Proteomics Glossary
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Proteomics Glossary
This is a partial glossary from from the GenomicGlossaries.com, Cambridge Heathcare Institute. Look down the list to find the word proteomics for the definition. Go to the GenomicGlossaries.com site for other information and definitions. Fascinating!
Proteomics Glossary
Evolving Terminology for Emerging Technologies
Suggestions? Revisions? Comments? Questions? mchitty@healthtech.com
Last revised February 14, 2005
Applications Map: Finding guide to terms in these glossaries Site Map
Related glossaries include Proteomics categories
Applications: Functional genomics, Metabolic engineering, Structural Genomics
Informatics Algorithms, In silico & Molecular Modeling, Information Management & Interpretation
Technologies: Chromatography & electrophoresis, Mass spectrometry, Microarrays & protein chips, NMR & x-ray crystallography
Biology: Expression, Proteins, Protein Structure
2D gel electrophoresis: A key technology for proteomics. Chromatography & electrophoresis glossary
allosteric ribozymes (allozymes): Pharmaceutical biology glossary Potential for use in proteomics.
annotation- proteins: The annotation of a protein sequence needs the following steps: protein classification into defined groups according to its homology to well characterized proteins, relevant literature is given by a link to Pub- Med, protein assignment into at least one functional category. Complete genome annotation, Munich Information Center for Protein Sequences MIPS, 2003 http://mips.gsf.de/projects/annotation
In SWISS- PROT, as in most other sequence databases, two classes of data can be distinguished: the core data and the annotation. For each sequence entry the core data consists of the sequence data, the citation information (bibliographical references), and the taxonomic data (description of the biological source of the protein), while the annotation consists of the description of the following items: Function(s) of the protein, Post- translational modification(s). For example carbohydrates, phosphorylation, acetylation, GPI- anchor, etc., Domains and sites. For example calcium binding regions, ATP- binding sites, zinc fingers, homeobox, kringle, etc., Secondary structure, Quaternary structure, Similarities to other proteins, Disease(s) associated with deficiencie(s) in the protein, Sequence conflicts, variants, etc. [Rolf Apweiler et. al " Protein Sequence Annotation in the Genome Era: The Annotation Concept of SWISS- PROT + TrEMBL" Intelligent Systems in Molecular Biology, 1997] http://www.ebi.ac.uk/swissprot/Publications/ismb97.html
Narrower terms: annotation- proteomes, functional annotation - proteome
annotation- proteomes: By working on an industrial scale with large samples of human tissues and biofluids, GeneProt is able to search effectively for novel, low- abundance proteins and peptides. The company's strategy of identifying and characterizing as many compounds as possible that are present in original samples is achieved through full integration of an efficient, customized LIMS; optimization of high- throughput data processing capacity; optimal use of proteomics data accessible through dedicated software; maximization of database storage capacity; and the intelligent use of data and information. "From Sample to Annotated Proteomes" Dr. Lydie Bougueleret, Chief Bioinformatician, GeneProt, Inc. Protein Informatics PepTalk Jan. 13- 14, 2003 San Diego CA
antibody arrays: Microarrays & protein chips categories for studying regulation at the protein level
bait: The basic format of the yeast-two hybrid system involves the creation of two hybrid molecules, one in which the "bait" protein is fused with a transcription factor, and one in which the "prey" protein is fused with a related transcription factor. If the bait and prey proteins indeed interact then the two factors fused to these two proteins are also brought into proximity with each other. As a result a specific signal is produced, indicating an interaction has taken place. [CHI Proteomics report]
binary interactions: It is important to realize that there is not a single, clear definition of a 'binary interaction'. In case of the MIPS protein complexes, the matrix representation, in which each complex is represented by the set of binary interactions corresponding to all pairs of proteins from the complex, is almost exclusively. used. For complex pull-down experiments, two different representations have been proposed: the matrix representation and the spoke representation in which only bait- prey interactions are included. Lars J. Jensen, Peer Bork, Quality analysis and integration of large- scale molecular data sets. Drug Discovery Today: Targets, 3(2): 51-56.
biological atlas: Maps, genomic & genetic glossary
cell expression profiles: Cell biology glossary
cell mapping: Maps genomic & genetic Can determine subcellular locations of proteins.
cellular pathways: Metabolic engineering See under metabolic engineering
cellular proteome: All of the proteins expressed in a cell.
chemical microarrays: Microarrays category Can be used for high throughput analysis of the interaction of proteins with organic compounds.
clinical proteomics: Molecular Medicine glossary
Google = about 435 Sept. 18, 2002
combinatorial peptide libraries: Combinatorial libraries & synthesis
contextual data: Information management & Interpretation
DNA protein interactions: See protein- DNA interactions
degradomics: -Omes & -omics glossary
Google = about 59 Sept. 18, 2002
designer proteins: Protein categories
Google = about 314 Sept. 18, 2002
differential labeling: Labeling, signaling & detection glossary Used for comparing the proteomes of different cell states.
directed protein evolution: We have developed an integrated program for the discovery and production of antibody mimetics that are screened for microarray applications. Using our proprietary directed protein evolution technology, PROfusion™, stable binding proteins are rapidly produced with high affinity and specificity for their target antigens. Automation of the PROfusion™ system, coupled with an automated E. coli- based protein expression system, has allowed for the high- throughput generation of binders at low cost. Dr. Richard W. Wagner, Research, Phylos, Inc. "Development of an Automated Directed Protein Evolution Engine to Produce High- Affinity Binders for Protein Microarrays Protein Arrays: Technology and Applications: PepTalk January 7- 8, 2002 San Diego CA
dissociator assays: A collective term for yeast- one hybrid, yeast- two hybrid or yeast- three hybrid assays.
domain: Protein structure glossary
evolutionary genomics, evolutionary homology: Phylogenomics glossary
Expressed Protein Tags EPTs: Multi- cellular organisms have been evolving a system with which they can discriminate between cells of their own origin and other adventitious cells or cells which have been infected with intracellular pathogens. To achieve this goal, a family of receptors, known as multi- ligand receptors (MLR), have evolved to be remarkably promiscuous binders of peptide ligands. The MLR- bound ligands are derived from degradation intermediates of cellular proteins. Typically, these ligands are 8-12 amino acids in length and have been coined by CANVAS as "expressed protein tags" or EPTs. EPTs are of sufficient length to differentiate particular proteins and/ or individual genes. Each MLR has a single binding site and thus contains a single EPT copy. [Canvas Informatics, Inc, "Technology" 2001] http://canvasw.vh.primushost.com/
Represent the collection of proteins which are present in a cell. [Robert G. Urban "Proteomics: Making sense of the census" Current Drug Discovery, Aug. 2001] http://www.current-drugs.com/CDD/CDD/CDDContents-August.htm
Related term: DNA glossary EST expressed sequence tags
Flex repository: FLEX (Full-Length Expression) will be a complete repository of full- length cDNA clones for the human and other model organisms. The fundamental goal of this repository is to enable high- throughput protein expression. To this end, the clones are all constructed using a recombination- based vector system so that hundreds or thousands of coding regions can be simultaneously transferred into any protein expression vector overnight. These transfers can be made mutation free into virtually any kind of expression vector allowing the broadest variety of experiments. [HIP Flex database, Harvard Institute of Proteomics, 200] http://134.174.168.120/YFlex/wall/overview.html
fragmentome: -Omes & -omics glossary
functional annotation - proteome: Advances in genome sequencing have created an immense opportunity to understand, describe, and model whole living organisms. Complete new genomes for various organisms are being published almost every month, and the Human Genome Project is now essentially completed. However, functional and structural characterization of newly sequenced proteins is still problematic. It is estimated that the function of a protein can only be identified about 50% of Sequence- based comparison methods alone can only identify function for about half of all proteins. Knowledge of a protein's structure often plays a crucial role in functional identification and characterization. We have focused on methods for extending the amount of information that can be extracted from the genome, thereby identifying new and unique potential targets for drug discovery. "High-Throughput Functional Annotation of the Proteome" Dr. David J. Edwards, Director, Computational Proteomics, Life Sciences, Accelrys, Inc. Functional Genomics: Genomics on target Nov. 18-21, 2002 Boston MA
functional genomic data - integration with proteomic: The availability of complete genome sequences suggests new approaches for biological research to complement conventional genetics and biochemistry. In this context, the goals of this laboratory are to generate a comprehensive protein- protein interaction map for C. elegans and develop new concepts to integrate this map with other functional maps such as expression profiles, global phenotypic analysis, and comprehensive localization- of- expression projects. The resulting "atlas" of integrated maps should be valuable for the development of a systems biology approach to the study of development. Integration of Functional Genomic and Proteomic Data Dr. Marc Vidal, Assistant Professor, Dana- Farber Cancer Institute Functional Genomics: Genomics on target Nov. 18-21, 2002 Boston MA
functional protein microarrays: Microarrays categories
functional proteomics: Proteomics categories
Google = about 3,160 Sept. 18, 2002
glycosylation: Proteins glossary
guilt by association: Expression glossary
HUPO: SEE Human Proteome Project
Hidden Markov Models HMM: In silico & Molecular modeling glossary
high-density protein arrays: Microarrays categories
high- throughput proteomics: Proteomics categories
homointeraction: A lot of proteins interact with themselves. [Dr. Jong Paik, Bioinformatics/ Proteomics, Dunn Human Nutrition Unit, Medical Research Council, UK, 2001] http://www.mrc-dunn.cam.ac.uk/research/bioinformatics_proteomics.html
homolog, homologue, homology: Functional Genomics
homology modelling: Structural genomics glossary
Human Plasma Proteome: See under Human Proteome
Human Proteome: Plotting the Course of Discovery from Diagnostics and Drug Evaluation to Treat Disease The Human Proteome: Plasma Proteomics, Jan. 12-13, 2005, San Diego CA
Human Proteome Organisation HUPO: The reason for creating HUPO is to assist in increasing the awareness of this discipline of science across society, particularly with regard to the Human Proteome Project and to engender a broader understanding of the importance of proteomics and the opportunities it offers in the diagnosis, prognosis and therapy of disease. As a global body it will also have the objective of fostering international cooperation across the proteomics community and of promoting scientific research in an on- going manner around the world.. HUPO Human Proteome Organisation website: http://www.hupo.org/
Human Proteomics Initiative: http://www.expasy.ch/sprot/hpi/ Swiss Institute of Bioinformatics' major project to annotate all known human sequences according to the quality standards of SWISS- PROT. This means providing, for each known protein, a wealth of information that include the description of its function, its domain structure, subcellular location, post- translational modifications, variants, similarities to other proteins, etc.
immunoproteomics: -Omes & -Omics glossary
interaction proteomics: Proteomics categories
Google = about 73 Sept. 18, 2002
interactome, interactomics: Omes & omics glossary
interologs: Protein interaction maps have provided insight into the relationships among the predicted proteins of model organisms for which a genome sequence is available. These maps have been useful in generating potential interaction networks, which have confirmed the existence of known complexes and pathways and have suggested the existence of new complexes and or crosstalk between previously unlinked pathways. However, the generation of such maps is costly and labor intensive. Here, we investigate the extent to which a protein interaction map generated in one species can be used to predict interactions in another species. [LR Matthews "Identification of potential interaction networks using sequence- based searches for conserved protein- protein interactions or "Interologs" Genome Research 11 (12): 2120- 2126, Dec. 2001]
Isotope Coded Infinity Tag ICAT: These tags provide the ability to both identify and quantify a broad range of proteins in a high- throughput mode. Using ICAT reagents, researchers can compare the expression levels of proteins from two samples, such as from normal and diseased cells. ICAT reagents comprise a protein reactive group, an affinity tag (biotin), and an isotopically labeled linker. [CHI Profiting from Proteomics: High-Throughput Expression, Functional Proteomics, Protein Chips, and Protein Informatics report, 2002
Related term: protein profiling
localization: SEE protein localization: Proteins glossary
localizome: Omes & omics glossary
localizome mapping: Maps, genomic & genetic glossary
microfluidics: Nanoscience & Miniaturization glossary
MudPIT Multidimensional Protein identification Technology: We will describe a largely unbiased method for rapid and large- scale proteome analysis via multidimensional liquid chromatography, tandem mass spectrometry, and database searching via the SEQUEST algorithm named multidimensional protein identification technology (MudPIT). The method has been applied to the analysis of yeast total cell lysates. Categorization of the proteins identified demonstrated this technology's ability to detect and identify proteins rarely seen in proteome analysis including integral membrane proteins from several cellular compartments and low abundance proteins like transcription factors and protein kinases. Of particular interest was our identification of 131 proteins with three or more predicted transmembrane domains. Dr. John Yates, Scripps Research Institute, "Large- Scale Analysis of Proteomes Using Mass Spectrometry" Proteomics June 21- 22, 2000, San Francisco, CA
Related term: Databases & Software Directory SEQUEST [software]
NHLBI Proteomics Initiative: Proteomics offers significant potential for addressing fundamental biological questions, as well as clinical applications. Thus, the National Heart, Lung, and Blood Institute recently funded 10 Proteomics Centers to enhance and develop innovative proteomic technologies and apply them to relevant biological questions in order to advance our knowledge of heart, lung, blood, and sleep health and disease. The goals of these 10 Centers will be presented. "NHLBI Proteomics Initiative to Develop and Apply Innovative Proteomics Technologies" Dr. Susan Old, National Heart, Lung, and Blood Institute Proteomics: Applications in Therapeutic and Diagnostic Development June 18- 19, 2003 | San Diego, CA
ORFeome: Omes & omics glossary
ontologies - proteomics: A principal aim of post- genomic biology is elucidating the structures, functions and biochemical properties of all gene products in a genome. However, to adequately comprehend such a large amount of information we need new descriptions of proteins that scale to the genomic level. In short, we need a unified ontology for proteomics. Much progress has been made towards this end, including a variety of approaches to systematic structural and functional classification and initial work towards developing standardized, unified descriptions for protein properties. In relation to function, there is a particularly great diversity of approaches, involving placing a protein in structured hierarchies or more- generalized networks and a recent approach based on circumscribing a protein's function through systematic enumeration of molecular interactions. N Lan, GT Montelione, M. Gerstein, Ontologies for proteomics: towards a systematic definition of structure and function that scales to the genome level, Current Opinion in Chemical Biology 7(1): 44- 54, Feb. 2003
PepTalk: Fourth Annual Protein Information Week Jan. 10- 13, 2004 San Diego, CA
peptide mapping, peptide maps: Maps, genomic & genetic
peptidomics: -Omes & -omics glossary
Google = about 180 Sept. 18, 2002; about 748 July 14, 2004
perturbagens: Peptides or protein fragments that, when expressed in cells, create desirable shifts in phenotype. These phenotypic probes ("perturbagens") can be used in turn to define their binding partners using a variant of yeast two- hybrid methodology. Drs. Jon Karpilow, Giordano Caponigro, Arcaris Inc. "Trans- FACS Analysis in Melanoma" CHI Gene Functional Analysis, Mar. 2-3, 2000, San Francisco CA
Used in physics to determine the effects of a number of variables upon a system.
phage display: Functional genomics glossary
phage display peptide libraries: Combinatorial libraries & synthesis
pharmacoproteomics: Pharmacogenomics glossary
Google = about 195 Sept. 18, 2002, about 488 July 14, 2004
Focused proteomic approaches through the use of a new type of protein array: the reverse phase protein microarray, has been developed and employed on laser capture microdissected cells procured from human cancer biopsy specimens. We are employing this array for multiplexed phospho- specific signal pathway profiling using clinical material of patients treated before, during and after molecular targeted therapeutic intervention trials. Unsupervised clustering analysis of and mathematic modeling of dozens to hundreds of phospho- specific signaling events can be can be achieved to identify signaling pathways that correlate with response to therapy and identify classes of patients who would most likely respond can performed using these arrays. "Phosphoproteome Portrait Analysis for Tailoring Therapy and Disease Prognosis", Dr. Emanuel Petricoin, Co- Director, Office of Cell, Tissue and Gene Therapies, FDA-NCI Clinical Proteomics Program, Bioinformatics and Genome Research: Beyond genome June 13- 14, 2005, San Francisco, California
Characterization of post- translational modifications in proteins is one of the major tasks that is to be accomplished in the post- genomic era. Phosphorylation is a key reversible modification that regulates enzymatic activity, subcellular localization, complex formation and degradation of proteins. DE Kalume et. al, Tackling the phosphoproteome: tools and strategies, Current Opinion in Chemical Biology 7(1): 64- 69, Feb. 2003
Ahn NG, Resing KA (2001) Toward the phosphoproteome. Nature Biotechnology 19:317- 19318
Google = about 88 Sept. 19, 2002; about 773 June 18, 2004; about 3,600 Feb. 14, 2005
phosphorylation: Proteins glossary
phylogenetic profiles: Phylogenomics glossary Can be used to hypothesize protein function.
plasma proteome: The proteins found in human plasma perform many important functions in the body. Having too much or too little of these proteins can thus cause disease directly, or reveal its presence. Plasma Proteome Institute, US http://www.plasmaproteome.org/plasmaframes.htm
Plotting the Course of Discovery from Diagnostics and Drug Evaluation to Treat Disease The Human Proteome: Plasma Proteomics, Jan. 12-13, 2005, San Diego CA
post-proteomics: Companies are taking position at the end stages of drug discovery in the hopes that industry- wide efforts in gene expression, protein expression, protein- protein interaction and other proteomic studies will yield many disease targets that must have their function verified. But to become a marketable solution for the industry, they must significantly increase the scale of functional experiments such as animal models and cell assays that, historically, have not been easily scaled. ["The Current State of Proteomic Technology" CHI's GenomeLink 3.1] http://www.healthtech.com/newsarticles/issue3_1.ASP
post- translational modification identification: ExPASy Proteomics Tools http://www.expasy.ch/tools/#ptm list a number of tools for prediction of post- translational modification, as do other websites. Identification of these modifications may provide important structural- functional information.
post-translational modifications: Proteins glossary
prey: See under yeast two hybrid
Profusion technology: Enables one to link messenger RNA (mRNA) to the protein that it encodes. The significance of this is the ability to use advanced nucleic acid- based technologies to access protein, or alternatively to use protein selection methods to access the gene. .. Because the bond between the gene product and the protein product is covalent, it is very robust and can be purified under a wide variety of conditions. [CHI Summit Proteomics report]
protein: Proteins glossary
protein activity: Unraveling the mystery of protein activity is one of the largest challenges in scientific research and a key driver in the development of tools that enable the quick identification of high- quality targets. Current proteomics technologies can only identify already known proteins or proteins predicted from genomic data. Dr. Matthias Mann, MDS Proteomics, "Proteomics Technology for Easier Mining of Novel Genes and Expressed Proteins" Proteomics Europe: Proteins to Profits March 25- 27, 2002, Munich, Germany
protein analysis: The characterization of proteins based on various relevant parameters such as purity, charge, mass, isoelectric point, reactivity, degree of post- translational modification, abundance, stability, amino acid composition, and amino acid sequence. It has grown from the characterization of structure and function of individual purified proteins to the simultaneous characterization of multiple proteins from a single sample of a complex mixture of proteins. This explosion of Protein Analysis capabilities is generally referred to as Proteomics. Indiana Centers for Applied Protein Sciences INCAPS, Protein Analysis & Proteomics http://indianacaps.com/protein/
protein and mRNA data: Although the relationship between mRNA and protein levels is vague for individual genes, some of the statistics for broad categories of protein properties are much more robust... In contrast to the differences between mRNA and protein data for individual genes, the broad categories show that the transcriptome and translatome populations are remarkably similar; both contain roughly the same proportions of secondary structure and functional categories. Moreover, this contrasts the difference with the genome, which appears to have a distinctly different composition of functional categories. This illustrates that we get a more consistent picture when we average across the population, i.e. there is broad similarity between the characteristics of highly expressed mRNA and highly abundant proteins. [Dov Greenbaum, Mark Gerstein et. al. "Interrelating Different Types of Genomic Data" Dept. of Biochemistry and Molecular Biology, Yale Univ. 2001] http://bioinfo.mbb.yale.edu/e-print/omes-genomeres/text.pdf
Related terms: Expression glossary; Genomics glossary genome data; functional genomics data Omes & omics transcriptome, translatome
protein annotation - dictionary-driven For many years, computational methods seeking to automatically determine the properties (functional, structural, physiochemical, etc.) of a protein directly from sequence have been the focus of numerous research groups, including ours. By general admission, this is a difficult problem and the methods that have been proposed over the years typically concentrated on the analysis of individual genes. With the advent of advanced sequencing methods and systems, the number of amino acid sequences and fragments being deposited in the public databases has been increasing steadily. This in turn generated a renewed demand for automated approaches that can quickly, exhaustively and objectively annotate individual sequences as well as complete genomes. In this paper, we present one such approach. The approach is centered around and exploits the Bio- Dictionary, an exhaustive collection of amino acid patterns (referred to as seqlets) that completely covers the natural sequence space of proteins to the extent that this space is sampled by the currently available public databases. Isidore Rigoutsos, Tien Huynh, Laxmi P. Parida, Daniel E. Platt, Aris Floratos, Dictionary Driven Protein Annotation, Nucleic Acids Research, 30 (no 17) 3901- 3916, 2002
protein arrays: Microarrays & protein chips glossary
Google = about 2,050 Sept. 18, 2002; about 10,200 July 14, 2004
protein biomarkers: Biomarkers glossary
protein- carbohydrate interactions: The overarching goal of the [Consortium for Functional Glycomics] program is to: Define paradigms by which protein-carbohydrate interactions mediate cell communication. Consortium for Functional Glycomics, funded by NIGMS, US http://web.mit.edu/glycomics/consortium/organization/program/program.shtml
protein chips: Microarrays & protein chips glossary
Google = about 2,450 Sept. 18, 2002; about 7.450 July 14, 2004
protein complexes: To date scientists have studied proteins largely as discrete entities, yet most proteins operate collectively as part of protein complexes or pathways. A deeper understanding of protein interactions will assist in validating novel drug targets and may extend the usefulness of existing drug targets. At Cellzome we have implemented a high- throughput use of Tandem Affinity Purification (TAP) for effective isolation of complexes involved in human disease that is very robust, and is providing novel insights into cellular pathways. Dr. Walter Blackstock, Cellzome UK, "The Large- scale Study of Protein Complexes for Target Validation" Proteomics Europe: Proteins to Profits March 25- 27, 2002, Munich, Germany
Google = about 23,900 Sept. 18, 2002; about 151,000 July 14, 2004
Related terms: complexome: -Omes & -omics glossary; Metabolic engineering glossary
protein-DNA interactions: Can be detected by DNA footprinting, gel shift analysis, yeast one hybrid assays or Southwestern blots. John A Wagner "The logic of molecular approaches to biological problems" Cornell University Medical College http://www-users.med.cornell.edu/~jawagne/logic_&_experimental_desig.html
Can also be analyzed by genetic analysis and X-ray crystallography. [John Little Biochemistry Fall 2000, University of Arizona]
Related terms: Proteomics categories interaction proteomics
protein databases: Protein location can be determined by such genome- wide techniques as green fluorescent protein (GFP) tagging, and protein- protein interactions can be determined by affinity chromatography, immunoprecipitation and yeast two- hybrid experiments. Databases resulting from these methods are beginning to emerge, but they are of uncertain accuracy. Defining the Mandate of Proteomics in the Post- Genomics Era, Board on International Scientific Organizations, National Academy of Sciences, 2002 http://www.nap.edu/books/NI000479/html/R1.html
Dr. Stanley Fields, Professor of Genetics and Medicine at the Univ. of Washington and developer of the yeast two hybrid system writes that protein databases "will need to become much more sophisticated if they are to help scientists make sense of the staggering number of experimental measurements that will soon emerge. ... protein data will need to be integrated with results from expression profiling, genome- wide mutation or antisense analyses, and polymorphism detection. As proteomic data accumulate, we will become better at triangulating from multiple disparate bits of information to gain a bearing on what a protein does in the cell. [S. Fields "Proteomics in Genomeland" Science 291: 1221-1224 Feb. 16, 2001]
Related terms: protein identification, protein localization; Expression glossary expression profiling
Protein databases Databases & software directory
protein dynamics: Certain parts of a particular protein will be rigid, but others may be flexible and change their shape, even when bound. ... NMR has the unique ability to characterize protein fluctuations quantitatively, much more so than crystallography can. [CHI Structural proteomics report]
Understanding the function of a protein is fundamental for gaining insight into many biological processes. Proteins are stable mechanical constructs that allow certain internal motions to enable their biological function. Structural properties of a protein can be obtained with X-ray crystallography or NMR acquisition techniques. Molecular dynamics (MD) simulations at pico/ nano- second time scales output one or more trajectory files which describe the coordinates of each individual atom over time. The main problem with animating these trajectories is one of temporal scale. Taking large time steps will destroy the impression of smooth motion, while small time steps will result in the camouflage of interesting motions. [Henk Huitema, Robert van Liere " Interactive Visualization of Protein Dynamics" ERCIM [European Research Consortium for Computers and Informatics] News No. 44 - January 2001] http://www.ercim.org/publication/Ercim_News/enw44/van_liere.html
Google = about 5,800 Sept. 18, 2002; about 18,200 July 14, 2004
protein expression: Is variable, not all encoded proteins are expressed at all times. More ... Expression glossary
Google = about 68,000 Sept. 18, 2002; about 544,000 July 14, 2004
protein expression mapping: Maps, genetic & genomic glossary
protein expression profiling: Expression glossary
protein folding simulations: Atomistic simulations of protein folding starting purely from sequence have been a major goal of computational biology. One great challenge associated with protein folding simulation is the relatively long time scales (tens to hundreds of microseconds) compared with typical atomistic simulation time scales (nanoseconds). Using novel algorithms and a cluster of over 40,000 computer processors ("Folding@Home" http://folding.stanford.edu), we have simulated over a millisecond of atomistic molecular dynamics simulation- several orders of magnitude greater than the previous state of the art. For the first time, we have used molecular dynamics to fold proteins and, moreover, to predict protein folding rates. These predictions of protein structure and rates compare well with recent experiments. We conclude with novel applications of this methodology and delineation of its limitations. "Atomistic Simulations of Protein Folding on the Tens of Microsecond Time Scale: Using Worldwide Distributed Computing to Bridge the Gap between Simulation and Experiment" Dr. Vijay Pande, Assistant Professor of Chemistry and, by courtesy, of Structural Biology, Stanford University Strategic Biocomputing track Molecular Medicine Marketplace, Mar. 20-21, 2003 , Santa Clara CA
protein folding disorders: Molecular medicine glossary
protein function: Function is not a fixed property for many, if not most proteins. There are many ways that gene products can be altered to elicit modified or completely new functions. For example there are exist - alternative splicing - which may affect as many as ¼ or more of the genes in a higher eukaryote and can alter biochemical function either drastically or subtly, producing truncated proteins and proteins with different compositions - post- translational modification, such as phosphorylation and glycosidation (which can occur on numerous sites on the same protein) - pre-enzymes made for secretion and pro- enzymes that are activated by cleavage - acylation and ubiquitination - non- enzymatic modifications like oxidation, so a given protein exists in the cell in different oxidized states. Defining the Mandate of Proteomics in the Post- Genomics Era, Board on International Scientific Organizations, National Academy of Sciences, 2002 http://www.nap.edu/books/NI000479/html/R1.html
More systematic attempts have been made to place proteins within a hierarchy of standard functional categories or to connect them in overlapping networks of varying types of associations. These networks can obviously include protein- protein interactions ... More broadly, they can include pathways, regulatory systems and signaling cascades... Perhaps, in the future, the systematic combination of networks may provide for a truly rigorous definition of protein function. [Mark Gerstein, et. al "Integrating Interactomes" Science 295 (5553): 284, Jan. 2002]
A biologically useful definition of the function of a protein requires a description at several different levels. To the biochemist, function means the biochemical role of an individual protein: if it is an enzyme, function refers to the reaction catalyzed; if it is a signaling protein, function refers to the interactions that the protein makes. To the geneticist or cell biologist, function includes these roles but will also encompass the cellular roles of the protein, such as the phenotype of its deletion, the pathway in which it operates, among others. A physiologist or developmental biologist may have an even broader view of function, including tissue specificity and expression during the life cycle of the organism. [Gregory A Petsko, Dagmar Ringe "Overview: The Structural Basis of Protein Function" from Chapter 2 of Protein Structure and Function: New Science Press, 1991-2001] http://www.biomedcentral.com/nspprimers/proteinfunction/full
In the expanded view of protein function, a protein is defined as an element in the network of its interactions. Various terms have been coined for this expanded notion of function, such as ‘contextual function’ or ‘cellular function’ … Whatever the term, the idea is that each protein in living matter functions as part of an extended web of interacting molecules … Often it is possible to understand the cellular functions of uncharacterized proteins through their linkages to characterized proteins. In broader terms, the networks of linkages offer a new view of the meaning of protein function, and in time should offer a deepened understanding of the function of cells. [David Eisenberg et al "Protein function in the post- genomic era" Nature 405: 823- 826, 15 June 2000]
The principal problem facing the post- genome era. [Walter Blackstock & Malcolm Weir "Proteomics" Trends in Biotechnology: 121-134 Mar 1999]
Google = about 27,400 Sept. 18, 2002 about 58,400 Aug. 18, 2003, about 133,000 July 14, 2004
Related terms: Protein categories interaction proteomics; Functional genomics glossary gene function, Gene OntologyTM ; Maps cell mapping
protein identification: The analytical method used most commonly to visualize and identify large numbers of proteins is 2D-gel electrophoresis. One can theoretically visualize changes in protein production, both qualitatively and quantitatively, from two individual samples (e.g., a control preparation and a treated preparation). Furthermore, one can potentially accomplish protein identification by "picking" proteins from the 2D- gel and subjecting the highly purified protein to MALDI- TOF mass spectrometry. ["High - Throughput Genomics, CHI Genome Link 14.1] http://www.healthtech.com/newsarticles/issue14_1.asp
Google = about 8,460 Sept. 18, 2002 about 15,000 Aug. 18, 2003, about 32,000 July 14, 2004
Related term: protein databases
protein informatics: The fragmentation of data over many databases with differing structures and locations increases the need for easier access to the data to allow users the concurrent exploitation of different information resources. Essential here are improvements in the standardization and integration of data. Examples of promising approaches with a potentially huge impact on proteomics are the UniProt, InterPro, and Integr8 projects as well as the Proteomics Standards Initiative. All these efforts are steps necessary on the bioinformatics side to accelerate the delivery of the goods scientists expect from genomics and proteomics. "Integration and Standardization: Driving Forces in Protein Informatics" Dr. Rolf Apweiler, EMBL Outstation, European Bioinformatics Institute . Proteomics: Applications in Therapeutic and Diagnostic Development June 18- 19, 2003 | San Diego, CA
The Protein Informatics Group currently consists of ten scientists with highly diversified training background, ranging from biochemistry, computational chemistry, biophysics, physics to computer science, statistics and mathematics. Our common interests are in development of computational tools for solving problems from molecular biology. Our work ranges from construction of mathematical/ statistical models to development of algorithms to code implementation on various platforms to applications of computational tools to solve various bio- data analysis problems. Our current R&D activities focus on the following four areas: Protein Structure Prediction and Modeling... Hybrid Methods for Protein Structure Determination ... Gene Expression Data Analysis and Biological Pathway Construction. [Protein Informatics Group, Computational Biology, Oak Ridge National Lab, US] http://grail.lsd.ornl.gov/protein_group/
Although mining of protein structure homology data is a relatively small field now, it is likely to experience dramatic growth and to become pivotal in the ultimate exploitation of genomic data and tools. [CHI Target Validation report]
Google = about 561 Sept. 18, 2002, about 888 Aug. 18, 2003, about 1,810 July 14, 2004
Related terms: proteoinformatics; Algorithms glossary; Bioinformatics glossary protein bioinformatics; In Silico & molecular modeling glossary, Structural genomics glossary
protein interactions: It is estimated that 40% of drugs on the market were originally conceived for other indications. Whether or not this figure is precise, our experimental evidence suggests that proteins rarely function in isolation, but are part of complex networks of interacting proteins. The action of a drug on a target may therefore have unforeseen effects. Cellzome has developed technology to rapidly define complex interactions, expand signalling pathways and map drugs to protein networks with a new level of precision, that will explain secondary indications and adverse toxicity. "Connecting Drug, Target and Network" Dr. Walter Blackstock, Cellzome AG Human Proteome Project: PepTalk Jan. 15-16, 2003 San Diego CA
Google = about 59,900 Sept. 18, 2002; about 141,000 Aug. 18, 2003, about 271,000 July 14, 2004
Narrower terms: annotation- proteins, binary interaction, interaction proteomics, protein- DNA interactions, protein- protein interactions, protein- RNA interactions; Related terms: protein networks; -Omes & -omics glossary interactome
protein interaction mapping: Maps genomic & genetic
protein knockouts: Genetic manipulation & disruption
Google = about 63, July 14, 2004
protein linkage maps: Maps genomic & genetic
protein localization: Proteins glossary
protein microarrays: Microarrays & protein chips glossary
Google = about 1,410 Sept. 18, 2002; about 4,380 Aug. 18, 2003' about 11,000 July 14, 2004
protein networks: To better describe the molecular context of identified targets, high- throughput data from differential display proteomics analyses are mapped onto "protein networks" that are based on biological complexes or pathways. This approach helps to understand the underlying complexity and facilitates the progression of disease- relevant proteins in the drug discovery process. "Integrating Proteomics Data for Target Validation" Dr. Eva Jung, Drug Innovation & Approval Informatics, Aventis Pharma Protein Informatics PepTalk Jan. 13- 14, 2003 San Diego CA
Google = about 1,160 Sept. 18, 2002; about 2,530 Aug. 18, 2003; about 6,170 July 14, 2004
Related term: protein interactions
protein profiling: Expression glossary
Google = about 1,290 Sept. 18, 2002; about 2,820 Aug. 18, 2003, about 6,700 July 14, 2004
protein- protein interactions: A central phenomenon determining the biological pathways found in living systems. They are the focus of many proteomic technologies being developed today to decipher an intricate network of interactions. [CHI Summit Proteomics report]
As the level of general knowledge of proteins and protein interaction networks advances, the common understanding of a PPI [protein- protein interaction] becomes complex. It is currently possible to define this term in a number of different ways ... At the simplest level, two discrete proteins A and B physically associate with each other in a stable complex ... Alternatively, two associating proteins might retain unaltered individual functions ... Another possibility is that a PPI may result in a loss of activity, or destruction for component A or B, or both ... Alternatively, an interaction may serve a regulatory function ... Alternatively, the interaction of A+ B may exclude A or B from interaction with another potential partner molecule. [Erica A. Golemis, Kenneth D. Tew, Disha Dadke "Protein Interaction - Targeted Drug Discovery" Biotechniques 32 (3): 636- 647, 2002]
Can be detected by yeast two- hybrids, phage display or immunoprecipitation assays. [John A Wagner "The logic of molecular approaches to biological problems" Cornell University Medical College] http://www-users.med.cornell.edu/~jawagne/logic_&_experimental_desig.html
Correlated changes in protein expression (such as co- regulation or sequential regulation) provide a hint that two proteins may be interacting with each other. [CHI Proteomics report]
Play a major role in almost all relevant physiological processes occurring in living organisms, including DNA replication and transcription, RNA splicing, protein biosynthesis, and signal transduction.
Related terms: interaction proteomics, yeast two-hybrid.
Protein interaction databases Databases & software directory.
protein-protein interaction inhibitors: See under Proteomics categories functional proteomics
protein-RNA interactions: Can be detected by the yeast three- hybrid assay. [John A Wagner "The logic of molecular approaches to biological problems" Cornell University Medical College] http://www-users.med.cornell.edu/~jawagne/logic_&_experimental_desig.html
Involved in gene expression and protein synthesis.
Related terms: interaction proteomics; Omes & omics glossary riboproteomics; Cell biology glossary ribosome
protein small molecule interactions: At Ambit, we have developed a highly parallel method to find the unknown protein targets of biologically active small molecules and peptides. The ProteomeScan technology is versatile, general, scalable, and quantitative. The approach is being used to discover proteins that bind to drugs with unknown mechanisms of action, to identify off- target interactions that may be important for side effects, to assess the specificity of lead compounds, and to screen for new molecules that compete with known or newly identified interactions. "Chemistry- Directed Discovery of Protein- Small Molecule Interactions" Dr. David J. Lockhart, Ambit Biosciences Genomic Drug Discovery Molecular Medicine Marketplace, Mar. 17-19, 2003 , Santa Clara CA
Related term: proteomimetics - small molecule
protein therapeutics: Molecular Medicine glossary
proteoinformatics: The sequencing of the human genome has provided the sequence blueprint of all human proteins and has spawned the field of proteomics. Advanced instrumentation has been developed to rapidly, and with great sensitivity, acquire mass spectral data for searching databases. Lacking in these developments, however, are sophisticated software algorithms to enable the automated interrogation and processing of mass spectral data. Informatics plays a critical and central role to achieve and maintain a successful proteomics effort. Similar to genomic platforms, current proteomics platforms yield a vast amount of data, and therefore it is important to develop intelligent data analysis tools to manage, correlate, and compare disparate data sets to draw biological and biochemical relationships that will aid in drug discovery and development. This presentation will focus on informatic tools designed and developed by the proteomics/bioinformatics groups at BMS to aid and enhance drug target and biomarker discovery efforts. "ProteoInformatics Tools in Drug Target and Biomarker Discovery" Dr. Ashok R. Dongre, Clinical Discovery, Bristol- Myers Squibb PRI Protein Informatics PepTalk Jan. 13- 14, 2003 San Diego CA
Google = about 11 Sept. 18, 2002; about 48 Aug, 18, 2003; about 244 July 14, 2004
Related term: protein informatics
proteome: The scope note for the Journal of Proteome Research (Jan.2002) states that "primary topics will include: New approaches to sample preparation, including 2- D gels and chromatographic techniques, Advancements in high- throughput protein identification and analysis, Array- based measurements, Structural genomics data related to protein function, Research on quantitative and structural analysis of proteins and their post- translational modifications, Metabolic and signal pathway analysis, including metabolomics and peptidomics, Protein- protein, protein- DNA, and protein- small molecule interactions, Computational approaches to predict protein function, Use of Bioinformatics/ Cheminformatics to mine and analyze data, New tools in proteomic analysis, Studies on proteomics with an impact on the understanding of disease, diagnosis and medicine. http://pubs.acs.org/journals/jprobs/
The dynamic nature of the proteome calls for methods to monitor, for any organism, the entire proteome's conditional state accurately and sensitively from thousands of samples. This will require greater completeness, resolution, and sensitivity than has been possible in the past using conventional imaging and gel-based technologies. Also, new tools characterizing these complexes must be developed to bridge the current size and resolution gap between single proteins suitable for high-resolution X-ray crystallographic study and the very large protein assemblies and cellular ultrastructures amenable to electron microscopy.
The importance of post- transcriptional and post- translational regulation is recognized by placing emphasis on direct knowledge of proteins and their higher- order associations in contrast to less direct inferences about proteome composition drawn from RNA measurements. Molecular Machines of Life, DOE Genomes to Life, US http://www.doegenomestolife.org/program/goal1.html
Comprehensive quantitative data on the proteins of an organism under a variety of conditions (ideally including post synthetic modifications and interactions with other molecules). To achieve this, purification each protein (including modified versions and interacting antibodies) will be an important related project George Church Lab, Harvard- Lipper Center for Computational Genomics, 2001 http://arep.med.harvard.edu/
The concept of the proteome is fundamentally different to that of the genome: while the genome is virtually static and can be well defined for an organism, the proteome continually changes in response to external and internal events. Marc Wilkins and Denis Hockstrasser "Thinking Big Proteome Studies in a Post- Genome Era" ABRF News Dec 1996 http://www.abrf.org/ABRFNews/1996/December1996/Proteome.html
Marc Wilkins is credited with coining the word in 1994 at the Conference on Genome and Protein Maps in Siena, Italy. PROTEin complement expressed by a genOME. Wilkins et al "Progress with gene product mapping of the Mollicutes" Electrophoresis 16:1090-1094, July 1995
Proteome Society: http://www.proteome.org/ Proteome Society glossary http://www.proteome.org/4Resources/glossary.htm
Google = about 83,500 Sept. 18, 2002; about 159,000 Aug. 18, 2003, about 268,000 July 14, 2004
Broader terms: Genomics glossary genome; -Omes & -omics glossary ORFeome
Related terms: -Omes & -omics glossary translatome. See translatome for a discussion of the ambiguities in competing definitions of proteome.
proteome chip: Microarrays & protein chips glossary
Google = about 76 Sept. 18, 2002; about 120 Aug. 18, 2003, about 208 July 14, 2004
proteome database mining: the identification of intrinsic patterns and relationships in translational expression data generated by large- scale proteomics experiments. Improvements in genome, gene expression and proteome database mining algorithms will enable the prediction of protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. Thus, the final objective of such higher- level functional analysis will be the elucidation of high- resolution structural and functional maps of the human genome. [John L. Houle et. al., White Paper: Database Mining in the Human Genome Initiative, AMITA Corp. 2000] http://www.biodatabases.com/whitepaper01.html
Related terms: proteome mining; Expression glossary gene expression database mining; Genomics glossary: genome database mining Narrower terms: cellular proteome, HUPO Human Proteome Organization, proteome chip, proteome informatics, proteome map, whole proteome
proteome informatics: Peer Bork and David Eisenberg, "Genome and proteome informatics" Current Opinion in Structural Biology 10 (3): 341-342, 2000
Proteome Informatics group is part of the Swiss Institute of Bioinformatics (SIB). It is in charge of research and development in the fields of bioinformatics, molecular imaging and the use of Internet for biomedical applications. [ExPASy, Swiss Institute of Bioinformatics] http://www.expasy.ch/people/PI_group.html
Google = about 261 Sept. 18, 2002; about 453 Aug. 18, 2003; about 708 July 14, 2004
proteome map: Maps, genomic & genetic glossary
Google = about 149 Sept. 18, 2002; about 319 Aug. 18, 2003; about 746 June 21, 2004
proteome mining: Timothy AJ Haystead "Proteome Mining: Exploiting serendipity in drug discovery" Current Drug Discovery, March 2001] http://www.current-drugs.com/CDD/CDD/CDDPDF/HAYSTEAD.pdf
Google = about 68 Sept. 18, 2002; about 156 Aug. 18, 2003; about 276 June 21, 2004
Related term: proteome database mining:
proteomic analysis: Systematic and quantitative analysis of the properties that define protein activity and functions within a defined context, essential for biology and medicine. Ruedi Aebersold quoted in Defining the Mandate of Proteomics in the Post- Genomics Era, National Academies Press, 2002 http://www.nap.edu/books/NI000479/html/R1.html
A systematic analysis of proteins for their identify quantity and function. J Peng and Steven Gygi, Proteomics: the move to mixtures, Journal of Mass Spectrometry 35: 1083- 1091, 2001 http://www.spectroscopynow.com/Spy/pdfs/jms361083.pdf
proteomic analysis - cells and tissue: Cell biology glossary
proteomic diversity: Alternative RNA splicing generates extreme proteomic diversity in the mammalian nervous system, where hundreds of thousands of distinct proteins are generated from approximately 30,000 genes. These protein counterparts play important roles in learning and memory, cell communication, and neural development. [Paula Grabowski, Dept. of Biological Sciences, Univ. of Pittsburgh, US, 2001] http://www.pitt.edu/AFShome/b/i/biohome/public/html/Dept/Frame/Faculty/...
Related term: RNA glossary alternative RNA splicing
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