Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “quantitative proteomics”

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 1,027 records · Page 57Linked to original sources
PubMed2006

Identification of substrates of the extracellular protease ADAMTS1 by DIGE proteomic analysis.

Proteolytic modification of components of the extracellular milieu by metalloproteinases plays important roles in the regulation of multiple cellular and physiological processes and pathological conditions. ADAMTS1 is a secreted enzyme of the ADAMTS (a disintegrin and metalloproteinase with thrombospondin motifs) family of proteases, which is related to angiogenesis and inflammation processes. Here, we describe a proteomic screening for putative ADAMTS1 substrates by analyzing the protein profiles obtained from cultures of transfected cells overexpressing the protease as compared to parental cells. Conditioned medium proteins of cultures of the two cell lines have been quantitatively compared by DIGE. Proteins showing differential levels have been identified by MS techniques leading to the finding of five potential new substrates of ADAMTS1: the basement membrane proteins nidogen-1 and -2, the desmosomal protein desmocollin-3, and the extracellular glycoproteins dystroglycan 1 and Mac-2-binding protein. Nidogen-1 and -2 have been further validated as substrates by immunochemical analysis. Our results demonstrate the utility of the DIGE proteomic technique for the discovery of specific substrates of matrix proteases.

ADAM Proteins↗
PubMed2004

Identification of specific plant nucleolar phosphoproteins in a functional proteomic analysis.

The soluble fraction of nuclear proteins is a functionally significant fraction, since it has been shown that it contains ribonucleoproteins active in nuclear RNA metabolism. The aim of this work was to detect variations associated with cell proliferation, by comparing two-dimensional proteomes obtained from the soluble fractions of onion nuclei isolated from actively proliferating root meristematic cells versus nonmeristematic root cells. In particular, we have studied the physicochemical features of the major nucleolar protein NopA100, a highly phosphorylated, nucleolin-like protein. A total of 384 spots were quantified in meristematic nuclei, while only 209 were detected in nonmeristematic nuclei. The comparison of both proteomes resulted in the determination of specific spots for each proliferative state and those which were common to both cases. Furthermore, among these latter, we could discriminate quantitative differences. Interestingly, well-known nucleolar proteins, such as RNA polymerase I, B23 and the nucleolin-like protein NopA100, were significantly increased in proliferating cells. Western blots with anti-NopA100 antibody demonstrated 26 spots in the meristematic sample. All the spots detected were clustered at 100 kDa and were distributed through an isoelectric point (pI) range of 4.3-6.6. In contrast, only seven spots were found in the extract from nonmeristematic nuclei, and the pI range was shortened to 4.8-6.1. These results indicate that the state of NopA100 phosphorylation correlates with the degree of nucleolar activity, i.e. the protein is more highly phosphorylated in cycling cells. We have also analyzed the bidimensional silver staining of the nucleolar organizing region (Ag-NOR) pattern of the soluble nuclear fraction in order to identify plant cell phosphoproteins that are considered to be markers of proliferation. These experiments demonstrated that NopA100, the onion, nucleolin-like protein, is an Ag-NOR protein. In addition we found that the plant homologue of the vertebrate nucleolar phosphoprotein B23 migrated as two clusters of acidic spots, 43 and 42 kDa respectively in molecular mass. The differences between these features and those described for mammalian cells is discussed. Our results demonstrate that the use of protein fractionation procedures with functional significance and the location of candidate spots by indirect techniques are advantageous, complementary methods to random selection procedures for proteomic studies involving further mass spectrometry analysis.

Cell Division↗
PubMed2006

Integration of two-dimensional LC-MS with multivariate statistics for comparative analysis of proteomic samples.

LC-MS-based proteomics requires methods with high peak capacity and a high degree of automation, integrated with data-handling tools able to cope with the massive data produced and able to quantitatively compare them. This paper describes an off-line two-dimensional (2D) LC-MS method and its integration with software tools for data preprocessing and multivariate statistical analysis. The 2D LC-MS method was optimized in order to minimize peptide loss prior to sample injection and during the collection step after the first LC dimension, thus minimizing errors from off-column sample handling. The second dimension was run in fully automated mode, injecting onto a nanoscale LC-MS system a series of more than 100 samples, representing fractions collected in the first dimension (8 fractions/sample). As a model study, the method was applied to finding biomarkers for the antiinflammatory properties of zilpaterol, which are coupled to the beta2-adrenergic receptor. Secreted proteomes from U937 macrophages exposed to lipopolysaccharide in the presence or absence of propanolol or zilpaterol were analysed. Multivariate statistical analysis of 2D LC-MS data, based on principal component analysis, and subsequent targeted LC-MS/MS identification of peptides of interest demonstrated the applicability of the approach.

Adrenergic beta-Antagonists↗
PubMed2006

Transcription and mass-spectroscopic proteomic studies of electron transport oxidoreductases in Dehalococcoides ethenogenes.

Besides 19 potential reductive dehalogenase genes, the genome of Dehalococcoides ethenogenes strain 195 contains over 60 genes annotated as encoding oxidoreductases, including five hydrogenase complexes and a formate dehydrogenase (Fdh). Using quantitative reverse transcriptase polymerase chain reaction, we found that genes encoding a periplasmic Hup hydrogenase and the Fdh were the most highly expressed in batch-grown pure cultures, in which the H2 partial pressure was >0.1 atm, and in butyrate/tetrachloroethene-mixed cultures, in which H2 partial pressures were 10(-4)-10(-5) atm. Shotgun electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry were used to identify multiple peptides in pure culture membrane-enriched fractions matching several highly expressed respiratory enzymes, including three hydrogenases, two reductive dehalogenases, Fdh and DET1407, a 105.5-kDa protein we propose to be part of an S-layer cell wall. Both transcript and mass spectrometric approaches indicated that the putative Fdh was an important oxidoreductase in these cells; nevertheless, D. ethenogenes cultures could not use formate as an electron donor for reductive dechlorination. Analysis of the gene encoding the large subunit of Fdh indicated that while it was related to other Fdh proteins, its sequence encodes serine rather than cysteine or selenocysteine at a critical position, casting doubt on its function. Overall, genomic and proteomic approaches have provided novel insights into the metabolism of this difficult to culture organism.

Bacterial Proteins↗
PubMed2004

Understanding human dendritic cell biology through gene profiling.

Dendritic cells are potent antigen presenting cells whose function has been associated with a variety of immunological disorders. Because of their relevance to human disease, extensive efforts have been made to gain a better understanding of their biology. One aspect of these efforts has been in the identification of pertinent molecules expressed in these cells through gene profiling experiments and proteomics. In this review, we summarize the results from the various profiling studies that have been done with human dendritic cells. We focus on molecules, which have been confirmed by other methods, such as quantitative PCR, or have been identified in multiple profiling studies to be expressed in the respective dendritic cell type. Through such profiling experiments and subsequent analysis, interesting molecules have been identified which can be further studied to determine their role in dendritic cell biology.

Dendritic Cells↗
PubMed2026

Deciphering novel targets in salivary gland pleomorphic adenoma by integrating plasma proteomics and parotid transcriptomics analyses.

BACKGROUND/PURPOSE: Pleomorphic adenoma (PA) is the most common salivary gland benign tumor, with its molecular drivers elusive due to a lack of experimental models. This study aimed to decipher novel targets in PA by systematically integrating plasma protein quantitative trait loci (pQTL)-based Mendelian randomization (MR) with multi-omics profiling of parotid gland tissues. MATERIALS AND METHODS: We performed two-sample MR using 5450 plasma pQTLs and genome-wide association study summary for benign or broader salivary gland diseases from FinnGen consortium. Bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) comparing PA to normal tissue were used for transcriptomic validation. Immunohistochemistry (IHC) was applied for protein-level validation in human PA, adenoid cystic carcinoma (ACC), and murine inflammatory lesions. RESULTS: MR identified 12 plasma proteins associated with benign salivary gland tumor risk. Transmembrane serine protease 6 (TMPRSS6) was the only protein significantly risk-increasing for both benign and broader salivary gland diseases. Strikingly, mitogen-activated protein kinase kinase 4 (MAP2K4) showed opposite MR effects between benign and all-lesion outcomes. Bulk RNA-seq showed limited concordance with MR findings, while scRNA-seq revealed a unique plastic epithelium and partially validated candidates at cellular resolution. Critically, IHC confirmed MAP2K4 protein overexpression specifically in human PA, but not in ACC or inflammatory lesions, while TMPRSS6 was downregulated in established pathologies despite its genetic risk association. CONCLUSION: By integrating plasma proteome-based causal inference with parotid tissue multi-omics, this study unveils MAP2K4 as a potential PA-specific driver. This integrative framework provides novel, context-specific targets for further functional investigation in salivary gland tumorigenesis.

Gene expression profiling↗
PubMedDate not supplied

Integrated sampling procedure for metabolome analysis.

Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures < or =95 degrees C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h(-)(1).

Adenosine Triphosphate↗
PubMed2006

Proteomic profiling of ClpXP substrates after DNA damage reveals extensive instability within SOS regulon.

ClpXP, a bacterial AAA+ protease, controls intracellular levels of many stress-response proteins. To investigate substrate profile changes caused by a specific environmental stress, quantitative mass spectrometry (SILAC) was used to analyze proteins trapped by ClpXP(trap) before and after DNA damage. The abundance of half of the trapped proteins changed more than 3-fold after damage. Overrepresented substrates included the DNA-repair proteins RecN and UvrA. Among SOS-response proteins, 25% were ClpXP substrates and, importantly, nearly all of the highly induced regulon members were rapidly degraded. Other proteins, including the stress regulator sigma(S), were underrepresented in ClpXP(trap) after DNA damage; overproduction experiments suggest that simple substrate competition does not account for this reduced recognition. We conclude that damage-response proteins are an unusually rapidly degraded family and that ClpXP has substantial capacity to process the influx of newly synthesized substrates while maintaining the ability to degrade its other substrates in an environmentally responsive manner.

Adenosine Triphosphatases↗
PubMed2026

A nucleolar stress gene signature enables quantitative scoring across multi-omics contexts.

The nucleolus is essential for ribosome biogenesis and cellular homeostasis, and its dysfunction can induce nucleolar stress, a process implicated in cancer and other diseases. However, nucleolar stress is commonly inferred from morphological changes or a limited set of functional assays, and quantitative approaches based on gene expression profiles remain lacking. Here, we integrate literature curation with multi-dataset screening to define a nucleolar stress gene signature and develop a nucleolar stress score (NuS) applicable to bulk transcriptomics, single-cell transcriptomics, proteomics, and spatial transcriptomics. Using this framework, we show in colorectal cancer models that oxaliplatin induces nucleolar stress, suppresses nascent rRNA synthesis, and activates p53 signaling, whereas these responses are attenuated in oxaliplatin-resistant cells. Combined with a ribosome biogenesis activity score (RiboSis), NuS captures related but distinct dimensions of nucleolar function and stratifies tumors into functional states associated with clinical outcomes. NuS-based analysis of perturbational transcriptomes further prioritizes compounds with putative nucleolar stress-inducing activity. Collectively, this study provides a quantitative framework for evaluating nucleolar stress and illustrates its applications in disease stratification and drug mechanism discovery.

Cell Nucleolus↗
PubMed2006

Transcriptomic and proteomic analyses of the pMOL30-encoded copper resistance in Cupriavidus metallidurans strain CH34.

The four replicons of Cupriavidus metallidurans CH34 (the genome sequence was provided by the US Department of Energy-University of California Joint Genome Institute) contain two gene clusters putatively encoding periplasmic resistance to copper, with an arrangement of genes resembling that of the copSRABCD locus on the 2.1 Mb megaplasmid (MPL) of Ralstonia solanacearum, a closely related plant pathogen. One of the copSRABCD clusters was located on the 2.6 Mb MPL, while the second was found on the pMOL30 (234 kb) plasmid as part of a larger group of genes involved in copper resistance, spanning 17 857 bp in total. In this region, 19 ORFs (copVTMKNSRABCDIJGFLQHE) were identified based on the sequencing of a fragment cloned in an IncW vector, on the preliminary annotation by the Joint Genome Institute, and by using transcriptomic and proteomic data. When introduced into plasmid-cured derivatives of C. metallidurans CH34, the cop locus was able to restore the wild-type MIC, albeit with a biphasic survival curve, with respect to applied Cu(II) concentration. Quantitative-PCR data showed that the 19 ORFs were induced from 2- to 1159-fold when cells were challenged with elevated Cu(II) concentrations. Microarray data showed that the genes that were most induced after a Cu(II) challenge of 0.1 mM belonged to the pMOL30 cop cluster. Megaplasmidic cop genes were also induced, but at a much lower level, with the exception of the highly expressed MPL copD. Proteomic data allowed direct observation on two-dimensional gel electrophoresis, and via mass spectrometry, of pMOL30 CopK, CopR, CopS, CopA, CopB and CopC proteins. Individual cop gene expression depended on both the Cu(II) concentration and the exposure time, suggesting a sequential scheme in the resistance process, involving genes such as copK and copT in an initial phase, while other genes, such as copH, seem to be involved in a late response phase. A concentration of 0.4 mM Cu(II) was the highest to induce maximal expression of most cop genes.

Amino Acid Sequence↗
PubMed2006

Effect of staining reagent on peptide mass fingerprinting from in-gel trypsin digestions: a comparison of SyproRuby and DeepPurple.

As the new fluorescent stains such as SyproRuby and DeepPurple are getting widespread recognition for proteome analyses by the traditional 2-D gel method, it becomes important to test the feasibility of these stains with respect to staining reproducibility, protein quantitation, and compatibility of the stain with downstream MS. The binding of epicocconone, active ingredient of DeepPurple, to one of the primary cleavage sites of trypsin (lysine residue) raises the possibility of incomplete cleavage and interference with PMF. However, the current study tests and concludes that the DeepPurple stain can result in increased peptide recovery compared to SyproRuby stain and can improve MS-based identification of lower intensity proteins spots.

Coloring Agents↗
PubMed2006

The emergence of yeast lipidomics.

The emerging field of lipidomics, driven by technological advances in lipid analysis, provides greatly enhanced opportunities to characterize, on a quantitative or semi-quantitative level, the entire spectrum of lipids, or lipidome, in specific cell types. When combined with advances in other high throughput technologies in genomics and proteomics, lipidomics offers the opportunity to analyze the unique roles of specific lipids in complex cellular processes such as signaling and membrane trafficking. The yeast system offers many advantages for such studies, including the relative simplicity of its lipidome as compared to mammalian cells, the relatively high proportion of structural and regulatory genes of lipid metabolism which have been assigned and the excellent tools for molecular genetic analysis that yeast affords. The current state of application of lipidomic approaches in yeast and the advantages and disadvantages of yeast for such studies are discussed in this report.

Gene Expression Regulation, Fungal↗
PubMed2003

Expression screen by enzyme-linked immunofiltration assay designed for high-throughput purification of affinity-tagged proteins.

High-throughput purification of affinity-tagged fusion proteins is currently one of the fastest developing areas of molecular proteomics. A prerequisite for success in protein purification is sufficient soluble protein expression of the target protein in a heterologous host. Hence, a fast and quantitative evaluation of the soluble-protein levels in an expression system is one of the key steps in the entire process. Here we describe a high-throughput expression screen for affinity-tagged fusion proteins based on an enzyme linked immunofiltration assay (ELIFA). An aliquot of a crude Escherichia coli extract containing the analyte, an affinity-tagged protein, is adsorbed onto the membrane. Subsequent binding of specific antibodies followed by binding of a secondary antibody horseradish peroxidase (HRP) complex then allows quantitative evaluation of the analyte using tetramethylbenzidine as the substrate for HRP. The method is accurate and quantitative, as shown by comparison with results from western blotting and an enzymatic glutathione S-transferase (GST) assay. Furthermore, it is a far more rapid assay and less cumbersome than western blotting, lending itself more readily to high-throughput analysis. It can be used at the expression level (cell lysates) or during the subsequent purification steps to monitor yield of specific protein.

Blotting, Western↗
PubMed2026

PDZ-binding kinase promotes ovarian cancer cell proliferation and invasion via CCNB1 regulation.

BACKGROUND: Ovarian cancer is one of the most lethal gynecological malignancies, characterized by late diagnosis, frequent recurrence, and high mortality. PDZ-binding kinase (PBK), a serine/threonine kinase of the mitogen-activated protein kinase kinase (MAPKK) family, has been implicated in the tumorigenesis of multiple cancers, yet its role in ovarian cancer remains incompletely characterized. This study aimed to investigate the effect of PBK on the proliferation and invasion of ovarian cancer cells. METHODS: The expression of PBK and cyclin B1 (CCNB1) in normal ovarian tissues and ovarian cancer tissues was analyzed using online databases including Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Kaplan-Meier Plotter. Clinical tissue specimens were collected to detect the expression of PBK and CCNB1 by immunohistochemistry. Quantitative real-time polymerase chain reaction (PCR) was performed to detect PBK messenger RNA (mRNA) expression levels in clinical specimens and cell lines. Western blot was used to detect PBK protein expression in ovarian cancer cell lines. ES2 and A2780 cells with higher PBK expression were selected to construct PBK knockdown cell lines using lentiviral interference vectors. Cell Counting Kit-8 (CCK-8) assay, colony formation assay, and 5-ethynyl-2'-deoxyuridine (EdU) assay were performed to explore the effect of PBK knockdown on cell proliferation. Transwell assay was used to investigate the effect on cell invasion. The Cancer Genome Atlas (TCGA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized to analyze PBK-related pathways and predict CCNB1 as the gene most closely related to PBK. RESULTS: PBK was significantly overexpressed in ovarian cancer tissues and cell lines compared with normal controls, and high PBK expression was associated with poor overall survival (OS) and progression-free survival (PFS). Knockdown of PBK expression inhibited the proliferation, colony formation, and invasion of ovarian cancer cells. Bioinformatics analysis revealed that CCNB1 was significantly overexpressed in ovarian cancer and high CCNB1 expression was associated with poor OS. CCNB1 was also significantly highly expressed in ovarian cancer tissues as validated by immunohistochemistry and was associated with lymph node metastasis. PBK and CCNB1 expression showed a significant positive correlation in TCGA ovarian cancer datasets. Knockdown of PBK inhibited CCNB1 expression in ovarian cancer cells. CONCLUSIONS: PBK promotes ovarian cancer cell proliferation and invasion. PBK knockdown leads to CCNB1 downregulation. These findings suggest that CCNB1 contributes to PBK-mediated oncogenic effects and identify the PBK-CCNB1 axis as a potential therapeutic target for ovarian cancer treatment.

PDZ-binding kinase (PBK)↗
PubMed2006

Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics.

Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDS-PAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LC-MS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.

Mitochondrial Proteins↗
PubMed2002

The postgenomic age: characterization of proteomes.

Global analysis of biological systems is becoming increasingly feasible as technologies that facilitate genome-wide analyses of gene expression are developed. Proteomics is the global analysis of expressed proteins (including posttranslational modifications) and seeks to establish the relationship between genome sequence, expressed proteins, protein-protein interactions, and cell and tissue phenotype. While the relative abundance of transcripts can be quantified using gene expression microarrays, the identification and quantitation of expressed proteins is more challenging. Nevertheless, the potential payoff for global protein analyses is immense because identification of distinctive protein signatures associated with cell function may provide novel therapeutic targets, molecular markers of disease, and increased understanding of determinants of cell phenotype. The challenges and promises of applications of established and emerging proteome strategies to detect and quantify differentially expressed proteins in culture cells are discussed.

Animals↗
PubMed2006

A quantitative analysis of secondary RNA structure using domination based parameters on trees.

BACKGROUND: It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary RNA structures have frequently been represented by various modeling methods as graph-theoretic trees. Using graph theory as a modeling tool allows the vast resources of graphical invariants to be utilized to numerically identify secondary RNA motifs. The domination number of a graph is a graphical invariant that is sensitive to even a slight change in the structure of a tree. The invariants selected in this study are variations of the domination number of a graph. These graphical invariants are partitioned into two classes, and we define two parameters based on each of these classes. These parameters are calculated for all small order trees and a statistical analysis of the resulting data is conducted to determine if the values of these parameters can be utilized to identify which trees of orders seven and eight are RNA-like in structure. RESULTS: The statistical analysis shows that the domination based parameters correctly distinguish between the trees that represent native structures and those that are not likely candidates to represent RNA. Some of the trees previously identified as candidate structures are found to be "very" RNA like, while others are not, thereby refining the space of structures likely to be found as representing secondary RNA structure. CONCLUSION: Search algorithms are available that mine nucleotide sequence databases. However, the number of motifs identified can be quite large, making a further search for similar motif computationally difficult. Much of the work in the bioinformatics arena is toward the development of better algorithms to address the computational problem. This work, on the other hand, uses mathematical descriptors to more clearly characterize the RNA motifs and thereby reduce the corresponding search space. These preliminary findings demonstrate that graph-theoretic quantifiers utilized in fields such as computer network design hold significant promise as an added tool for genomics and proteomics.

Algorithms↗
PubMed2006

FCP: functional coverage of the proteome by structures.

MOTIVATION: Tools and resources for translating the remarkable growth witnessed in recent years in the number of protein structures determined experimentally into actual gain in the functional coverage of the proteome are becoming increasingly necessary. We introduce FCP, a publicly accessible web tool dedicated to analyzing the current state and trends of the population of structures within protein families. FCP offers both graphical and quantitative data on the degree of functional coverage of enzymes and nuclear receptors by existing structures, as well as on the bias observed in the distribution of structures along their respective functional classification schemes. AVAILABILITY: http://cgl.imim.es/fcp CONTACT: jmestres@imim.es.

Algorithms↗