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Discrimination of the native from misfolded protein models with an energy function including implicit solvation.

An essential requirement for theoretical protein structure prediction is an energy function that can discriminate the native from non-native protein conformations. To date most of the energy functions used for this purpose have been extracted from a statistical analysis of the protein structure database, without explicit reference to the physical interactions responsible for protein stability. The use of the statistical functions has been supported by the widespread belief that they are superior for such discrimination to physics-based energy functions. An effective energy function which combined the CHARMM vacuum potential with a Gaussian model for the solvation free energy is tested for its ability to discriminate the native structure of a protein from misfolded conformations; the results are compared with those obtained with the vacuum CHARMM potential. The test is performed on several sets of misfolded structures prepared by others, including sets of about 650 good decoys for six proteins, as well as on misfolded structures of chymotrypsin inhibitor 2. The vacuum CHARMM potential is successful in most cases when energy minimized conformations are considered, but fails when applied to structures relaxed by molecular dynamics. With the effective energy function the native state is always more stable than grossly misfolded conformations both in energy minimized and molecular dynamics-relaxed structures. The present results suggest that molecular mechanics (physics-based) energy functions, complemented by a simple model for the solvation free energy, should be tested for use in the inverse folding problem, and supports their use in studies of the effective energy surface of proteins in solution. Moreover, the study suggests that the belief in the superiority of statistical functions for these purposes may be ill founded.

Models, Molecular↗

2-DE proteomic profiling of neuronal stem cells.

Proteomics has become a powerful tool in neuroscience studies. Although numerous human neural stem cells are available for research purposes since many years, there exists only limited information on proteomic data from stable neural stem cell lines. Profiling and functional proteome studies of neuronal stem cells will help to describe the protein inventory as well as protein activity and interactions, subcellular localization and posttranslational modifications. The proteomic analysis of neuronal differentiation processes will elucidate the complex events leading to the generation of different phenotypes via distinctive developmental programs that control self-renewal, differentiation, and plasticity. Using the ReNcell VM197 model, a cell line derived from human fetal ventral mesencephalon stem cells, we studied the protein inventory of the stem cells by 2-DE gel electrophoresis and mass spectrometric protein identification and constructed a 2-DE protein map consisting of more than 400 identified protein spots. This proteome reference database constitutes the basis for further investigations of differential protein expression during differentiation. A profiling of the neuronal differentiation-associated changes displayed the large rearrangement of the proteome during this process, and the proteomic techniques proved to be a valuable tool for the elucidation of neuronal differentiation process and for target protein screening.

Animals↗

A two-dimensional map and database of soluble nuclear proteins from HepG2 cells as reference for identification of nutrient-regulated transcription factors.

BACKGROUND: Eukaryotic cells of higher organisms are able to regulate gene transcription in response to changes in the supply of nutrients. In hepatocytes, extracellular glucose levels affect transcription of genes that encode enzymes engaged in glycolysis, gluconeogenesis and lipogenesis. While glucose response elements have been located within a few model gene promoters, the identity of glucose-sensing transcription factors and the mechanisms of their activation remain to be elucidated. AIM OF THE STUDY: We intended to establish a two-dimensional map of nuclear proteins as a reference for identification of nutrient-regulated transcription factors. METHODS: Human hepatoma HepG2 cells were used for the preparation of nuclear extracts. 150-200 microg of the protein mixture were analyzed by 2-dimensional gel electrophoresis (2-DE) and silver-stained protein spots were identified by MALDI-TOF mass spectrometry. RESULTS: Nuclear extracts capable of transcriptional initiation and elongation and containing low amounts of cytoplasmic contaminations were prepared. 543 spots between 17 and 100 kDa and pI 3.7 and 8.8 have been resolved. From these, 65 spots were analyzed by MALDI-TOF mass spectrometry and 53 spots were identified as known proteins of which six represented transcription factors. Regulation by glucose was shown for the activator protein-1 component cJun. Since cJun was not visible on the silver stained 2-DE gel, western blotting of 1-DE gels and immunological detection had to be used in this case. The data were used to construct an online database. CONCLUSIONS: A 2-DE map and database of soluble nuclear proteins is presented. The identification of several transcription factors was possible on the silver-stained gels. However, further fractionation of the nuclear extracts will facilitate the detection of larger numbers of transcriptional regulators. The database and 2-DE map shown here may provide a useful reference for the identification of transcription factors from liver nuclei that are activated by different stimuli, e. g., nutrients.

Carcinoma, Hepatocellular↗

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↗

High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

We have developed a method that predicts both the presence and the type of beta-turns, using a straightforward approach based on propensities and multiple alignments. The propensities were calculated classically, but the way to use them for prediction was completely new: starting from a tetrapeptide sequence on which one wants to evaluate the presence of a beta-turn, the propensity for a given residue is modified by taking into account all the residues present in the multiple alignment at this position. The evaluation of a score is then done by weighting these propensities by the use of Position-specific score matrices generated by PSI-BLAST. The introduction of secondary structure information predicted by PSIPRED or SSPRO2 as well as taking into account the flanking residues around the tetrapeptide improved the accuracy greatly. This latter evaluated on a database of 426 reference proteins (previously used on other studies) by a sevenfold crossvalidation gave very good results with a Matthews Correlation Coefficient (MCC) of 0.42 and an overall prediction accuracy of 74.8%; this places our method among the best ones. A jackknife test was also done, which gave results within the same range. This shows that it is possible to reach neural networks accuracy with considerably less computional cost and complexity. Furthermore, propensities remain excellent descriptors of amino acid tendencies to belong to beta-turns, which can be useful for peptide or protein engineering and design. For beta-turn type prediction, we reached the best accuracy ever published in terms of MCC (except for the irregular type IV) in the range of 0.25-0.30 for types I, II, and I' and 0.13-0.15 for types VIII, II', and IV. To our knowledge, our method is the only one available on the Web that predicts types I' and II'. The accuracy evaluated on two larger databases of 547 and 823 proteins was not improved significantly. All of this was implemented into a Web server called COUDES (French acronym for: Chercher Ou Une Deviation Existe Surement), which is available at the following URL: http://bioserv.rpbs.jussieu.fr/Coudes/index.html within the new bioinformatics platform RPBS.

Amino Acid Sequence↗

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources.

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco-protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O:-linked oligosaccharides from the last 50 years and most N:-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono-isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N:- or O:-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.

Animals↗

Rice proteome database: a step toward functional analysis of the rice genome.

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a beta-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.

Calreticulin↗

Prediction algorithm for amino acid types with their secondary structure in proteins (PLATON) using chemical shifts.

The algorithm PLATON is able to assign sets of chemical shifts derived from a single residue to amino acid types with its secondary structure (amino acid species). A subsequent ranking procedure using optionally two different penalty functions yields predictions for possible amino acid species for the given set of chemical shifts. This was demonstrated in the case of the alpha-spectrin SH3 domain and applied to 9 further protein data sets taken from the BioMagRes database. A database consisting of reference chemical shift patterns (reference CSPs) was generated from assigned chemical shifts of proteins with known 3D-structure. This reference CSP database is used in our approach for extracting distributions of amino acid types with their most likely secondary structure elements (namely alpha-helix, beta-sheet, and coil) for single amino acids by comparison with query CSPs. Results obtained for the 10 investigated proteins indicates that the percentage of correct amino acid species in the first three positions in the ranking list, ranges from 71.4% to 93.2% for the more favorable penalty function. Where only the top result of the ranking list for these 10 proteins is considered, 36.5% to 83.1% of the amino acid species are correctly predicted. The main advantage of our approach, over other methods that rely on average chemical shift values is the ability to increase database content by incorporating newly derived CSPs, and therefore to improve PLATON's performance over time.

Algorithms↗

A protocol for the update of references to scientific literature in biological databases.

Entries in biological databases are usually linked to scientific references. To generate those links and to keep them up-to-date, database maintainers have to continuously scan the scientific literature to select references that are relevant for each single database entry. The continuous growth of both the corpus of scientific literature and the size of biological databases makes this task very hard. We present a protocol intended to assist the updating of an existing set of literature (abstract) links from a single database entry with new references. It consists of taking the set of MEDLINE neighbour references of the existing linked abstracts and evaluating their relevance according to the existing set of abstracts. To test the applicability of the algorithm, we did a simple benchmark of the system using the references associated with the entries of a protein domain database. Human experts found the references that the algorithm scored highly were more relevant to the database entry than those scored lowly, suggesting that the algorithm was useful.

Abstracting and Indexing↗

MitoP2: the mitochondrial proteome database--now including mouse data.

The MitoP2 database (http://www.mitop.de) integrates information on mitochondrial proteins, their molecular functions and associated diseases. The central database features are manually annotated reference proteins localized or functionally associated with mitochondria supplied for yeast, human and mouse. MitoP2 enables (i) the identification of putative orthologous proteins between these species to study evolutionarily conserved functions and pathways; (ii) the integration of data from systematic genome-wide studies such as proteomics and deletion phenotype screening; (iii) the prediction of novel mitochondrial proteins using data integration and the assignment of evidence scores; and (iv) systematic searches that aim to find the genes that underlie common and rare mitochondrial diseases. The data and analysis files are referenced to data sources in PubMed and other online databases and can be easily downloaded. MitoP2 users can explore the relationship between mitochondrial dysfunctions and disease and utilize this information to conduct systems biology approaches on mitochondria.

Animals↗

The Universal Protein Resource (UniProt): an expanding universe of protein information.

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases/.

Databases, Protein↗

The ubiquitin superfamily: members, features, and phylogenies.

The ubiquitin superfamily is a rich repository of small, conserved, functionally unique, and important proteins. Its member proteins fold simply and similarly, with kinetic and thermodynamic ease (Sorenson, J. M.; Head-Gordon, T. Toward minimalist models of larger proteins: A ubiquitin-like protein. Proteins 2002, 46, 368-379). They have been implicated in numerous cancers, neurodegenerations, inflammations, and various disorders affecting signal transduction or protein half-life. These proteins serve the cell generally as portable recognition tags with distinct intracellular roles; indeed, tagging with small protein modifiers has become a new hallmark of post-translational modifications and other signal transduction phenomenon (Finley, D. J. Signal transduction. An alternative to destruction. Nature 2001, 412, 283, 285-286). Because many ubiquitin-like proteins bear similarities in sequence, structure, and function, we gathered protein sequences containing the ubiquitin domain from public databases and created a highly granular and defined protein catabolism database to catalog, summarize, reference, and relate them to their targets and specific ligases (to be described elsewhere). In this paper, we reveal a compilation of proteins possessing the ubiquitin domain. This comprises the first and most important part of our database content. We searched available organismal proteomes for sequence-related members of the ubiquitin superfamily and here present over 200 proteins possessing this domain. These proteins were organized phylogenetically and functionally, thereby defining several new families. To our knowledge, this is the most complete assemblage of ubiquitin domains to date.

Animals↗

Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.

Online Mendelian Inheritance in Man (OMIM) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (http://www.ncbi.nlm.nih.gov/omim/) is now distributed electronically by the National Center for Biotechnology Information, where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, HUGO nomenclature, MapViewer, GeneTests, patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.

Chromosome Mapping↗

Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.

Online Mendelian Inheritance in Man (OMIM) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support research and education in human genomics and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (www.ncbi.nlm.nih.gov/omim) is now distributed electronically by the National Center for Biotechnology Information (NCBI), where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, approved gene nomenclature, and the highly detailed mapviewer, as well as patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.

Chromosome Mapping↗

Online Mendelian Inheritance in Man (OMIM).

Online Mendelian Inheritance In Man (OMIM) is a public database of bibliographic information about human genes and genetic disorders. Begun by Dr. Victor McKusick as the authoritative reference Mendelian Inheritance in Man, it is now distributed electronically by the National Center for Biotechnology Information (NCBI). Material in OMIM is derived from the biomedical literature and is written by Dr. McKusick and his colleagues at Johns Hopkins University and elsewhere. Each OMIM entry has a full text summary of a genetic phenotype and/or gene and has copious links to other genetic resources such as DNA and protein sequence, PubMed references, mutation databases, approved gene nomenclature, and more. In addition, NCBI's neighboring feature allows users to identify related articles from PubMed selected on the basis of key words in the OMIM entry. Through its many features, OMIM is increasingly becoming a major gateway for clinicians, students, and basic researchers to the ever-growing literature and resources of human genetics.

Alleles↗

Expression and functional proteomics studies in colorectal cancer.

Cell dysfunction results from multiple rather than from single gene interactions in the majority of colorectal cancers (CRC). Proteins, not mRNA, are the functional molecules in the cell, and the relationship between gene expression measured at the mRNA level and the corresponding protein level is not linear. Current proteomics tools allow for the determination of post-translational modifications, and hence the presence of protein isoforms--some of them being disease-relevant. Thus, proteomics approaches are a welcome complement to traditional genetic approaches. In CRC, expression proteomics studies were carried out with colorectal cell lines, whole tissue biopsies, and purified epithelial cells. For CRC, two-dimensional electrophoresis reference maps, protein, and membrane protein databases are available on the internet. Functional proteomics studies have been performed to better understand signaling pathways, to characterize the molecular targets of novel drugs, and to identify tumor-associated antigens in CRC. The increasing use of proteomics technologies, when addressing clinical problems, will accelerate the evolution towards personalized medicine in CRC.

Adenocarcinoma↗

A novel p34(cdc2)-binding and activating protein that is necessary and sufficient to trigger G(2)/M progression in Xenopus oocytes.

The activation of maturation-promoting factor (MPF) is required for G(2)/M progression in eukaryotic cells. Xenopus oocytes are arrested in G(2) and are induced to enter M phase of meiosis by progesterone stimulation. This process is known as meiotic maturation and requires the translation of specific maternal mRNAs stored in the oocytes. We have used an expression cloning strategy to functionally identify proteins involved in G(2)/M progression in Xenopus oocytes. Here we report the cloning of two novel cDNAs that when expressed in oocytes induce meiotic maturation efficiently. The two cDNAs encode proteins of 33 kD that are 88% identical and have no significant homologies to other sequences in databases. These proteins, which we refer to as p33(ringo) (rapid inducer of G(2)/M progression in oocytes), induce very rapid MPF activation in cycloheximide-treated oocytes. Conversely, ablation of endogenous p33(ringo) mRNAs using antisense oligonucleotides inhibits progesterone-induced maturation, suggesting that synthesis of p33(ringo) is required for this process. We also show that p33(ringo) binds to and activates the kinase activity of p34(cdc2) but does not associate with p34(cdc2)/cyclin B complexes. Our results identify a novel p34(cdc2) binding and activating protein that regulates the G(2)/M transition during oocyte maturation.

Amino Acid Sequence↗

The Universal Protein Resource (UniProt).

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two weeks.

Amino Acid Sequence↗