Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “reference protein database”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 451 records · Page 25Linked to original sources
PubMed1998

Characterization of ten novel and 13 recurring BRCA1 and BRCA2 germline mutations in Italian breast and/or ovarian carcinoma patients. Mutations in brief no. 178. Online.

Germline mutations in the BRCA1 and BRCA2 genes are associated with approximately 80% of families with a high incidence of breast and/or ovarian cancers (OMIM database reference numbers: 113705, 600185). Furthermore, constitutional mutations in the these genes have been reported in women with early-onset breast carcinoma and without family history of cancer. We analyzed by protein truncation test (PTT) and single strand conformation polymorphism (SSCP) followed by sequence analysis, BRCA1 exons 11 and 20 and BRCA2 exons 10 and 11 in 142 Italian cancer patients. These included six male breast cancer cases, 61 women with breast carcinoma diagnosed before 36 years old and selected independently of family history of breast cancer and 75 familial breast and/or ovarian cancer patients. In a previous report, we described 11 different BRCA1 mutations in a subset of 70 cases. Here, we report the characterization of 23 additional mutations, 14 in BRCA1 and 9 in BRCA2, subsequently identified. Ten mutations were not previously described, while the other 13 were recurrent. Of the 61 women with early-onset breast cancer, 11 carried a germline mutation in BRCA1 (18.0%) and four in BRCA2 (6.6%). These frequencies indicate that BRCA1/BRCA2 genetic tests should be advised to women with breast cancer diagnosed at early age, independently of family history of cancer.

BRCA1 Protein↗
PubMed2004

Preformed structural elements feature in partner recognition by intrinsically unstructured proteins.

Intrinsically unstructured proteins (IUPs) are devoid of extensive structural order but often display signs of local and limited residual structure. To explain their effective functioning, we reasoned that such residual structure can be crucial in their interactions with their structured partner(s) in a way that preformed structural elements presage their final conformational state. To check this assumption, a database of 24 IUPs with known 3D structures in the bound state has been assembled and the distribution of secondary structure elements and backbone torsion angles have been analysed. The high proportion of residues in coil conformation and with phi, psi angles in the disallowed regions of the Ramachandran map compared to the reference set of globular proteins shows that IUPs are not fully ordered even in their bound form. To probe the effect of partner proteins on IUP folding, inherent conformational preferences of IUP sequences have been assessed by secondary structure predictions using the GOR, ALB and PROF algorithms. The accuracy of predicting secondary structure elements of IUPs is similar to that of their partner proteins and is significantly higher than the corresponding values for random sequences. We propose that strong conformational preferences mark regions in IUPs (mostly helices), which correspond to their final structural state, while regions with weak conformational preferences represent flexible linkers between them. In our interpretation, preformed elements could serve as initial contact points, the binding of which facilitates the reeling of the flexible regions onto the template. This finding implies that IUPs draw a functional advantage from preformed structural elements, as they enable their facile, kinetically and energetically less demanding, interaction with their physiological partner.

Databases, Protein↗
PubMed2000

InterPro--an integrated documentation resource for protein families, domains and functional sites.

MOTIVATION: InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed initially as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. RESULTS: Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc. Merged and individual entries (i.e. those that have no counterpart in the companion resources) are assigned unique accession numbers. Release 1.2 of InterPro (June 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 6581 different regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1000000 hits from 264333 different proteins out of 384572 in SWISS-PROT and TrEMBL).

Computational Biology↗
PubMed2006

ExtraTrain: a database of Extragenic regions and Transcriptional information in prokaryotic organisms.

BACKGROUND: Transcriptional regulation processes are the principal mechanisms of adaptation in prokaryotes. In these processes, the regulatory proteins and the regulatory DNA signals located in extragenic regions are the key elements involved. As all extragenic spaces are putative regulatory regions, ExtraTrain covers all extragenic regions of available genomes and regulatory proteins from bacteria and archaea included in the UniProt database. DESCRIPTION: ExtraTrain provides integrated and easily manageable information for 679816 extragenic regions and for the genes delimiting each of them. In addition ExtraTrain supplies a tool to explore extragenic regions, named Palinsight, oriented to detect and search palindromic patterns. This interactive visual tool is totally integrated in the database, allowing the search for regulatory signals in user defined sets of extragenic regions. The 26046 regulatory proteins included in ExtraTrain belong to the families AraC/XylS, ArsR, AsnC, Cold shock domain, CRP-FNR, DeoR, GntR, IclR, LacI, LuxR, LysR, MarR, MerR, NtrC/Fis, OmpR and TetR. The database follows the InterPro criteria to define these families. The information about regulators includes manually curated sets of references specifically associated to regulator entries. In order to achieve a sustainable and maintainable knowledge database ExtraTrain is a platform open to the contribution of knowledge by the scientific community providing a system for the incorporation of textual knowledge. CONCLUSION: ExtraTrain is a new database for exploring Extragenic regions and Transcriptional information in bacteria and archaea. ExtraTrain database is available at http://www.era7.com/ExtraTrain/.

Archaea↗
PubMed2000

NCBI genetic resources supporting immunogenetic research.

The NCBI creates and maintains a set of integrated bibliographic, sequence, map, structure and other database resources to promote the efficient retrieval of information and the discovery of novel relationships. The connections made between elements of these resources permit researchers to start a search from a wide spectrum of entry points. These multiple dimensions of data can be roughly categorized by primary content as text or bibliographic (PubMed, PubMedCentral, OMIM, LocusLink), sequence (GenBank, Reference Sequence Project (RefSeq), dbSNP, MMDB), protein structure (MMDB) or map position (MapView). They can also becategorized by level of expert curation, which may range from validation of submissions from external groups (GenBank, PubMed, PubMedCentral,), to automatic computation (HomoloGene, UniGene), and to highly reviewed and corrected (LocusLink, MMDB, OMIM, RefSeq). Searches can be made by words (in an article title, key words, sequence annotation, database value, author) by sequence (BLAST or e-PCR against multiple sequence databases), or by map coordinates. By computing or curating bi-directional links between related objects, NCBI can represent content on the genetics, molecular biology, and clinical considerations of interest to immunogeneticists. There is also an emerging resource developed by the NCBI in collaboration with the IHWG devoted to the presentation of MHC data (dbMHC). How dbMHC will augment existing resources at the NCBI is described.

Computational Biology↗
PubMed2025

PEELing: an integrated and user-centric platform for spatially resolved proteomics data analysis.

SUMMARY: Molecular compartmentalization is vital for cellular physiology. Spatially resolved proteomics allows biologists to survey protein composition and dynamics with subcellular resolution. Here, we present PEELing, an integrated package and user-friendly web service for analyzing spatially resolved proteomics data. PEELing assesses data quality using curated or user-defined references, performs cutoff analysis to remove contaminants, connects to databases for functional annotation, and generates data visualizations-providing a streamlined and reproducible workflow to explore spatially resolved proteomics data. AVAILABILITY AND IMPLEMENTATION: PEELing and its tutorial are publicly available at https://peeling.janelia.org/ (Zenodo DOI: 10.5281/zenodo.15692517). A Python package of PEELing is available at https://github.com/JaneliaSciComp/peeling/ (Zenodo DOI: 10.5281/zenodo.15692434).

Proteomics↗
PubMed2005

A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy.

Characterization of the human blood plasma proteome is critical to the discovery of routinely useful clinical biomarkers. We used an accurate mass and time (AMT) tag strategy with high-resolution mass accuracy cLC-FT-ICR MS to perform a global proteomic analysis of pilot study samples as part of the HUPO Plasma Proteome Project. HUPO reference serum and citrated plasma samples from African Americans, Asian Americans, and Caucasian Americans were analyzed, in addition to a Pacific Northwest National Laboratory reference serum and plasma. The AMT tag strategy allowed us to leverage two previously published "shotgun" proteomics experiments to perform global analyses on these samples in triplicate in less than 4 days total analysis time. A total of 722 (22% with multiple peptide identifications) International Protein Index redundant proteins, or 377 protein families by ProteinProphet, were identified over the six individual HUPO serum and plasma samples. The samples yielded a similar number of identified redundant proteins in the plasma samples (average 446 +/- 23) as found in the serum samples (average 440 +/- 20). These proteins were identified by an average of 956 +/- 35 unique peptides in plasma and 930 +/- 11 unique peptides in serum. In addition to this high-throughput analysis, the AMT tag approach was used with a Z-score normalization to compare relative protein abundances. This analysis highlighted both known differences in serum and citrated plasma such as fibrinogens, and reproducible differences in peptide abundances from proteins such as soluble activin receptor-like kinase 7b and glycoprotein m6b. The AMT tag strategy not only improved our sample throughput but also provided a basis for estimated quantitation.

Blood Proteins↗
PubMed2006

Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes.

BACKGROUND: A cluster analysis is the most commonly performed procedure (often regarded as a first step) on a set of gene expression profiles. In most cases, a post hoc analysis is done to see if the genes in the same clusters can be functionally correlated. While past successes of such analyses have often been reported in a number of microarray studies (most of which used the standard hierarchical clustering, UPGMA, with one minus the Pearson's correlation coefficient as a measure of dissimilarity), often times such groupings could be misleading. More importantly, a systematic evaluation of the entire set of clusters produced by such unsupervised procedures is necessary since they also contain genes that are seemingly unrelated or may have more than one common function. Here we quantify the performance of a given unsupervised clustering algorithm applied to a given microarray study in terms of its ability to produce biologically meaningful clusters using a reference set of functional classes. Such a reference set may come from prior biological knowledge specific to a microarray study or may be formed using the growing databases of gene ontologies (GO) for the annotated genes of the relevant species. RESULTS: In this paper, we introduce two performance measures for evaluating the results of a clustering algorithm in its ability to produce biologically meaningful clusters. The first measure is a biological homogeneity index (BHI). As the name suggests, it is a measure of how biologically homogeneous the clusters are. This can be used to quantify the performance of a given clustering algorithm such as UPGMA in grouping genes for a particular data set and also for comparing the performance of a number of competing clustering algorithms applied to the same data set. The second performance measure is called a biological stability index (BSI). For a given clustering algorithm and an expression data set, it measures the consistency of the clustering algorithm's ability to produce biologically meaningful clusters when applied repeatedly to similar data sets. A good clustering algorithm should have high BHI and moderate to high BSI. We evaluated the performance of ten well known clustering algorithms on two gene expression data sets and identified the optimal algorithm in each case. The first data set deals with SAGE profiles of differentially expressed tags between normal and ductal carcinoma in situ samples of breast cancer patients. The second data set contains the expression profiles over time of positively expressed genes (ORF's) during sporulation of budding yeast. Two separate choices of the functional classes were used for this data set and the results were compared for consistency. CONCLUSION: Functional information of annotated genes available from various GO databases mined using ontology tools can be used to systematically judge the results of an unsupervised clustering algorithm as applied to a gene expression data set in clustering genes. This information could be used to select the right algorithm from a class of clustering algorithms for the given data set.

Algorithms↗
PubMed1996

cDNA expression and human two-dimensional gel protein databases: towards integrating DNA and protein information.

The rapid progress in characterizing genes and mRNAs (expressed sequence tags, ESTs) as a result of the Human Genome Project makes it imperative to develop strategies to interface DNA mapping and sequencing data with protein information, as the latter orchestrate most cellular functions. Presently, the only technique able to resolve and record the thousands of proteins present in cells and tissues is two-dimensional (2-D) gel electrophoresis in combination with computer-aided technology to scan the gels, make synthetic images, assign numbers to individual spots as well as to enter qualitative and quantitative information. To date, comprehensive 2-D gel databases containing information about various properties of proteins (cellular localization, identification, regulatory properties, partial amino acid sequences, etc.) have been established (available on the internet: http:@biobase.dk/cgi-bin/celis). What remains is to provide a link between these data and the forthcoming information from the Human Genome Project. We are pursuing two approaches to achieve this goal: (i) microsequencing and mass spectrometry analysis of proteins resolved from 2-D gels and (ii) expression of cDNAs in the vaccinia virus expression system. Using the latter approach we have expressed about 60 cDNAs in human cells under conditions that faithfully reproduce post-translational trimmings and modifications of the proteins. The method, in combination with 2-D gel electrophoresis, allows precise matching of almost any cDNA to its protein product, irrespective of the protein abundance.

Animals↗
PubMed1998

The chicken homologue of zona pellucida protein-3 is synthesized by granulosa cells.

Oocyte development within avian ovarian follicles is an intricate process involving yolk deposition and the formation of extraoocytic matrices. Of these, the perivitelline membrane (pvm) not only plays a role in sperm binding but also provides mechanical support for the large oocyte's journey through the oviduct after ovulation. To date we have focused on the mechanisms for uptake of yolk precursors into oocytes of the chicken; now we extend our studies to a detailed analysis of the pvm. In the course of characterization of its major components, we obtained partial protein sequences; comparison with the GenBank database revealed that one of the pvm proteins is the homologue of mammalian zona pellucida glycoprotein 3 (ZP3), a key component in sperm binding. Following a nomenclature based on gene structure, the protein is referred to as chicken ZPC (chZPC). The chicken protein (444 residues) and murine ZP3 (424 residues) are highly conserved, with 41% of the amino acids identical. As shown by Northern blot analysis, the avian ZPC gene is expressed exclusively in the granulosa cells surrounding the oocyte, in contrast to murine ZP3, which is synthesized by the oocyte. Upon reaching a size larger than 1.5 mm in diameter, follicles accumulate chZPC in highly polarized fashion, i.e., in the space intercalated between the oocyte and the granulosa cells, as revealed by immunohistochemistry of follicle sections. ChZPC synthesis and secretion by granulosa cells was demonstrated directly by metabolic labeling and immunoprecipitation from the culture medium of granulosa cell sheets isolated ex vivo from follicles. Immunoblot analysis and glycosidase treatment of chZPC from preovulatory and freshly ovulated oocytes, as well as laid eggs, revealed that the primary product undergoes a two-step decrease in size from follicle to laid egg that is unlikely to be due to modification of the carbohydrate moiety.

Amino Acid Sequence↗
PubMed2006

Efficient molecular docking of NMR structures: application to HIV-1 protease.

Docking ligands into an ensemble of NMR conformers is essential to structure-based drug discovery if only NMR structures are available for the target. However, sequentially docking ligands into each NMR conformer through standard single-receptor-structure docking, referred to as sequential docking, is computationally expensive for large-scale database screening because of the large number of NMR conformers involved. Recently, we developed an efficient ensemble docking algorithm to consider protein structural variations in ligand binding. The algorithm simultaneously docks ligands into an ensemble of protein structures and achieves comparable performance to sequential docking without significant increase in computational time over single-structure docking. Here, we applied this algorithm to docking with NMR structures. The HIV-1 protease was used for validation in terms of docking accuracy and virtual screening. Ensemble docking of the NMR structures identified 91% of the known inhibitors under the criterion of RMSD < 2.0 A for the best-scored conformation, higher than the average success rate of single docking of individual crystal structures (66%). In the virtual screening test, on average, ensemble docking of the NMR structures obtained higher enrichments than single-structure docking of the crystal structures. In contrast, docking of either the NMR minimized average structure or a single NMR conformer performed less satisfactorily on both binding mode prediction and virtual screening, indicating that a single NMR structure may not be suitable for docking calculations. The success of ensemble docking of the NMR structures suggests an efficient alternative method for standard single docking of crystal structures and for considering protein flexibility.

Algorithms↗
PubMed2003

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

The mapping of the human genome and the determination of corresponding gene functions, pathways, and biological mechanisms are driving the emergence of the new research fields of toxicogenomics and systems toxicology. Many technological advances such as microarrays are enabling this paradigm shift that indicates an unprecedented advancement in the methods of understanding the expression of toxicity at the molecular level. At the National Center for Toxicological Research (NCTR) of the U.S. Food and Drug Administration, core facilities for genomic, proteomic, and metabonomic technologies have been established that use standardized experimental procedures to support centerwide toxicogenomic research. Collectively, these facilities are continuously producing an unprecedented volume of data. NCTR plans to develop a toxicoinformatics integrated system (TIS) for the purpose of fully integrating genomic, proteomic, and metabonomic data with the data in public repositories as well as conventional (Italic)in vitro(/Italic) and (Italic)in vivo(/Italic) toxicology data. The TIS will enable data curation in accordance with standard ontology and provide or interface a rich collection of tools for data analysis and knowledge mining. In this article the design, practical issues, and functions of the TIS are discussed through presenting its prototype version, ArrayTrack, for the management and analysis of DNA microarray data. ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to gene information in the LIB.

Databases, Factual↗
PubMedDate not supplied

The Dictyostelium discoideum proteome--the SWISS-2DPAGE database of the multicellular aggregate (slug).

The cellular slime mold Dictyostelium discoideum is a eukaryotic microorganism which has developmental life stages attractive to the cell and molecular biologist. By displaying the two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) protein map of different developmental stages, the key molecules can be identified and characterised, allowing a detailed understanding of the D. discoideum proteome. Here we describe the preparation of reference gel of the D. discoideum multicellular aggregate, the slug. Proteins were separated by 2-D PAGE with immobilised pH gradients (pH 3.5-10) in the first dimension and sodium dodecyl sulfate (SDS)-PAGE in the second dimension. Micropreparative gels were electroblotted onto polyvinylidene difluoride (PVDF) membranes and 150 spots were visualised by amido black staining. Protein spots were excised and 31 were putatively identified by matching their amino acid composition, estimated isoelectric point (pI) and molecular weight (M(r)) against the SWISS-PROT database with the ExPASy AAcompID tool (http:// expasy.hcuge.ch/ch2d/aacompi.html). A total of 25 proteins were identified by matching against database entries for D. discoideum, and another six by cross-species matching against database entries for Saccharomyces cerevisiae proteins. This map will be available in the SWISS-2DPAGE database.

Animals↗
PubMed2006

Strength of the purifying selection against different categories of the point mutations in the coding regions of the human genome.

Using available Information on the total absolute size of the coding region of the human genome, data on codon usage and pseudogene-derived mutation rates for different single nucleotide substitutions we have estimated, for the human genome, the potential numbers of mutation events capable to produce: (1) nonsense; (2) missense (radical and conservative); (3) silent; (4) splice; and (5) protein-elongating (those changing wild-type stop codon into an amino acid encoding codon) mutations. We used the NCBI dbSNP database to retrieve data on the observed number of polymorphisms of each category. The fraction of polymorphisms in each category among all potential events in the genome depends on the strength of selection: the higher the rate of polymorphism, the weaker the selection. We used nonsense mutations as a referent group. Compared with nonsense mutations, we found that the relative selection coefficient against protein-elongating mutations was 21%, and the relative selection was 12% against missense mutations. Radical missense mutations were found to be four times more deleterious compared to conservative ones. Surprisingly, we found that silent mutations on average are not neutral; with the average harmfulness of 3% of nonsense mutations. Silent mutations may be deleterious when they affect splicing by creating cryptic donor-acceptor sites or by disturbing exonic splicing enhancers (ESESs). The average selection coefficient against splice mutations was 48% of that against nonsense mutations. Converting the relative selection coefficients into absolute ones using data on loss-of-function mutations in Saccharomyces cerevisiae and Caenorhabditis elegans, or by analysis of the expected frequency of mutations in the human genome, suggested that genetic drift could play a role in population dynamics of conservative missense and silent mutations.

Computational Biology↗
PubMed2006

Estimating probabilities of peptide database identifications to LC-FTICR-MS observations.

BACKGROUND: The field of proteomics involves the characterization of the peptides and proteins expressed in a cell under specific conditions. Proteomics has made rapid advances in recent years following the sequencing of the genomes of an increasing number of organisms. A prominent technology for high throughput proteomics analysis is the use of liquid chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS). Meaningful biological conclusions can best be made when the peptide identities returned by this technique are accompanied by measures of accuracy and confidence. METHODS: After a tryptically digested protein mixture is analyzed by LC-FTICR-MS, the observed masses and normalized elution times of the detected features are statistically matched to the theoretical masses and elution times of known peptides listed in a large database. The probability of matching is estimated for each peptide in the reference database using statistical classification methods assuming bivariate Gaussian probability distributions on the uncertainties in the masses and the normalized elution times. RESULTS: A database of 69,220 features from 32 LC-FTICR-MS analyses of a tryptically digested bovine serum albumin (BSA) sample was matched to a database populated with 97% false positive peptides. The percentage of high confidence identifications was found to be consistent with other database search procedures. BSA database peptides were identified with high confidence on average in 14.1 of the 32 analyses. False positives were identified on average in just 2.7 analyses. CONCLUSION: Using a priori probabilities that contrast peptides from expected and unexpected proteins was shown to perform better in identifying target peptides than using equally likely a priori probabilities. This is because a large percentage of the target peptides were similar to unexpected peptides which were included to be false positives. The use of triplicate analyses with a "2 out of 3" reporting rule was shown to have excellent rejection of false positives.

Journal Article↗
PubMed1995

Effects of local environment on the circular dichroism spectra of polypeptides.

The secondary structures of proteins may be estimated by analysis of their circular dichroism spectra using techniques which empirically fit component spectra derived from water-soluble protein databases. However, local environment effects red- or blue-shift peptide energy transitions primarily through solvent polarization effects and may be an especially important factor for proteins in nonaqueous environments. In this study the reference basis spectra were deconvoluted into three component Gaussian curves corresponding to each of the peptide absorbances in the wavelength range from 190 to 240 nm. These Gaussians were then systematically shifted and utilized in the analyses of the spectra of crambin solubilized in a variety of nonaqueous solvents, including that of the polypeptide associated with small unilamellar phospholipid vesicles. Crambin was selected since its well-characterized structure was found to retain native structure in a variety of nonaqueous environments. This method was more successful in estimating the helical content of this protein than conventional methodologies. This type of analysis may prove to be appropriate for estimating the secondary structure of proteins found in nonaqueous environments, such as membrane proteins.

Alcohols↗
PubMed2003

Rapid detection and identification of angiotensin-converting enzyme inhibitors by on-line liquid chromatography-biochemical detection, coupled to electrospray mass spectrometry.

An analytical method based on on-line liquid chromatography-biochemical detection (LC-BCD) coupled to electrospray mass spectrometry was developed for the detection and identification of angiotensin-converting enzyme (ACE) inhibitors in complex mixtures, such as hydrolyzed whey proteins. ACE inhibitory activity was detected by coupling a homogeneous, substrate conversion based bioassay on-line to high-performance liquid chromatography (HPLC). Chemical information was obtained by directing part of the HPLC effluent towards a mass spectrometer. After correlating the biochemical and chemical data, the accurate molecular masses of the bioactive peptides were used as search queries in protein databases. Combined with the recorded mass spectrometry (MS)-MS fingerprints, bioactive peptides were selected from the database search results. The results of LC-BCD-MS analyses were verified by establishing a bioactivity balance. Reference samples, containing several peptides at concentration levels similar to those observed in the hydrolyzed milk samples, were analyzed by LC-BCD-MS. High recoveries of biological activity were obtained, indicating that the correct ACE inhibitors were identified and that no co-elution of significantly bioactive molecules had occurred. Approximately, 30 ACE inhibitors were detected and identified. IC50 values of ACE inhibitors, reported in literature, ranged between 43 and 580 microM.

Amino Acid Sequence↗
PubMed2004

GenAge: a genomic and proteomic network map of human ageing.

The aim of this work was to provide an overview of the genetics of human ageing to gain novel insights about the mechanisms involved. By incorporating findings from model organisms to humans, such as mutations that either delay or accelerate ageing in mice, we constructed the gene networks previously related to ageing: namely, the network related to DNA metabolism and the network involving the GH/IGF-1 axis. Gathering data about the interacting partners of these proteins allowed us to suggest the involvement in ageing of a number of proteins through a "guilt-by-association" methodology. To organize our data, we developed the first curated database of genes related to human ageing: GenAge. With over 200 entries, GenAge may serve as a reference database of genes related to human ageing. Moreover, we rendered the first proteomic network map of human ageing, which suggests a relationship between the genetics of development and the genetics of ageing. Our work serves as a framework upon which a systems-biology understanding of ageing can be developed. GenAge is freely available for academic purposes at: http://genomics.senescence.info/genes/.

Aging↗