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At least 307 records · Page 17Linked to original sources
PubMed2002

Protein-interaction networks: from experiments to analysis.

Functional proteomics approaches aim to characterize comprehensively the function of gene products, and provide a first-level understanding of cellular mechanisms. Here, we review recent techniques for the construction and prediction of large-scale protein-interaction networks, with a particular emphasis on computational processing steps and comparative assessment of the reliability and completeness of the various approaches. We also discuss the use of protein-interaction network information in functional annotation and in the generation of higher-level biological hypotheses on pathways.

Computational Biology↗
PubMed2005

Probabilistic model of the human protein-protein interaction network.

A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans-a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.

Chromosome Mapping↗
PubMed2001

Markovian domain fingerprinting: statistical segmentation of protein sequences.

MOTIVATION: Characterization of a protein family by its distinct sequence domains is crucial for functional annotation and correct classification of newly discovered proteins. Conventional Multiple Sequence Alignment (MSA) based methods find difficulties when faced with heterogeneous groups of proteins. However, even many families of proteins that do share a common domain contain instances of several other domains, without any common underlying linear ordering. Ignoring this modularity may lead to poor or even false classification results. An automated method that can analyze a group of proteins into the sequence domains it contains is therefore highly desirable. RESULTS: We apply a novel method to the problem of protein domain detection. The method takes as input an unaligned group of protein sequences. It segments them and clusters the segments into groups sharing the same underlying statistics. A Variable Memory Markov (VMM) model is built using a Prediction Suffix Tree (PST) data structure for each group of segments. Refinement is achieved by letting the PSTs compete over the segments, and a deterministic annealing framework infers the number of underlying PST models while avoiding many inferior solutions. We show that regions of similar statistics correlate well with protein sequence domains, by matching a unique signature to each domain. This is done in a fully automated manner, and does not require or attempt an MSA. Several representative cases are analyzed. We identify a protein fusion event, refine an HMM superfamily classification into the underlying families the HMM cannot separate, and detect all 12 instances of a short domain in a group of 396 sequences. CONTACT: jill@cs.huji.ac.il; tishby@cs.huji.ac.il.

Algorithms↗
PubMed2004

Protein interaction mapping on a functional shotgun sequence of Rickettsia sibirica.

Protein interaction maps can reveal novel pathways and functional complexes, allowing 'guilt by association' annotation of uncharacterized proteins. To address the need for large-scale protein interaction analyses, a bacterial two-hybrid system was coupled with a whole genome shotgun sequencing approach for microbial genome analysis. We report the first large-scale proteomics study using this system, integrating de novo genome sequencing with functional interaction mapping and annotation in a high-throughput format. We apply the approach by shotgun sequencing and annotating the genome of Rickettsia sibirica strain 246, an obligate intracellular human pathogen among the Spotted Fever Group rickettsiae. The bacteria invade endothelial cells and cause lysis after large amounts of progeny have accumulated. Little is known about specific Rickettsial virulence factors and their mode of pathogenicity. Analysis of the combined genomic sequence and protein-protein interaction data for a set of virulence related Type IV secretion system (T4SS) proteins revealed over 250 interactions and will provide insight into the mechanism of Rickettsial pathogenicity.

Bacterial Proteins↗
PubMed2001

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

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/.

Binding Sites↗
PubMed2003

Phydbac (phylogenomic display of bacterial genes): An interactive resource for the annotation of bacterial genomes.

Phydbac is a web interactive resource based on phylogenomic profiling, designed to help microbiologists to annotate bacterial proteins. Phylogenomic annotation is based on the assumption that functionally linked protein-coding genes must evolve in a coordinated manner. The detection of subsets of co-evolving genes within a given genome involves the computation of protein sequence conservation profiles across a spectrum of microbial species, followed by the identification of significant pairwise correlations between them. Many ongoing studies are devoted to the problem of computing the most biologically significant phylogenomic profiles and how best identifying clusters of 'functionally interacting' genes. Here we introduce a web tool, Phydbac, allowing the dynamic construction of phylogenomic profiles of protein sequences of interest and their interactive display. In addition, Phydbac can identify Escherichia coli proteins exhibiting the evolution pattern most similar to arbitrary query protein sequences, hence providing functional hints for open reading frames (ORFs) of hypothetical or unknown function. The phylogenomic profiles of all E.coli K-12 protein-coding genes are pre-computed, allowing queries about E.coli genes to be answered instantaneously. The profiles and phylogenomic neighborhoods are computed using an original method shown to perform better than previous ones. An extension of Phydbac, including precomputed profiles for all available bacterial genomes (including major pathogens) will soon be available. Phydbac can be accessed at: http://igs-server.cnrs-mrs.fr/phydbac/.

Bacterial Proteins↗
PubMed2003

Genome-based identification and analysis of collagen-related structural motifs in bacterial and viral proteins.

Collagens are extended trimeric proteins composed of the repetitive sequence glycine-X-Y. A collagen-related structural motif (CSM) containing glycine-X-Y repeats is also found in numerous proteins often referred to as collagen-like proteins. Little is known about CSMs in bacteria and viruses, but the occurrence of such motifs has recently been demonstrated. Moreover, bacterial CSMs form collagen-like trimers, even though these organisms cannot synthesize hydroxyproline, a critical residue for the stability of the collagen triple helix. Here we present 100 novel proteins of bacteria and viruses (including bacteriophages) containing CSMs identified by in silico analyses of genomic sequences. These CSMs differ significantly from human collagens in amino acid content and distribution; bacterial and viral CSMs have a lower proline content and a preference for proline in the X position of GXY triplets. Moreover, the CSMs identified contained more threonine than collagens, and in 17 of 53 bacterial CSMs threonine was the dominating amino acid in the Y position. Molecular modeling suggests that threonines in the Y position make direct hydrogen bonds to neighboring backbone carbonyls and thus substitute for hydroxyproline in the stabilization of the collagen-like triple-helix of bacterial CSMs. The majority of the remaining CSMs were either rich in proline or rich in charged residues. The bacterial proteins containing a CSM that could be functionally annotated were either surface structures or spore components, whereas the viral proteins generally could be annotated as structural components of the viral particle. The limited occurrence of CSMs in eubacteria and lower eukaryotes and the absence of CSMs in archaebacteria suggests that DNA encoding CSMs has been transferred horizontally, possibly from multicellular organisms to bacteria.

Amino Acid Motifs↗
PubMed2006

Gene3D: modelling protein structure, function and evolution.

The Gene3D release 4 database and web portal (http://cathwww.biochem.ucl.ac.uk:8080/Gene3D) provide a combined structural, functional and evolutionary view of the protein world. It is focussed on providing structural annotation for protein sequences without structural representatives--including the complete proteome sets of over 240 different species. The protein sequences have also been clustered into whole-chain families so as to aid functional prediction. The structural annotation is generated using HMM models based on the CATH domain families; CATH is a repository for manually deduced protein domains. Amongst the changes from the last publication are: the addition of over 100 genomes and the UniProt sequence database, domain data from Pfam, metabolic pathway and functional data from COGs, KEGG and GO, and protein-protein interaction data from MINT and BIND. The website has been rebuilt to allow more sophisticated querying and the data returned is presented in a clearer format with greater functionality. Furthermore, all data can be downloaded in a simple XML format, allowing users to carry out complex investigations at their own computers.

Databases, Protein↗
PubMed2002

EXProt: a database for proteins with an experimentally verified function.

EXProt is a non-redundant protein database containing a selection of entries from genome annotation projects and public databases, aimed at including only proteins with an experimentally verified function. In EXProt release 2.0 we have collected entries from the Pseudomonas aeruginosa community annotation project (PseudoCAP), the Escherichia coli genome and proteome database (GenProtEC) and the translated coding sequences from the Prokaryotes division of EMBL nucleotide sequence database, which are described as having an experimentally verified function. Each entry in EXProt has a unique ID number and contains information about the species, amino acid sequence, functional annotation and, in most cases, links to references in MEDLINE/PubMed and to the entry in the original database. EXProt is indexed in SRS at CMBI (http://www.cmbi.kun.nl/srs/) and can be searched with BLAST and FASTA through the EXProt web page (http://www.cmbi.kun.nl/EXProt/).

Animals↗
PubMed2006

Comparative analysis of Saccharomyces cerevisiae WW domains and their interacting proteins.

BACKGROUND: The WW domain is found in a large number of eukaryotic proteins implicated in a variety of cellular processes. WW domains bind proline-rich protein and peptide ligands, but the protein interaction partners of many WW domain-containing proteins in Saccharomyces cerevisiae are largely unknown. RESULTS: We used protein microarray technology to generate a protein interaction map for 12 of the 13 WW domains present in proteins of the yeast S. cerevisiae. We observed 587 interactions between these 12 domains and 207 proteins, most of which have not previously been described. We analyzed the representation of functional annotations within the network, identifying enrichments for proteins with peroxisomal localization, as well as for proteins involved in protein turnover and cofactor biosynthesis. We compared orthologs of the interacting proteins to identify conserved motifs known to mediate WW domain interactions, and found substantial evidence for the structural conservation of such binding motifs throughout the yeast lineages. The comparative approach also revealed that several of the WW domain-containing proteins themselves have evolutionarily conserved WW domain binding sites, suggesting a functional role for inter- or intramolecular association between proteins that harbor WW domains. On the basis of these results, we propose a model for the tuning of interactions between WW domains and their protein interaction partners. CONCLUSION: Protein microarrays provide an appealing alternative to existing techniques for the construction of protein interaction networks. Here we built a network composed of WW domain-protein interactions that illuminates novel features of WW domain-containing proteins and their protein interaction partners.

Amino Acid Motifs↗
PubMed2005

The complete genomes and proteomes of 27 Staphylococcus aureus bacteriophages.

Bacteriophages are the most abundant life forms in the biosphere. They play important roles in bacterial ecology, evolution, adaptation to new environments, and pathogenesis of human bacterial infections. Here, we report the complete genomic sequences, and predicted proteins of 27 bacteriophages of the Gram-positive bacterium Staphylococcus aureus. Comparative nucleotide and protein sequence analysis indicates that these phages are a remarkable source of untapped genetic diversity, encoding 2,170 predicted protein-encoding ORFs, of which 1,402 cannot be annotated for structure or function, and 522 are proteins with no similarity to other phage or bacterial sequences. Based on their genome size, organization of their gene map and comparative nucleotide and protein sequence analysis, the S. aureus phages can be organized into three groups. Comparison of their gene maps reveals extensive genome mosaicism, hinting to a large reservoir of unidentified S. aureus phage genes. Among the phages in the largest size class (178-214 kbp) that we characterized is phage Twort, the first discovered bacteriophage (responsible for the Twort-D'Herelle effect). These phage genomes offer an exciting opportunity to discern molecular mechanisms of phage evolution and diversity.

Chromosome Mapping↗
PubMed2002

EXProt--a database for EXPerimentally verified Protein functions.

EXProt (database for EXPerimentally verified Protein functions) is a new non-redundant database containing protein sequences for which the function has been experimentally verified. It is a selection of 3976 entries from the Prokaryotes section of the EMBL Nucleotide Sequence Database, Release 66, and 375 entries from the Pseudomonas Community Annotation Project (PseudoCAP). The entries in EXProt all have a unique ID number and provide information about the organism, protein sequence, functional annotation, link to entry in original database, and if known, gene name and link to references in PubMed/Medline. The EXProt web page (http://www.cmbi.nl/EXProt) provides further details of the database and a link to a BLAST search (blastp & blastx) of the database. The EXProt entries are indexed in SRS (http://www.cmbi.nl/srs/) and can be searched by means of keywords. Authors can be reached by email (exprot(cmbi.kun.nl).

Amino Acid Sequence↗
PubMed2026

Assessment of the impact of manual curation in BioCyc.

INTRODUCTION: BioCyc is an extensive collection of databases of genomic and pathway information for microorganisms and model eukaryotes. These organismal databases integrate diverse biological data by combining computationally inferred information, data imported from other databases, and, for selected organisms, literature-based manual curation. This study investigates the magnitude and significance of annotation changes performed during the curation of 10 prokaryotic genomes to better understand the rate of erroneous annotations and the value of BioCyc curation. METHODS: We identified curation changes by finding cases where the annotation of the protein at the start of the curation process differed from its annotation at the end of the process. RESULTS: We found that across a sample of curated databases (n = 10), the annotation of 6,753, or 25.6% of the proteins in the pooled protein dataset (n = 26,126) were modified. Assessment of considerable sampling fractions of these proteins found that a median of 62% (mean of 52.9%) represented functionally informative name changes, rather than stylistic annotation changes. These results were then extrapolated to total proteins with name changes with uncertainty quantified via finite population correction, indicating that most Tier 2 Biocyc PGDBs received hundreds of functionally informative name changes during manual curation. On average 363, or13% (±5.4% SD) of the proteins encoded in each genome received functionally informative annotation changes, ranging from 5.3% (Streptococcus pneumoniae D39V) to 22.7% (Staphylococcus aureus NCTC 8325). DISCUSSION: These findings demonstrate a substantial improvement in the accuracy of manually curated BioCyc databases compared with automated annotation pipelines. This result is particularly impactful as the rate of downstream propagation of erroneous annotations across biological databases can significantly compromise scientific discovery.

annotation errors↗
PubMed2000

The SBASE protein domain library, release 7.0: a collection of annotated protein sequence segments.

SBASE 7.0 is the seventh release of the SBASE protein domain library sequences that contains 237 937 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to all major sequence databases and sequence pattern collections. The entries are clustered into over 1811 groups and are provided with two WWW-based search facilities for on-line use. SBASE 7.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb. trieste.it. Automated searching of SBASE with BLAST can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/and http://sbase.abc.hu/sbase/

Amino Acid Sequence↗
PubMed2004

PDBSiteScan: a program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins.

PDBSiteScan is a web-accessible program designed for searching three-dimensional (3D) protein fragments similar in structure to known active, binding and posttranslational modification sites. A collection of known sites we designated as PDBSite was set up by automated processing of the PDB database using the data on site localization in the SITE field. Additionally, protein-protein interaction sites were generated by analysis of atom coordinates in heterocomplexes. The total number of collected sites was more than 8100; they were assigned to more than 80 functional groups. PDBSiteScan provides automated search of the 3D protein fragments whose maximum distance mismatch (MDM) between N, Calpha and C atoms in a fragment and a functional site is not larger than the MDM threshold defined by the user. PDBSiteScan requires perfect matching of amino acids. PDBSiteScan enables recognition of functional sites in tertiary structures of proteins and allows proteins with functional information to be annotated. The program PDBSiteScan is available at http://wwwmgs.bionet.nsc.ru/mgs/systems/fastprot/pdbsitescan.html.

Binding Sites↗
PubMed2003

Identification of Gal80p-interacting proteins by Saccharomyces cerevisiae whole genome phage display.

Networks of interacting proteins and protein interaction maps can help in functional annotation in genome analysis projects. We present the application of genomic phage display as a tool to identify interacting proteins in Saccharomyces cerevisiae. We have developed a large phagemid display library (approximately 7.7x10(7) independent clones) of sheared S. cerevisiae genomic DNA (12.1 Mbp genome size) fused to gene III (lacking the N1 domain) of the filamentous phage M13. Baits tagged with an N-terminal E-tag and a C-terminal His(6)-tag are prepared in a novel Escherichia coli expression system. Using E-Gal80-His(6) as bait, biopanning of the library resulted in the isolation of two different clones containing fragments of the known interacting partner Gal4p. In addition, three new ligands (Ubr1p, YCL045c and Prp8p) with potential physiological relevance were isolated. Interactions were confirmed by ELISA. These results demonstrate the accessibility of the S. cerevisiae genome to display technology for protein-protein interaction screening.

Amino Acid Sequence↗
PubMed2001

A new family of CoA-transferases.

CoA-transferases are found in organisms from all lines of descent. Most of these enzymes belong to two well-known enzyme families, but recent work on unusual biochemical pathways of anaerobic bacteria has revealed the existence of a third family of CoA-transferases. The members of this enzyme family differ in sequence and reaction mechanism from CoA-transferases of the other families. Currently known enzymes of the new family are a formyl-CoA: oxalate CoA-transferase, a succinyl-CoA: (R)-benzylsuccinate CoA-transferase, an (E)-cinnamoyl-CoA: (R)-phenyllactate CoA-transferase, and a butyrobetainyl-CoA: (R)-carnitine CoA-transferase. In addition, a large number of proteins of unknown or differently annotated function from Bacteria, Archaea and Eukarya apparently belong to this enzyme family. Properties and reaction mechanisms of the CoA-transferases of family III are described and compared to those of the previously known CoA-transferases.

Bacteria, Anaerobic↗
PubMed2006

Transcript annotation in FANTOM3: mouse gene catalog based on physical cDNAs.

The international FANTOM consortium aims to produce a comprehensive picture of the mammalian transcriptome, based upon an extensive cDNA collection and functional annotation of full-length enriched cDNAs. The previous dataset, FANTOM2, comprised 60,770 full-length enriched cDNAs. Functional annotation revealed that this cDNA dataset contained only about half of the estimated number of mouse protein-coding genes, indicating that a number of cDNAs still remained to be collected and identified. To pursue the complete gene catalog that covers all predicted mouse genes, cloning and sequencing of full-length enriched cDNAs has been continued since FANTOM2. In FANTOM3, 42,031 newly isolated cDNAs were subjected to functional annotation, and the annotation of 4,347 FANTOM2 cDNAs was updated. To accomplish accurate functional annotation, we improved our automated annotation pipeline by introducing new coding sequence prediction programs and developed a Web-based annotation interface for simplifying the annotation procedures to reduce manual annotation errors. Automated coding sequence and function prediction was followed with manual curation and review by expert curators. A total of 102,801 full-length enriched mouse cDNAs were annotated. Out of 102,801 transcripts, 56,722 were functionally annotated as protein coding (including partial or truncated transcripts), providing to our knowledge the greatest current coverage of the mouse proteome by full-length cDNAs. The total number of distinct non-protein-coding transcripts increased to 34,030. The FANTOM3 annotation system, consisting of automated computational prediction, manual curation, and final expert curation, facilitated the comprehensive characterization of the mouse transcriptome, and could be applied to the transcriptomes of other species.

Animals↗