PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Databases, Protein”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources
PubMed2001

The RESID Database of protein structure modifications and the NRL-3D Sequence-Structure Database.

The RESID Database is a comprehensive collection of annotations and structures for protein post-translational modifications including N-terminal, C-terminal and peptide chain cross-link modifications. The RESID Database includes systematic and frequently observed alternate names, Chemical Abstracts Service registry numbers, atomic formulas and weights, enzyme activities, taxonomic range, keywords, literature citations with database cross-references, structural diagrams and molecular models. The NRL-3D Sequence-Structure Database is derived from the three-dimensional structure of proteins deposited with the Research Collaboratory for Structural Bioinformatics Protein Data Bank. The NRL-3D Database includes standardized and frequently observed alternate names, sources, keywords, literature citations, experimental conditions and searchable sequences from model coordinates. These databases are freely accessible through the National Cancer Institute-Frederick Advanced Biomedical Computing Center at these web sites: http://www. ncifcrf.gov/RESID, http://www.ncifcrf.gov/NRL-3D; or at these National Biomedical Research Foundation Protein Information Resource web sites: http://pir.georgetown.edu/pirwww/dbinfo/resid .html, http://pir.georgetown.edu/pirwww/dbinfo/nrl3d .html

Amino Acids↗
PubMed1996

Fast comparison of a DNA sequence with a protein sequence database.

We describe a computer program, named DNA-Protein Search (DPS), for comparing a megabase DNA sequence with a protein sequence database. The DPS program addresses the problems of frameshifts and introns in the DNA sequence. The DPS program was used to compare each of the following sequences with the Swiss-Prot database: the 1.8-megabase sequence of the Haemophilus influenzae Rd genome, the 0.58-megabase sequence of the Mycoplasma genitalium genome, and the 0.56-megabase sequence of Saccharomyces cerevisiae chromosome VIII. The comparisons found new regions that are similar to protein sequences. The sensitivity of DPS was evaluated using as test data the known coding regions of the three DNA sequences. The results demonstrate that the DPS program is a useful tool for finding the coding regions of the DNA sequence. The DPS program uses an order of magnitude less computer memory and is several times faster than the BLASTX program.

Amino Acid Sequence↗
PubMed1990

Construction of validated, non-redundant composite protein sequence databases.

A strategy has been developed for the construction of a validated, comprehensive composite protein sequence database. Entries are amalgamated from primary source data bases by a largely automated set of processes in which redundant and trivially different entries are eliminated. A modular approach has been adopted to allow scientific judgement to be used at each stage of database processing and amalgamation. Source databases are assigned a priority depending on the quality of sequence validation and commenting. Rejection of entries from the lower priority database, in each pairwise comparison of databases, is carried out according to optionally defined redundancy criteria based on sequence segment mismatches. Efficient algorithms for this methodology are embodied in the COMPO software system. COMPO has been applied for over 2 years in construction and regular updating of the OWL composite protein sequence database from the source databases NBRF-PIR, SWISS-PROT, a GenBank translation retrieved from the feature tables, NBRF-NEW, NEWAT86, PSD-KYOTO and the sequences contained in the Brookhaven protein structure databank. OWL is part of the ISIS integrated data resource of protein sequence and structure [Akrigg et al. (1988) Nature, 335, 745-746]. The modular nature of the integration process greatly facilitates the frequent updating of OWL following releases of the source databases. The extent of redundancy in these sources is revealed by the comparison process. The advantages of a robust composite database for sequence similarity searching and information retrieval are discussed.

Amino Acid Sequence↗
PubMed2002

The CATH extended protein-family database: providing structural annotations for genome sequences.

An automatic sequence search and analysis protocol (DomainFinder) based on PSI-BLAST and IMPALA, and using conservative thresholds, has been developed for reliably integrating gene sequences from GenBank into their respective structural families within the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath_new). DomainFinder assigns a new gene sequence to a CATH homologous superfamily provided that PSI-BLAST identifies a clear relationship to at least one other Protein Data Bank sequence within that superfamily. This has resulted in an expansion of the CATH protein family database (CATH-PFDB v1.6) from 19,563 domain structures to 176,597 domain sequences. A further 50,000 putative homologous relationships can be identified using less stringent cut-offs and these relationships are maintained within neighbour tables in the CATH Oracle database, pending further evidence of their suggested evolutionary relationship. Analysis of the CATH-PFDB has shown that only 15% of the sequence families are close enough to a known structure for reliable homology modeling. IMPALA/PSI-BLAST profiles have been generated for each of the sequence families in the expanded CATH-PFDB and a web server has been provided so that new sequences may be scanned against the profile library and be assigned to a structure and homologous superfamily.

Algorithms↗
PubMed1996

Puzzle pieces defined: locating common packing units in tertiary protein contacts.

Puzzle pieces are defined as small packing units which make up the unique tertiary interactions in proteins. Anti-parallel and perpendicular helix-helix contacts were broken down into basic puzzle-piece pairs in order to study the traits of such contacts: their limited geometry, preferred residue involvement, residue conformation and other common constraints. These traits can then be used for continued comparison of other protein structures, improving models of and designing proteins de novo and, in time, predicting 3D structure from primary sequence. Results from a small (100 proteins) database of anti-parallel helix-helix contacts and from preliminary work on a large database (600 proteins) of perpendicular helix-helix contacts are presented.

Amino Acid Sequence↗
PubMed1997

A contact scoring matrix for qualitative prediction of change in folding of alpha-helices in globular proteins caused by a mutation.

The atomic pairs in contact for atoms from pairs of amino-acid residues on pairs of helices in a protein database consisting of 48 proteins of known tertiary structure from the Brookhaven Protein Data Bank are searched and counted to construct a primary scoring system. Each score in the primary scoring system is weighted further with the possibility of occurrence of each residue pair in the protein database to give a final scoring matrix. Scores for predicting change in folding of alpha-helices in a mutant protein are calculated by assuming that every pair of helices in the protein can closely interact with each other. It is shown that the change in folding of alpha-helices in several mutant proteins are reflected in both the change of the contact scores and the helix geometry calculated.

Databases, Factual↗
PubMed2000

Update of KEYnet: a gene and protein names database for biosequences functional organisation.

KEYnet is a database where gene and protein names are hierarchically structured. Particular care has been devoted to the search and organisation of synonyms. The structuring is based on biological criteria in order to assist the user in data search and to minimise the risk of information loss. Links to the EMBL data library by the entry name and the accession number are implemented. KEYnet is available through the WWW at the following site: http://www.ba.cnr.it/keynet.html

Databases, Factual↗
PubMed1995

The protein disease database of human body fluids: I. Rationale for the development of this database.

We are developing a relational database to facilitate quantitative and qualitative comparisons of proteins in human body fluids in normal and disease states. For decades researchers and clinicians have been studying proteins in body fluids such as serum, plasma, cerebrospinal fluid and urine. Currently, most clinicians evaluate only a few specific proteins in a body fluid such as plasma when they suspect that a patient has a disease. Now, however, high resolution two-dimensional protein electrophoresis allows the simultaneous evaluation of 1,500 to 3,000 proteins in complex solutions, such as the body fluids. This and other high resolution methods have encouraged us to collect the clinical data for the body fluid proteins into an easily accessed database. For this reason, it has been constructed on the Internet World Wide Web (WWW) under the title Protein Disease Database (PDD). In addition, this database will provide a linkage between the disease-associated protein alterations and images of the appropriate proteins on high-resolution electrophoretic gels of the body fluids. This effort requires the normalization of data to account for variations in methods of measurement. Initial efforts in the establishment of the PDD have been concentrated on alterations in the acute-phase proteins in individuals with acute and chronic diseases. Even at this early stage in the development of our database, it has proven to be useful as we have found that there appear to be several common acute-phase protein alterations in the plasma and cerebrospinal fluid from patients with Alzheimer's disease, schizophrenia and major depression. Our goal is to provide access to the PDD so that systematic correlations and relationships between disease states can be examined and extended.

Body Fluids↗
PubMed2000

The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000.

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domains structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases. Recent developments of the database include format and content enhancements, cross-references to additional databases, new documentation files and improvements to TrEMBL, a computer-annotated supplement to SWISS-PROT. TrEMBL consists of entries in SWISS-PROT-like format derived from the translation of all coding sequences (CDSs) in the EMBL Nucleotide Sequence Database, except the CDSs already included in SWISS-PROT. We also describe the Human Proteomics Initiative (HPI), a major project to annotate all known human sequences according to the quality standards of SWISS-PROT. SWISS-PROT is available at: http://www.expasy.ch/sprot/ and http://www.ebi.ac.uk/swissprot/

Animals↗
PubMed2001

Inverse 18O labeling mass spectrometry for the rapid identification of marker/target proteins.

Systematic analysis of proteins is essential in understanding human diseases and their clinical treatments. To achieve the rapid and unambiguous identification of marker or target proteins, a new procedure termed "inverse labeling" is proposed. With this procedure, to evaluate protein expression of a diseased or a drug-treated sample in comparison with a control sample, two converse labeling experiments are performed in parallel. The perturbed sample (by disease or by drug treatment) is labeled in one experiment, whereas the control is labeled in the second experiment. When mixed and analyzed with its unlabeled counterpart for differential comparison using mass spectrometry, a characteristic inverse labeling pattern of mass shift will be observed between the two parallel analyses for proteins that are differentially expressed. In this study, protein labeling is achieved through 18O incorporation into peptides by proteolysis performed in [18O]water. Once the peptides are identified with the characteristic inverse labeling pattern of 18O/16O ion intensity shift, MS data of peptide fingerprints or peptide sequence information can be used to search a protein database for protein identification. The methodology has been applied successfully to two model systems in this study. It permits quick focus on the signals of differentially expressed proteins. It eliminates the detection ambiguities caused by the dynamic range of detection on proteins of extreme changes in expression. It enables the detection of protein modifications responding to perturbation. This strategy can also be extended to other protein-labeling methods, such as chemical or metabolic labeling, to realize the same benefits.

Biomarkers↗
PubMed1994

Searching protein structure databases has come of age.

The number of protein structures known in atomic detail has increased from one in 1960 (Kendrew, J.C., Strandberg, B.E., Hart, R.G., Davies, D.R., Phillips, D.C., Shore, V.C. Nature (London) 185:422-427, 1960) to more than 1000 in 1994. The rate at which new structures are being published exceeds one a day as a result of recent advances in protein engineering, crystallography, and spectroscopy. More and more frequently, a newly determined structure is similar in fold to a known one, even when no sequence similarity is detectable. A new generation of computer algorithms has now been developed that allows routine comparison of a protein structure with the database of all known structures. Such structure database searches are already used daily and they are beginning to rival sequence database searches as a tool for discovering biologically interesting relationships.

Algorithms↗
PubMed2002

DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions.

The Database of Interacting Proteins (DIP: http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. It provides the scientific community with an integrated set of tools for browsing and extracting information about protein interaction networks. As of September 2001, the DIP catalogs approximately 11 000 unique interactions among 5900 proteins from >80 organisms; the vast majority from yeast, Helicobacter pylori and human. Tools have been developed that allow users to analyze, visualize and integrate their own experimental data with the information about protein-protein interactions available in the DIP database.

Animals↗
PubMed1997

Pfam: a comprehensive database of protein domain families based on seed alignments.

Databases of multiple sequence alignments are a valuable aid to protein sequence classification and analysis. One of the main challenges when constructing such a database is to simultaneously satisfy the conflicting demands of completeness on the one hand and quality of alignment and domain definitions on the other. The latter properties are best dealt with by manual approaches, whereas completeness in practice is only amenable to automatic methods. Herein we present a database based on hidden Markov model profiles (HMMs), which combines high quality and completeness. Our database, Pfam, consists of parts A and B. Pfam-A is curated and contains well-characterized protein domain families with high quality alignments, which are maintained by using manually checked seed alignments and HMMs to find and align all members. Pfam-B contains sequence families that were generated automatically by applying the Domainer algorithm to cluster and align the remaining protein sequences after removal of Pfam-A domains. By using Pfam, a large number of previously unannotated proteins from the Caenorhabditis elegans genome project were classified. We have also identified many novel family memberships in known proteins, including new kazal, Fibronectin type III, and response regulator receiver domains. Pfam-A families have permanent accession numbers and form a library of HMMs available for searching and automatic annotation of new protein sequences.

Amino Acid Sequence↗
PubMed1997

Predicting helical segments in proteins by a helix-coil transition theory with parameters derived from a structural database of proteins.

A novel helix-coil transition theory has been developed. This new theory contains more types of interactions than similar theories developed earlier. The parameters of the models were obtained from a database of 351 nonhomologous proteins. No manual adjustment of the parameters was performed. The interaction parameters obtained in this manner were found to be physically meaningful, consistent with current understanding of helix stabilizing/destabilizing interactions. Novel insights into helix stabilizing/destabilizing interactions have also emerged from this analysis. The theory developed here worked well in sorting out helical residues from amino acid sequences. If the theory was forced to make prediction on every residue of a given amino acid sequence, its performance was the best among ten other secondary structural prediction algorithms in distinguishing helical residues from nonhelical ones. The theory worked even better if one only required it to make prediction on residues that were "predictable" (identifiable by the theory); > 90% predictive reliability could be achieved. The helical residues or segments identified by the helix-coil transition theory can be used as secondary structural contraints to speed up the prediction of the three-dimensional structure of a protein by reducing the dimension of a computational protein folding problem. Possible further improvements of this helix-coil transition theory are also discussed.

Algorithms↗
PubMed2000

RSDB: representative protein sequence databases have high information content.

MOTIVATION: Biological sequence databases are highly redundant for two main reasons: 1. various databanks keep redundant sequences with many identical and nearly identical sequences 2. natural sequences often have high sequence identities due to gene duplication. We wanted to know how many sequences can be removed before the databases start losing homology information. Can a database of sequences with mutual sequence identity of 50% or less provide us with the same amount of biological information as the original full database? RESULTS: Comparisons of nine representative sequence databases (RSDB) derived from full protein databanks showed that the information content of sequence databases is not linearly proportional to its size. An RSDB reduced to mutual sequence identity of around 50% (RSDB50) was equivalent to the original full database in terms of the effectiveness of homology searching. It was a third of the full database size which resulted in a six times faster iterative profile searching. The RSDBs are produced at different granularity for efficient homology searching. AVAILABILITY: All the RSDB files generated and the full analysis results are available through internet: ftp://ftp.ebi.ac. uk/pub/contrib/jong/RSDB/http://cyrah.e bi.ac.uk:1111/Proj/Bio/RSDB

Algorithms↗
PubMed2001

A database of protein expression in lung cancer.

We have developed a comprehensive approach to identifying molecular changes in lung cancer that includes both genomic and proteomic analyses. The related effort has produced a large amount of data pertaining to gene expression at the RNA and protein levels. As a result, we have constructed a database that contains protein expression data on lung cancer as well as other relevant data including DNA microarray derived data. A large number of proteins that are expressed in different types of lung cancer have been identified and have been correlated with the expression measures for their corresponding genes at the RNA level. The database is intended to facilitate our effort at developing novel classification schemes for lung cancer and the identification of novel markers for early diagnosis.

Biomarkers, Tumor↗
PubMed2001

iProClass: an integrated, comprehensive and annotated protein classification database.

The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200,000 non-redundant PIR and SWISS-PROT proteins organized with more than 28,000 superfamilies, 2600 domains, 1300 motifs, 280 post-translational modification sites and links to more than 30 databases of protein families, structures, functions, genes, genomes, literature and taxonomy. Protein and family summary reports provide rich annotations, including membership information with length, taxonomy and keyword statistics, full family relationships, comprehensive enzyme and PDB cross-references and graphical feature display. The database facilitates classification-driven annotation for protein sequence databases and complete genomes, and supports structural and functional genomic research. The iProClass is implemented in Oracle 8i object-relational system and available for sequence search and report retrieval at http://pir.georgetown.edu/iproclass/.

Databases, Factual↗