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PubMed2006

Human protein reference database--2006 update.

Human Protein Reference Database (HPRD) (http://www.hprd.org) was developed to serve as a comprehensive collection of protein features, post-translational modifications (PTMs) and protein-protein interactions. Since the original report, this database has increased to >20 000 proteins entries and has become the largest database for literature-derived protein-protein interactions (>30 000) and PTMs (>8000) for human proteins. We have also introduced several new features in HPRD including: (i) protein isoforms, (ii) enhanced search options, (iii) linking of pathway annotations and (iv) integration of a novel browser, GenProt Viewer (http://www.genprot.org), developed by us that allows integration of genomic and proteomic information. With the continued support and active participation by the biomedical community, we expect HPRD to become a unique source of curated information for the human proteome and spur biomedical discoveries based on integration of genomic, transcriptomic and proteomic data.

Databases, Protein↗

PubMed2003

Development of human protein reference database as an initial platform for approaching systems biology in humans.

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.

BRCA1 Protein↗

PubMed2005

Bioinformatics analyses of circular dichroism protein reference databases.

MOTIVATION: Circular dichroism (CD) spectroscopy has become established as a key method for determining the secondary structure contents of proteins which has had a significant impact on molecular biology. Many excellent mathematical protocols have been developed for this purpose and their quality is above question. However, reference database sets of proteins, with CD spectra matched to secondary structure components derived from X-ray structures, provide the key resource for this task. These databases were created many years ago, before most CD spectrophotometers became standardized and before it was commonplace to validate X-ray structures prior to publication. The analyses presented here were undertaken to investigate the overall quality of these reference databases in light of their extensive usage in determining protein secondary structure content from CD spectra. RESULTS: The analyses show that there are a number of significant problems associated with the CD reference database sets in current use. There are disparities between CD spectra for the same protein collected by different groups. These include differences in magnitudes, peak positions or both. However, many current reference sets are now amalgamations of spectra from these groups, introducing inconsistencies that can lead to inaccuracies in the determination of secondary structure components from the CD spectra. A number of the X-ray structures used fall short on the validation criteria now employed as standard for structure determination. Many have substantial percentages of residues in the disallowed regions of the Ramachandran plot. Hence their calculated secondary structure components, used as a foundation for the reference databases, are likely to be in error. Additionally, the coverage of secondary structure space in the reference datasets is poorly correlated to the secondary structure components found in the Protein Data Bank. A conclusion is that a new reference CD database with cross-correlated, machine-independent CD spectra and validated X-ray structures that cover more secondary structure components, including diverse protein folds, is now needed. However, that reasonably accurate values for the secondary structure content of proteins can be determined from spectra is a testament to CD spectroscopy being a very powerful technique.

Circular Dichroism↗

PubMed2026

ProteoParc: A Reference Protein Database Builder for Ancient and Nonmodel Organisms.

Over the past few years, the increasing interest in analyzing the proteome of extinct and nonmodel organisms has generated a new field of research expanding the scope of proteomics. The lack of curated databases and/or molecular data from these organisms forces researchers to manually search in different public repositories for related protein sequences, either for MS/MS peptide identification or ZooMS marker annotation. This can lead to format incongruences and hinder reproducibility between studies. To address this issue, we introduce ProteoParc, a user-friendly software that builds reference databases by systematically downloading and processing protein sequences from the most widely used public repositories. The pipeline's output is a nonredundant protein database, formatted in a way to be interpreted by typical peptide identification software. Moreover, the user can adjust the database dimension and composition by applying different criteria to include only a certain number of genes or species. Thus, ProteoParc is an easy and fast, custom-made bioinformatic tool useful for future paleoproteomics analysis in ancient samples related to understudied organisms.

Databases, Protein↗

PubMed2004

Human protein reference database as a discovery resource for proteomics.

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.

Computational Biology↗

PubMed2006

Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes.

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray co-expressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown.

Computational Biology↗

PubMed2002

The Protein Information Resource: an integrated public resource of functional annotation of proteins.

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).

Amino Acid Sequence↗

PubMed2005

Prediction of protein-protein interactions using distant conservation of sequence patterns and structure relationships.

MOTIVATION: Given that association and dissociation of protein molecules is crucial in most biological processes several in silico methods have been recently developed to predict protein-protein interactions. Structural evidence has shown that usually interacting pairs of close homologs (interologs) physically interact in the same way. Moreover, conservation of an interaction depends on the conservation of the interface between interacting partners. In this article we make use of both, structural similarities among domains of known interacting proteins found in the Database of Interacting Proteins (DIP) and conservation of pairs of sequence patches involved in protein-protein interfaces to predict putative protein interaction pairs. RESULTS: We have obtained a large amount of putative protein-protein interaction (approximately 130,000). The list is independent from other techniques both experimental and theoretical. We separated the list of predictions into three sets according to their relationship with known interacting proteins found in DIP. For each set, only a small fraction of the predicted protein pairs could be independently validated by cross checking with the Human Protein Reference Database (HPRD). The fraction of validated protein pairs was always larger than that expected by using random protein pairs. Furthermore, a correlation map of interacting protein pairs was calculated with respect to molecular function, as defined in the Gene Ontology database. It shows good consistency of the predicted interactions with data in the HPRD database. The intersection between the lists of interactions of other methods and ours produces a network of potentially high-confidence interactions.

Algorithms↗

PubMed2005

Atlas - a data warehouse for integrative bioinformatics.

BACKGROUND: We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. DESCRIPTION: The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. CONCLUSION: The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: http://bioinformatics.ubc.ca/atlas/

Computational Biology↗

PubMed2005

CysMap and CysJoin: database and tools for protein disulphides localisation.

We have developed a computer program able to make user-customised databases derived from the public PIR non-redundant reference protein database. When the database of interest has been created, the user will generate the map of all the possible linear peptides containing one and two cysteines for each protein and combine them to calculate the mass of all the possible clusters of linear peptides linked by a disulphide bridge with a cysteine pair. It is also possible to create selected maps corresponding to peptides formed by the action of specific proteases. In this way, mass spectrometric data obtained from the hydrolysis of proteins of unknown sequence can be related to that contained in the database for quick disulphide assignment and protein identification. To confirm signal attribution, the program will also furnish the expected mass of cluster peptides after performing a cycle of Edman degradation. The utility of the program is discussed and examples of application are given.

Amino Acid Sequence↗

PubMed2004

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Database Management Systems↗

PubMed2026

MegaPX: fast and space-efficient peptide assignment method using IBF-based multi-indexing.

MOTIVATION: A central problem for metaproteomic analysis is the often-unknown taxonomic composition of the analyzed microbiomes. Using a database search, the standard approach requires prior knowledge of which proteins and taxa to include in the protein reference database or to use tailored metagenome-derived databases, which are expensive and error-prone in their generation. A possible strategy to circumvent this database search issue is de novo sequencing, where peptide sequences are directly identified from mass spectra. However, these sequences must still be mapped back to potentially extensive databases. Here, alignment-based approaches enable robust and precise results, with the potential drawback of high memory usage and long run times. RESULTS: We present MegaPX, a software for rapidly classifying de novo peptide sequences against large protein databases. MegaPX implemented as a C++-based tool, uses an alignment-free, k-mer approach as a taxonomic classification method with the possibility of generating mutated reference databases for error-tolerant searching. It uses various algorithms, including interleaved Bloom filters, to efficiently compute approximate membership queries, ensuring fast processing times while querying and indexing large databases in a multi-indexing fashion. We demonstrate the potential of MegaPX by analyzing different samples, including metaproteomics, against extensive reference databases, highlighting its use as a fast screening tool.

Software↗

PubMed2005

Spectral magnitude effects on the analyses of secondary structure from circular dichroism spectroscopic data.

The effects of spectral magnitude on the calculated secondary structures derived from circular dichroism (CD) spectra were examined for a number of the most commonly used algorithms and reference databases. Proteins with different secondary structures, ranging from mostly helical to mostly beta-sheet, but which were not components of existing reference databases, were used as test systems. These proteins had known crystal structures, so it was possible to ascertain the effects of magnitude on both the accuracy of determining the secondary structure and the goodness-of-fit of the calculated structures to the experimental data. It was found that most algorithms are highly sensitive to spectral magnitude, and that the goodness-of-fit parameter may be a useful tool in assessing the correct scaling of the data. This means that parameters that affect magnitude, including calibration of the instrument, the spectral cell pathlength, and the protein concentration, must be accurately determined to obtain correct secondary structural analyses of proteins from CD data using empirical methods.

Albumins↗

PubMed1992

Human liver protein map: a reference database established by microsequencing and gel comparison.

This publication establishes a reference human liver protein map obtained with immobilized pH gradients. By microsequencing, 57 spots or 42 polypeptide chains were identified. By protein map comparison and matching (liver, red blood cell and plasma sample maps), 8 additional proteins were identified. The new polypeptides and previously known proteins are listed in a table and/or labeled on the protein map, thus providing a human liver two-dimensional gel database. This reference map can be used to identify protein spots on other samples such as rectal cancer biopsies.

Amino Acid Sequence↗

PubMed2005

Analysis of phosphatase and tensin homolog tumor suppressor interacting proteins by in vitro and in silico proteomics.

The phosphatase and tensin homolog (PTEN) tumor suppressor is a multifunctional protein deregulated in many types of cancer. To date, a comprehensive documentation of PTEN interacting proteins has not been performed. The goal of our study was to characterize the PTEN interactome using affinity pull-down and tandem mass spectrometry (MS/MS). Wild-type PTEN cDNA was inserted into pTRC-His2 vector to create a 6-His tagged protein, which was expressed in Escherichia coli. Lysate from a human lymphoma cell line was used in pull-down assays, utilizing affinity for nickel-agarose beads. Bound proteins were eluted with imidazole, digested and analyzed on an LCQ DecaXP ion trap mass spectrometer. The nickel affinity pull-down efficiency was evaluated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western blot analysis. Acquired data were searched against the NCBI nr.fasta nonredundant protein database using the SEQUEST algorithm and screened using INTERACT and ProteinProphet. All experiments were performed in duplicate with 6-His-lacZ serving as control. A total of 79 proteins were identified in the wild-type 6-His-PTEN pull-down by MS/MS. We further validated a subset of the proteins present in the PTEN interactome by performing immunoprecipitation using an anti-PTEN antibody and establishing the presence of the proteins in the immunocomplex by Western blot analysis. A search of published PTEN interactions was also performed using Online Mendelian Inheritance in Man, Human Protein Reference Database, the IntAct Project database, and PubMed. This in silico analysis confirmed 42 out of 79 (53%) of the proteins identified by MS/MS. The remaining 37 proteins represent probable PTEN interactions not previously documented in public databases or reported in the literature. These results highlight the value of combining both in vitro biochemical approaches with in silico analyses for a comprehensive study of protein-protein interactions.

Algorithms↗

PubMed2004

BioBuilder as a database development and functional annotation platform for proteins.

BACKGROUND: The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. RESULTS: BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database http://www.hprd.org, a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. CONCLUSIONS: As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL.

Computational Biology↗

PubMed2005

Functional insights from the distribution and role of homopeptide repeat-containing proteins.

Expansion of "low complex" repeats of amino acids such as glutamine (Poly-Q) is associated with protein misfolding and the development of degenerative diseases such as Huntington's disease. The mechanism by which such regions promote misfolding remains controversial, the function of many repeat-containing proteins (RCPs) remains obscure, and the role (if any) of repeat regions remains to be determined. Here, a Web-accessible database of RCPs is presented. The distribution and evolution of RCPs that contain homopeptide repeats tracts are considered, and the existence of functional patterns investigated. Generally, it is found that while polyamino acid repeats are extremely rare in prokaryotes, several eukaryote putative homologs of prokaryote RCP-involved in important housekeeping processes-retain the repetitive region, suggesting an ancient origin for certain repeats. Within eukarya, the most common uninterrupted amino acid repeats are glutamine, asparagines, and alanine. Interestingly, while poly-Q repeats are found in vertebrates and nonvertebrates, poly-N repeats are only common in more primitive nonvertebrate organisms, such as insects and nematodes. We have assigned function to eukaryote RCPs using Online Mendelian Inheritance in Man (OMIM), the Human Reference Protein Database (HRPD), FlyBase, and Wormpep. Prokaryote RCPs were annotated using BLASTp searches and Gene Ontology. These data reveal that the majority of RCPs are involved in processes that require the assembly of large, multiprotein complexes, such as transcription and signaling.

Amino Acid Sequence↗

PubMed2006

Proteome profiling in the rat Harderian gland.

The Harderian gland is an orbital gland located behind the ocular bulb in most terrestrial vertebrates probably functioning for production of lipid secretion to protect the eye. We herein present a protein reference database of the rat Harderian gland that may serve as analytical tool for future proteomic work, report lipid and porphyrin handling cascades, address sequence conflicts and report structures that have not been so far described by proteomics methods.

Amino Acid Sequence↗