on the natural spinning process, it was hypothesized that these proteins self-assemble without shear stress, as adult lacewings do not use a spinneret. To examine this, the first sequence identification and determination of the gene expression profile of several silk proteins and various transcript variants thereof was conducted, and then the three major proteins were recombinantly produced in Escherichia coli encoded by their native complementary DNA (cDNA) sequences. Circular dichroism measurements indicated that the silk proteins in aqueous solutions had a mainly intrinsically disordered structure. The largest silk protein, which we named ChryC1, exhibited a lower critical solution temperature (LCST) behavior and self-assembled into fibers or film morphologies, depending on the conditions used. The second silk protein, ChryC2, self-assembled into nanofibrils and subsequently formed hydrogels. Circular dichroism and Fourier transform infrared spectroscopy confirmed conformational changes of both proteins into beta sheet rich structures upon assembly. ChryC3 did not self-assemble into any morphology under the tested conditions. Thereby, through this work, it could be shown that recombinant lacewing silk proteins can be produced and further used for studying the fiber formation of lacewing egg stalks.

  11. Sorting of a HaloTag protein that has only a signal peptide sequence into exocrine secretory granules without protein aggregation.

    Science.gov (United States)

    Fujita-Yoshigaki, Junko; Matsuki-Fukushima, Miwako; Yokoyama, Megumi; Katsumata-Kato, Osamu

    2013-11-15

    The mechanism involved in the sorting and accumulation of secretory cargo proteins, such as amylase, into secretory granules of exocrine cells remains to be solved. To clarify that sorting mechanism, we expressed a reporter protein HaloTag fused with partial sequences of salivary amylase protein in primary cultured parotid acinar cells. We found that a HaloTag protein fused with only the signal peptide sequence (Met(1)-Ala(25)) of amylase, termed SS25H, colocalized well with endogenous amylase, which was confirmed by immunofluorescence microscopy. Percoll-density gradient centrifugation of secretory granule fractions shows that the distributions of amylase and SS25H were similar. These results suggest that SS25H is transported to secretory granules and is not discriminated from endogenous amylase by the machinery that functions to remove proteins other than granule cargo from immature granules. Another reporter protein, DsRed2, that has the same signal peptide sequence also colocalized with amylase, suggesting that the sorting to secretory granules is not dependent on a characteristic of the HaloTag protein. Whereas Blue Native PAGE demonstrates that endogenous amylase forms a high-molecular-weight complex, SS25H does not participate in the complex and does not form self-aggregates. Nevertheless, SS25H was released from cells by the addition of a β-adrenergic agonist, isoproterenol, which also induces amylase secretion. These results indicate that addition of the signal peptide sequence, which is necessary for the translocation in the endoplasmic reticulum, is sufficient for the transportation and storage of cargo proteins in secretory granules of exocrine cells.

  12. Epstein-Barr virus latent gene sequences as geographical markers of viral origin: unique EBNA3 gene signatures identify Japanese viruses as distinct members of the Asian virus family.

    Science.gov (United States)

    Sawada, Akihisa; Croom-Carter, Deborah; Kondo, Osamu; Yasui, Masahiro; Koyama-Sato, Maho; Inoue, Masami; Kawa, Keisei; Rickinson, Alan B; Tierney, Rosemary J

    2011-05-01

    Polymorphisms in Epstein-Barr virus (EBV) latent genes can identify virus strains from different human populations and individual strains within a population. An Asian EBV signature has been defined almost exclusively from Chinese viruses, with little information from other Asian countries. Here we sequenced polymorphic regions of the EBNA1, 2, 3A, 3B, 3C and LMP1 genes of 31 Japanese strains from control donors and EBV-associated T/NK-cell lymphoproliferative disease (T/NK-LPD) patients. Though identical to Chinese strains in their dominant EBNA1 and LMP1 alleles, Japanese viruses were subtly different at other loci. Thus, while Chinese viruses mainly fall into two families with strongly linked 'Wu' or 'Li' alleles at EBNA2 and EBNA3A/B/C, Japanese viruses all have the consensus Wu EBNA2 allele but fall into two families at EBNA3A/B/C. One family has variant Li-like sequences at EBNA3A and 3B and the consensus Li sequence at EBNA3C; the other family has variant Wu-like sequences at EBNA3A, variants of a low frequency Chinese allele 'Sp' at EBNA3B and a consensus Sp sequence at EBNA3C. Thus, EBNA3A/B/C allelotypes clearly distinguish Japanese from Chinese strains. Interestingly, most Japanese viruses also lack those immune-escape mutations in the HLA-A11 epitope-encoding region of EBNA3B that are so characteristic of viruses from the highly A11-positive Chinese population. Control donor-derived and T/NK-LPD-derived strains were similarly distributed across allelotypes and, by using allelic polymorphisms to track virus strains in patients pre- and post-haematopoietic stem-cell transplant, we show that a single strain can induce both T/NK-LPD and B-cell-lymphoproliferative disease in the same patient.

  13. Nucleotide sequence of a cDNA for branched chain acyltransferase with analysis of the deduced protein structure

    International Nuclear Information System (INIS)

    Hummel, K.B.; Litwer, S.; Bradford, A.P.; Aitken, A.; Danner, D.J.; Yeaman, S.J.

    1988-01-01

    Nucleotide