Biomedical subjects

S Brunak

Publications and source records attributed to S Brunak.

At least 37 records · Page 2Linked to original sources

PubMed2000

env sequences of simian immunodeficiency viruses from chimpanzees in Cameroon are strongly related to those of human immunodeficiency virus group N from the same geographic area.

Human immunodeficiency virus type 1 (HIV-1) group N from Cameroon is phylogenetically close, in env, to the simian immunodeficiency virus (SIV) cpz-gab from Gabon and SIVcpz-US of unknown geographic origin. We screened 29 wild-born Cameroonian chimpanzees and found that three (Cam3, Cam4, and Cam5) were positive for HIV-1 by Western blotting. Mitochondrial DNA sequence analysis demonstrated that Cam3 and Cam5 belonged to Pan troglodytes troglodytes and that Cam4 belonged to P. t. vellerosus. Genetic analyses of the viruses together with serological data demonstrated that at least one of the two P. t. troglodytes chimpanzees (Cam5) was infected in the wild, and revealed a horizontal transmission between Cam3 and Cam4. These data confirm that P. t. troglodytes is a natural host for HIV-1-related viruses. Furthermore, they show that SIVcpz can be transmitted in captivity, from one chimpanzee subspecies to another. All three SIVcpz-cam viruses clustered with HIV-1 N in env. The full Cam3 SIVcpz genome sequence showed a very close phylogenetic relationship with SIVcpz-US, a virus identified in a P. t. troglodytes chimpanzee captured nearly 40 years earlier. Like SIVcpz-US, SIVcpz-cam3 was closely related to HIV-1 N in env, but not in pol, supporting the hypothesis that HIV-1 N results from a recombination event. SIVcpz from chimpanzees born in the wild in Cameroon are thus strongly related in env to HIV-1 N from Cameroon, demonstrating the geographic coincidence of these human and simian viruses and providing a further strong argument in favor of the origin of HIV-1 being in chimpanzees.

Animals↗

PubMed2000

Matching protein beta-sheet partners by feedforward and recurrent neural networks.

Predicting the secondary structure (alpha-helices, beta-sheets, coils) of proteins is an important step towards understanding their three dimensional conformations. Unlike alpha-helices that are built up from one contiguous region of the polypeptide chain, beta-sheets are more complex resulting from a combination of two or more disjoint regions. The exact nature of these long distance interactions remains unclear. Here we introduce two neural-network based methods for the prediction of amino acid partners in parallel as well as anti-parallel beta-sheets. The neural architectures predict whether two residues located at the center of two distant windows are paired or not in a beta-sheet structure. Variations on these architecture, including also profiles and ensembles, are trained and tested via five-fold cross validation using a large corpus of curated data. Prediction on both coupled and non-coupled residues currently approaches 84% accuracy, better than any previously reported method.

Animals↗

PubMed2000

Identifying cytotoxic T cell epitopes from genomic and proteomic information: "The human MHC project.".

Complete genomes of many species including pathogenic microorganisms are rapidly becoming available and with them the encoded proteins, or proteomes. Proteomes are extremely diverse and constitute unique imprints of the originating organisms allowing positive identification and accurate discrimination, even at the peptide level. It is not surprising that peptides are key targets of the immune system. It follows that proteomes can be translated into immunogens once it is known how the immune system generates and handles peptides. Recent advances have identified many of the basic principles involved. The single most selective event is that of peptide binding to MHC, making it particularly important to establish accurate descriptions and predictions of peptide binding for the most common MHC variants. These predictions should be integrated with those of other steps involved in antigen processing, as these become available. The ability to translate the accumulating primary sequence databases in terms of immune recognition should enable scientists and clinicians to analyze any protein of interest for the presence of potentially immunogenic epitopes. The computational tools to scan entire proteomes should also be developed, as this would enable a rational approach to vaccine development and immunotherapy. Thus, candidate vaccine epitopes might be predicted from the various microbial genome projects, tumor vaccine candidates from mRNA expression profiling of tumors ("transcriptomes") and auto-antigens from the human genome.

Antigen Presentation↗

PubMed1999

Sequence and structure-based prediction of eukaryotic protein phosphorylation sites.

Protein phosphorylation at serine, threonine or tyrosine residues affects a multitude of cellular signaling processes. How is specificity in substrate recognition and phosphorylation by protein kinases achieved? Here, we present an artificial neural network method that predicts phosphorylation sites in independent sequences with a sensitivity in the range from 69 % to 96 %. As an example, we predict novel phosphorylation sites in the p300/CBP protein that may regulate interaction with transcription factors and histone acetyltransferase activity. In addition, serine and threonine residues in p300/CBP that can be modified by O-linked glycosylation with N-acetylglucosamine are identified. Glycosylation may prevent phosphorylation at these sites, a mechanism named yin-yang regulation. The prediction server is available on the Internet at http://www.cbs.dtu.dk/services/NetPhos/or via e-mail to NetPhos@cbs. dtu.dk.

Amino Acid Motifs↗

PubMed1999

The biology of eukaryotic promoter prediction--a review.

Computational prediction of eukaryotic promoters from the nucleotide sequence is one of the most attractive problems in sequence analysis today, but it is also a very difficult one. Thus, current methods predict in the order of one promoter per kilobase in human DNA, while the average distance between functional promoters has been estimated to be in the range of 30-40 kilobases. Although it is conceivable that some of these predicted promoters correspond to cryptic initiation sites that are used in vivo, it is likely that most are false positives. This suggests that it is important to carefully reconsider the biological data that forms the basis of current algorithms, and we here present a review of data that may be useful in this regard. The review covers the following topics: (1) basal transcription and core promoters, (2) activated transcription and transcription factor binding sites, (3) CpG islands and DNA methylation, (4) chromosomal structure and nucleosome modification, and (5) chromosomal domains and domain boundaries. We discuss the possible lessons that may be learned, especially with respect to the wealth of information about epigenetic regulation of transcription that has been appearing in recent years.

Chromosomes↗

PubMed1999

PhosphoBase, a database of phosphorylation sites: release 2.0.

PhosphoBase contains information about phosphorylated residues in proteins and data about peptide phosphorylation by a variety of protein kinases. The data are collected from literature and compiled into a common format. The current release of PhosphoBase (October 1998, version 2.0) comprises 414 phosphoprotein entries covering 1052 phosphorylatable serine, threonine and tyrosine residues. The kinetic data from peptide phosphorylation assays for approximately 330 oligopeptides is also included. The database entries are cross-referenced to the corresponding records in the Swiss-Prot protein database and literature references are linked to MedLine records. PhosphoBase is available via the WWW at http://www.cbs.dtu. dk/databases/PhosphoBase/

Animals↗

PubMed1999

O-GLYCBASE version 4.0: a revised database of O-glycosylated proteins.

O-GLYCBASE is a database of glycoproteins with O-linked glycosylation sites. Entries with at least one experimentally verified O-glycosylation site have been compiled from protein sequence databases and literature. Each entry contains information about the glycan involved, the species, sequence, a literature reference and http-linked cross-references to other databases. Version 4.0 contains 179 protein entries, an approximate 15% increase over the last version. Sequence logos representing the acceptor specificity patterns for GalNAc, GlcNAc, mannosyl and xylosyl transferases are shown. The O-GLYCBASE database is available through the WWW at http://www.cbs.dtu.dk/databases/OGLYCBASE/

Acetylgalactosamine↗

PubMed1999

Structural basis for triplet repeat disorders: a computational analysis.

MOTIVATION: Over a dozen major degenerative disorders, including myotonic distrophy, Huntington's disease and fragile X syndrome, result from unstable expansions of particular trinucleotides. Remarkably, only some of all the possible triplets, namely CAG/CTG, CGG/CCG and GAA/TTC, have been associated with the known pathological expansions. This raises some basic questions at the DNA level. Why do particular triplets seem to be singled out? What is the mechanism for their expansion and how does it depend on the triplet itself? Could other triplets or longer repeats be involved in other diseases? RESULTS: Using several different computational models of DNA structure, we show that the triplets involved in the pathological repeats generally fall into extreme classes. Thus, CAG/CTG repeats are particularly flexible, whereas GCC, CGG and GAA repeats appear to display both flexible and rigid (but curved) characteristics depending on the method of analysis. The fact that (1) trinucleotide repeats often become increasingly unstable when they exceed a length of approximately 50 repeats, and (2) repeated 12-mers display a similar increase in instability above 13 repeats, together suggest that approximately 150 bp is a general threshold length for repeat instability. Since this is about the length of DNA wrapped up in a single nucleosome core particle, we speculate that chromatin structure may play an important role in the expansion mechanism. We furthermore suggest that expansion of a dodecamer repeat, which we predict to have very high flexibility, may play a role in the pathogenesis of the neurodegenerative disorder multiple system atrophy (MSA). CONTACT: pfbaldi@ics.uci.edu, yves@netid.com, brunak@cbs.dtu.dk, gorm@cbs.dtu.dk.

Anticipation, Genetic↗

PubMed1999

Exploiting the past and the future in protein secondary structure prediction.

MOTIVATION: Predicting the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three-dimensional structure, as well as its function. Presently, the best predictors are based on machine learning approaches, in particular neural network architectures with a fixed, and relatively short, input window of amino acids, centered at the prediction site. Although a fixed small window avoids overfitting problems, it does not permit capturing variable long-rang information. RESULTS: We introduce a family of novel architectures which can learn to make predictions based on variable ranges of dependencies. These architectures extend recurrent neural networks, introducing non-causal bidirectional dynamics to capture both upstream and downstream information. The prediction algorithm is completed by the use of mixtures of estimators that leverage evolutionary information, expressed in terms of multiple alignments, both at the input and output levels. While our system currently achieves an overall performance close to 76% correct prediction--at least comparable to the best existing systems--the main emphasis here is on the development of new algorithmic ideas. AVAILABILITY: The executable program for predicting protein secondary structure is available from the authors free of charge. CONTACT: pfbaldi@ics.uci.edu, gpollast@ics.uci.edu, brunak@cbs.dtu.dk, paolo@dsi.unifi.it.

Algorithms↗

PubMed1999

MatrixPlot: visualizing sequence constraints.

UNLABELLED: MatrixPlot is a program for making high-quality matrix plots, such as mutual information plots of sequence alignments and distance matrices of sequences with known three-dimensional coordinates. The user can add information about the sequences (e.g. a sequence logo profile) along the edges of the plot, as well as zoom in on any region in the plot. AVAILABILITY: MatrixPlot can be obtained on request, and can also be accessed online at http://www. cbs.dtu.dk/services/MatrixPlot. CONTACT: gorodkin@cbs.dtu.dk

Nucleic Acids↗

PubMed1999

Scanning the available Dictyostelium discoideum proteome for O-linked GlcNAc glycosylation sites using neural networks.

Dictyostelium discoideum has been suggested as a eukaryotic model organism for glycobiology studies. Presently, the characteristics of acceptor sites for the N-acetylglucosaminyl-transferases in Dictyostelium discoideum, which link GlcNAc in an alpha linkage to hydroxyl residues, are largely unknown. This motivates the development of a species specific method for prediction of O-linked GlcNAc glycosylation sites in secreted and membrane proteins of D. discoideum. The method presented here employs a jury of artificial neural networks. These networks were trained to recognize the sequence context and protein surface accessibility in 39 experimentally determined O-alpha-GlcNAc sites found in D. discoideum glycoproteins expressed in vivo. Cross-validation of the data revealed a correlation in which 97% of the glycosylated and nonglycosylated sites were correctly identified. Based on the currently limited data set, an abundant periodicity of two (positions-3, -1, +1, +3, etc.) in Proline residues alternating with hydroxyl amino acids was observed upstream and downstream of the acceptor site. This was a consequence of the spacing of the glycosylated residues themselves which were peculiarly found to be situated only at even positions with respect to each other, indicating that these may be located within beta-strands. The method has been used for a rapid and ranked scan of the fraction of the Dictyostelium proteome available in public databases, remarkably 25-30% of which were predicted glycosylated. The scan revealed acceptor sites in several proteins known experimentally to be O-glycosylated at unmapped sites. The available proteome was classified into functional and cellular compartments to study any preferential patterns of glycosylation. A sequence based prediction server for GlcNAc O-glycosylations in D. discoideum proteins has been made available through the WWW at http://www.cbs.dtu.dk/services/DictyOGlyc/ and via E-mail to DictyOGlyc@cbs.dtu.dk.

Algorithms↗

PubMed1999

Machine learning approaches for the prediction of signal peptides and other protein sorting signals.

Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently, the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, have made it possible to achieve a level of reliability where practical use in, for example automatic database annotation is feasible. In this review, we concentrate on the present status and future perspectives of SignalP, our neural network-based method for prediction of the most well-known sorting signal: the secretory signal peptide. We discuss the problems associated with the use of SignalP on genomic sequences, showing that signal peptide prediction will improve further if integrated with predictions of start codons and transmembrane helices. As a step towards this goal, a hidden Markov model version of SignalP has been developed, making it possible to discriminate between cleaved signal peptides and uncleaved signal anchors. Furthermore, we show how SignalP can be used to characterize putative signal peptides from an archaeon, Methanococcus jannaschii. Finally, we briefly review a few methods for predicting other protein sorting signals and discuss the future of protein sorting prediction in general.

Algorithms↗

PubMed1999

Using sequence motifs for enhanced neural network prediction of protein distance constraints.

Correlations between sequence separation (in residues) and distance (in Angstrom) of any pair of amino acids in polypeptide chains are investigated. For each sequence separation we define a distance threshold. For pairs of amino acids where the distance between C alpha atoms is smaller than the threshold, a characteristic sequence (logo) motif, is found. The motifs change as the sequence separation increases: for small separations they consist of one peak located in between the two residues, then additional peaks at these residues appear, and finally the center peak smears out for very large separations. We also find correlations between the residues in the center of the motif. This and other statistical analysis are used to design neural networks with enhanced performance compared to earlier work. Importantly, the statistical analysis explains why neural networks perform better than simple statistical data-driven approaches such as pair probability density functions. The statistical results also explain characteristics of the network performance for increasing sequence separation. The improvement of the new network design is significant in the sequence separation range 10-30 residues. Finally, we find that the performance curve for increasing sequence separation is directly correlated to the corresponding information content. A WWW server, distanceP, is available at http://www.cbs.dtu.dk/services/distanceP/.

Algorithms↗

PubMed1998

DNA structure in human RNA polymerase II promoters.

The fact that DNA three-dimensional structure is important for transcriptional regulation begs the question of whether eukaryotic promoters contain general structural features independently of what genes they control. We present an analysis of a large set of human RNA polymerase II promoters with a very low level of sequence similarity. The sequences, which include both TATA-containing and TATA-less promoters, are aligned by hidden Markov models. Using three different models of sequence-derived DNA bendability, the aligned promoters display a common structural profile with bendability being low in a region upstream of the transcriptional start point and significantly higher downstream. Investigation of the sequence composition in the two regions shows that the bendability profile originates from the sequential structure of the DNA, rather than the general nucleotide composition. Several trinucleotides known to have high propensity for major groove compression are found much more frequently in the regions downstream of the transcriptional start point, while the upstream regions contain more low-bendability triplets. Within the region downstream of the start point, we observe a periodic pattern in sequence and bendability, which is in phase with the DNA helical pitch. The periodic bendability profile shows bending peaks roughly at every 10 bp with stronger bending at 20 bp intervals. These observations suggest that DNA in the region downstream of the transcriptional start point is able to wrap around protein in a manner reminiscent of DNA in a nucleosome. This notion is further supported by the finding that the periodic bendability is caused mainly by the complementary triplet pairs CAG/CTG and GGC/GCC, which previously have been found to correlate with nucleosome positioning. We present models where the high-bendability regions position nucleosomes at the downstream end of the transcriptional start point, and consider the possibility of interaction between histone-like TAFs and this area. We also propose the use of this structural signature in computational promoter-finding algorithms.

Algorithms↗

PubMed1998

Computational analyses and annotations of the Arabidopsis peroxidase gene family.

Classical heme-containing plant peroxidases have been ascribed a wide variety of functional roles related to development, defense, lignification, and hormonal signaling. More than 40 peroxidase genes are now known in Arabidopsis thaliana for which functional association is complicated by a general lack of peroxidase substrate specificity. Computational analysis was performed on 30 near full-length Arabidopsis peroxidase cDNAs for annotation of start codons and signal peptide cleavage sites. A compositional analysis revealed that 23 of the 30 peroxidase cDNAs have 5' untranslated regions containing 40-71% adenine, a rare feature observed also in cDNAs which predominantly encode stress-induced proteins, and which may indicate translational regulation.

Adenine↗

PubMed1998

Statistical analysis of protein kinase specificity determinants.

The site and sequence specificity of protein kinases, as well as the role of the secondary structure and surface accessibility of the phosphorylation sites on substrate proteins, was statistically analyzed. The experimental data were collected from the literature and are available on the World Wide Web at http://www.cbs.dtu.dk/databases/PhosphoBase/. The set of data involved 1008 phosphorylatable sites in 406 proteins, which were phosphorylated by 58 protein kinases. It was found that there exists almost absolute Ser/Thr or Tyr specificity, with rare exceptions. The sequence specificity determinants were less strict and were located between positions -4 and +4 relative to the phosphorylation site. Secondary structure and surface accessibility predictions revealed that most of the phosphorylation sites were located on the surface of the target proteins.

Amino Acids↗

PubMed1998

PhosphoBase: a database of phosphorylation sites.

PhosphoBase is a database of experimentally verified phosphorylation sites. Version 1.0 contains 156 entries and 398 experimentally determined phosphorylation sites. Entries are compiled and revised from the literature and from major protein sequence databases such as SwissProt and PIR. The entries provide information about the phosphoprotein and the exact position of its phosphorylation sites. Furthermore, part of the entries contain information about kinetic data obtained from enzyme assays on specific peptides. To illustrate the use of data extracted from PhosphoBase we present a sequence logo displaying the overall conservation of positions around serines phosphorylated by protein kinase A (PKA). PhosphoBase is available on the WWW at http://www.cbs.dtu.dk/databases/PhosphoBase/

Amino Acid Sequence↗

PubMed1998

O-GLYCBASE Version 3.0: a revised database of O-glycosylated proteins.

O-GLYCBASE is a revised database of information on glycoproteins and their O-linked glycosylation sites. Entries are compiled and revised from the literature, and from the sequence databases. Entries include information about species, sequence, glycosylation sites and glycan type and is fully cross-referenced. Compared to version 2.0 the number of entries has increased by 20%. Sequence logos displaying the acceptor specificity patterns for the GalNAc, mannose and GlcNAc transferases are shown. The O-GLYCBASE database is available through the WWW at http://www.cbs.dtu. dk/databases/OGLYCBASE/

Amino Acid Sequence↗