"Proteins are central to our understanding of cellular function and disease processes, and without a concerted effort in proteomics, the fruits of genomics will go unrealized." Nature 409, 747 (2001)
Now that the human genome has been sequenced, we face the greater challenge of making use of this information for improving healthcare and discovering new drugs. There is an increasing interest in proteomics technologies now because DNA sequence information provides only a static snapshot of the various ways in which the cell might use its proteins whereas the life of the cell is a dynamic process. With this background, DNA/RNA (ribonucleic acid) sequences, per se, are not enough for the clear identification of a therapeutic target because proteins and not DNA/RNA are the basis of mode of action of drugs. Structural genomics is the determination of structure of proteins, RNA and other biological macromolecules. Functional genomics is an ambitious attempt at high-throughput basic research through the integration of multiple automated technologies including RNA profiling, proteomics, genetics of animal models, assays, structural biology and bioinformatics. Parallel to these developments, there is an interest in functional proteomics - study of function of proteins.
What is proteome & proteomics?
‘PROTEOME is the PROTEINS expressed by a genome or a tissue’ (Wasinger et al. 1995)
The proteome has been defined as the entire complement of proteins expressed by a cell, organism, or tissue type, and accordingly, proteomics is the study of this complement expressed at a given time or under certain environmental conditions.
Proteomics represents the genome at work and is a dynamic process.
Proteomics can be divided into expression proteomics, the study of global changes in protein expression, and cell-map proteomics, the systematic study of protein-protein interactions through the isolation of protein complexes (Blackstock and Weir 1999). Proteins expressed by an organism change during growth, disease, and the death of cells and tissues. Modifications of proteins that occur during and after their synthesis, such as the attachment of sugarresidues or lipids, change the proteome complement. The minimum proteome size can be calculated from the size and 2-D polyacrylamide gel electrophoresis (2-D PAGE) separated proteins. Proteomics is based on leading edge technological capability for.undertaking the mass screening of proteins and their post-translational modifications in whole organisms as well as in their tissues in normal and diseased states.
There are three main steps in proteome research:
§ Separation of individual proteins by 2-D polyacrylamide gel electrophoresis (2-D PAGE).
§ Identification by mass spectrometry or N-terminal sequencing of individual proteins recovered from the gel.
§ Storage, manipulation, and comparison of the data using bioinformatics.
Some scientists do not like the term proteomics and continue to use terms describing various technologies for proteins such as protein separation, etc. However, there is a distinction to be made between the molecular function of an isolated protein and the function of that protein in the complex cellular environment as studied by proteomic technologies. Proteomics attempts to catalog and characterize these proteins, compare variations in their expression levels in health and disease, study their interactions, and identify their functional roles. Proteomics is not the study of individual proteins as has been done traditionally, but rather in an automated, large-scale manner which requires new technologies and considerable effort is currently being devoted to the development of novel tools.
Proteomics will contribute greatly to our understanding of gene function in the post-genomic era. Differential display proteomics for comparison of protein levels has potential application in a wide range of diseases Because it is often difficult to predict the function of a protein based on homology to other proteins or even their three-dimensional structure, determination of components of a protein complex or of a cellular structure is central in functional analysis. This aspect of proteomic studies is perhaps the area of greatest promise (Pandey and Mann 2000). After the revolution in molecular biology exemplified by the ease of cloning by DNA methods, proteomics will add to our understanding of the biochemistry of proteins, processes and pathways for years to come.
Proteomics will also play an important role for drug discovery and development (Müllner et al 1998). Proteomics is the link between genes, proteins and disease. Many of the best-selling drugs either act by targeting proteins or are proteins. In addition, many molecular markers of disease, the basis of diagnostics, are proteins Patterns of protein expression can be used as a guide to drug design. Application of proteomics to study underlying pharmaceutical mechanisms and use these for drug development is referred to as pharmaceutical proteomics. Unlike classical genomic approaches that discover genes related to a disease, proteomics could characterize the disease process directly by finding sets of proteins (pathways or clusters) that together participate in causing it. The same technology is used to study the effects of candidate drugs intended to reverse a disease process.
Landmarks in the evolution of proteomics
1860 Friedrich Miescher identified acid and basic protein components in cell nuclei which was mistakenly believed to carry the genetic material
1940 Beadle and Tatum linked genes to unique protein products and formulated the one gene - one protein concept that has now been revised as one gene codes more than one protein.
1953 Identification of the double-stranded structure of the DNA (Watson and Crick )
1956 Separation of proteins with a combination of paper and starch gel two-dimensional electrophoresis (Smithies and Poulik )
1961 Modern concept of gene expression following discovery of messenger RNA, deciphering of genetic code and description of theory of genetic regulatio n of protein synthesis.
1967 Protein sequencing defined and automated (Edman and Begg )
1970 Isoelectric focusing and gradient gel electrophoresis: a two -dimensional technique (Kenrick and Margolis )
1972 The Protein Data Bank with a collection of ten X-ray crystallographic protein structures (Bernstein et al )
1975 The modern form of two -dimensional electrophoresis of proteins by high resolution separation (O‘Farrell )
1981 Use of 2-D polyacrylamide gel electrophoresis (2-D PAGE) as the core methodology for pharmaceutical and toxicological studies (Anderson )
1982 The concept of mapping the human proteome was put forward (Anderson)
1986 Coined the word "Genomics" by Roderick as title of the journal, which started publication in 1987 (Kuska ).
1986 Creation of the first protein-sequence database -- SWISS-PROT -- at University of Geneva, Switzerland
1987 Formation of the first proteomics company - Large Scale Biology Corporation
1995 Definition of the proteome (Wilkins)
1997 Publication of the first book on proteomics (Wilkins et al )
1999 The first Chair in Proteomics created at the Universiteit Utrecht, The Netherlands. Occupant is Prof. Ian Humphery-Smith.
2000 March Publication of the most complete proteome of a whole organism, the bacterium Mycoplasma genitalium
2001 Sequencing of the human genome completed.
Proteomics – in the post-genomics era
Protein identification:
One-dimensional gels (for example, analysis after affinity purification)
Two-dimensional gels (for example, analysis after affinity purification, body fluids, etc.)
Protein chips (chips coated with, for example, proteins or antibodies)
Proteins/protein complexes in solution (identification without electrophoresis)
Post-translational modifications
Phosphorylation
Glycosylation
Determining Function
Assays for enzymatic activity or determining substrates
Bioassays for cytokines, receptor/ligand-binding assays
Localization within the cells (GFP fusions)
Proteomic analysis using large-scale mouse knockouts or RNA interference.
Phenotypic analysis using deletion strains
Molecular Medicine (no longer just pharmaceuticals)
Finding molecular (protein) drug targets
Disrupting protein–protein interactions using drugs
Large-scale animal assays for recombinant proteins, antibodies and inhibitors
Differential display by two-dimensional gels (superseded by DNA-based array in many situations)
Limited applications in:
Body fluids (for example, serum and urine)
Variants resulting from post-translational modifications
A Description of the Methodology
Prototype core facility for proteome analysis.
Most commonly used technologies are 2-D gel electrophoresis for protein separation and analysis of proteins by mass spectrometry. Microanalytical protein characterization with multidimentional liquid chromatography/mass spectrometry improves the throughput and reliability of peptide mapping. Matrix-Assisted Laser Desorption Mass Spectrometry (MALDI-MS) has become a widely used method for determination of biomolecules including peptides, proteins. Functional proteomics technologies include yeast two-hybrid system for studying protein- protein interactions. Establishing a proteomics platform in the industrial setting initially requires implementation of a series of robotic systems to allow a high-throughput approach for analysis and identification of differences observed on 2-D electrophoresis gels. Protein chips are also proving to be useful. Proteomic technologies are now being integrated into the drug discovery process as complimentary to genomic approaches. Use of bioinformatics is essential for analyzing the massive amount of data generated from both genomics and proteomics.
Two-dimensional Protein Electrophoresis (2DE)
The central tool for displaying the proteome is two-dimensional gel electrophoresis. Proteins areseparated on the basis of charge in the first dimension and molecular mass in the second. Several improvements have been made to this method in the past few years, particularly in the first-dimension separation.
The sample (eg, tissue, serum) is solubilised, and the proteins are denatured into their polypeptide subunits. This mixture is then separated by isoelectric focusing; on the application of a current, the charged polypeptide subunits migrate in a polyacrylamide gel strip that contains an immobilised pH gradient until they reach the pH at which their overall charge is neutral (isoelectric point or pI), hence producing a gel strip containing discrete protein bands along its length. This gel strip is then applied to the edge of a rectangular slab polyacrylamide gel containing sodium dodecyl sulphate, and the focused polypeptides migrate in an electric current into the second gel and are separated on the basis of molecular size.
Typically 1000–3000 interpretation of their expression takes into account their dynamics in specific biological contexts. The expression or function of proteins is modulated at many points from transcription to post-translation , which generally cannot be predicted from analysis of nucleic acids alone. There is poor correlation between the abundance of mRNA transcribed from the DNA and the respective proteins translated from that mRNA, and the proteins per gel can be visualised, for example by staining with silver. Complementary approaches such as immunoblotting allow greater sensitivity for specific molecules. Multiple forms of individual proteins can be readily visualised , and the particular subset of proteins examined from the proteome is determined by factors such as initial choice of sample solubilisation conditions and pH range of the gel strip used for the first dimension.
Mass Spectrometry
Introduction
Mass spectrometers consist of three essential parts.
The first, an ionization source, is a device to convert molecules into gas-phase ions.
Two powerful ionization techniques are in common use. The first, matrix-assisted laser desorption ionization (MALDI) creates ions by excitation of molecules isolated from the energy of the laser by an energy absorbing matrix. The laser energy strikes the crystalline matrix to cause rapid excitation of the matrix and the subsequent ejection of matrix and analyte ions into the gas-phase.
The second technique electrospray ionization (ESI) creates ions by application of a potential to a flowing liquid causing the liquid to charge and subsequently spray.The electrospray creates very small droplets of solvent-containing analyte. Solvent is removed as the droplets enter the mass spectrometer by heat or some other form of energy (e.g. energetic collisions with a gas), and multiply-charged ions are formed in the process. The detection limits that can be achieved with ESI have improved with a reduction in the flow rates and hence the use of small diameter columns to achieve separations at low flow rates.
II. Mass Analyzer & Ion Detector
Once ions are created individual mass-to-charge ratios (m/z) are separated by a second device, a mass analyzer, and transferred to the third device, an ion detector. A mass analyzer uses some physical property, e.g. electric or magnetic fields or time-of-flight, to separate ions of a particular m/z value that then strike the ion detector. The magnitude of the current produced at the detector as a function of time (e.g. the physical field in the mass analyzer is changed as a function of time or the time it takes the ion to move a certain distance) is used to determine the m/z value of the ion. This figure shows an ion trap mass spectrometer with ions trapped in the electric field.By changing the characteristics of the field ions can be manipulated and ejected from the trap to a detector. The time component as a function of the field is what determines the m/z value of the ions.
III. Tandem mass spectrometers
As mentioned before, a tandem mass spectrometer is very useful for gaining structural information about molecules . In the first stage a collection of ions is created in the ion source of the mass spectrometer. The ions are allowed to pass through the first mass analyzer and collision cell and their m/z values are measured in the second mass analyzer. Based on the data collected in the initial measurement, the first mass spectrometer is set to pass just one m/z value. This ion enters the collision cell and collides with argon. The kinetic energy of ions is converted to vibrational energy and the ions fragment. The m/z values of fragment ions are then determined in the second mass spectrometer.
Many types of tandem mass spectrometers have been developed and new innovations in tandem mass spectrometers allow greater automation and efficiency in data acquisition. Data can be generated in a data-dependent manner through interaction of the m/z data in each scan with a computer program to control the type of experiment performed. For example, a scan of the mass range can reveal the presence of several ions above a preset ion-abundance threshold. The computer can signal to the instrument to perform tandem mass spectrometry on each of the ions, thus improving the efficiency of data acquisition, particularly during separations when ions appear for only a brief period of time.
IV. Determining the amino acid sequence of a peptide.
By using tandem mass spectrometry, data specific to an individual peptide is collected. Fragmentation information can be used to determine the amino acid sequence of a peptide.
Shown is the manner in which peptides fragment by the bonds that have been observed to dissociate. The most common fragment ions are the b and y-type ions, which provide overlapping information about the sequence.
b ions <-------------------------------------> y ions
By calculating the molecular weight difference between ions of the same type the sequence can be determined.
The SEQUEST software, developed in the Yates laboratory, uses the fragmentation information of a tandem mass spectrum to search through the complete protein database of Sacchromyces cerevisiae to identify the sequence which best fits the fragmentation pattern.
SEQUEST
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Performs sequencing and identification by matching unknown MS/MS spectra to sequence in a database |
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Finds all peptides that matches the input masses. |
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Calculates a preliminary score based upon matching ion intensities of predicted frament ions to peaks in the experimental spectrum. |
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Calculates final scores by performing cross correlations of theoretical spectra of the top N preliminary scoring peptides against the input spectrum. |
Expected fragmentation patterns can be predicated from sequence and then compared to the spectrum.
In these figures the expected b-ions (in red) and y-ions (in blue) are compared to the acquired spectrum.
In the process of finding the sequence, that best fits the spectrum, the protein from which this sequence is derived is identified. Here is an example of the output.
V. Conclusion
An advantage of this approach is that each peptide tandem mass spectrum represents a unique piece of information, consequently matching one or more tandem mass spectra to sequences in the same protein provides a high level of confidence in the identification and enables the identification of proteins present in mixtures. This process has been automated in the software SEQUEST.
Definitions:
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Mass-to-charge ratio (m/z): Mass spectrometers measure the mass to charge ratios of ions. In MALDI and electrospray ionization, peptides are typically ionized by the addition of one or more protons. Thus, a peptide of molecular weight 1000 daltons will have a m/z value of 1001 after ionization by the addition of one proton and 501 with the addition of two (M+2H)+2. |
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Collision-induced dissociation (CID): One method of energetically activating ions to dissociate. Typically, a gas-phase collision cell filled with argon gas is used to subject ions to low energy collision (10-50 eV) causing energetic excitation. As ions become energetically excited, covalent bonds dissociate to produce structurally informative fragment ions. Often the molecular structure of the ion can be postulated from the fragmentation pattern, or in the case of peptides, the amino acid sequence deduced. |
Protein bioinformatics
Experiments done in a real laboratory need to be complemented by virtual experiments done on computer.
In addition to the software packages for analysing the electrophoretic separation, bioinformatic tools have been developed. Some of these are available via the internet with links to many provided from the ExPASy proteomics server (www.expasy.ch/www/tools.html).
These allow not only identification of proteins but further characterisation ranging from the calculation of basic physicochemical properties to the prediction of potential post-translational modifications and three-dimensional structures. Annotated protein and two-dimensional electrophoresis databases are the bioinformatic core of proteome research. SWISS-PROT is a typical example of such an annotated database.
Immersion in the proteomic world and its data flood...
Many proteome projects are now underway, resulting in the generation of two-dimensional electrophoresis databases that are accessible on the internet (many can be accessed via links from the ExPASy server at www.expasy.ch) and can be browsed with interactive software and integrated with in-house results. These databases include protein maps of human plasma, urine, cerebrospinal fluid, and tissues such as breast, heart, and bladder transitional-cell and squamous-cell carcinomas, as well as various microorganisms. Ultimately, given the dynamic nature of the proteome, complex experimental details and related results should be displayed with the relevant biochemical pathways or disease implications highlighted.
Yeast Two-hybrid System
The yeast two-hybrid system.
a, Different ORFs are expressed as fusion proteins to either the GAL4 DNA-binding domain (GAL4-BD) or its activation domain(GAL4-AD). If the proteins encoded by the ORFs do not interact with each other, the fusion proteins are not brought into close proximity and there is no activation of transcription of the reporter gene containing the upstream GAL4-binding sites.
b, If the ORFs encode proteins that interact with each other, the fusion proteins are assembled at the GAL4-binding site of the reporter gene, which leads to activation of transcription.
c, Library-based yeast two-hybrid screening method. In this strategy, two different yeast strains containing two different cDNA libraries are prepared. In one case, the ORFs are expressed as GAL4-BD fusions and in the other case, they are expressed as GAL4-AD fusions. The two yeast strains are then mated and diploids selected on deficient media. Thus, only the yeast cells expressing interacting proteins survive. The inserts from both the plasmids are then sequenced to obtain a pair of interacting genes.
The yeast two-hybrid system has emerged as a powerful tool to study protein–protein interactions. It is a genetic method based on the modular structure of transcription factors wherein close proximity of the DNA-binding domain to the activation domain induces increased transcription of a set of genes. The yeast hybrid system uses ORFs fused to the DNA-binding or -activation domain of GAL4 such that increased transcription of a reporter gene results when the proteins encoded by two ORFs interact in the nucleus of the yeast cell. One of the main consequences of this is that once a positive interaction is detected, the ORF is identified simply by sequencing the relevant clones. For these reasons it is a generic method that is simple and amenable to high-throughput screening of protein–protein interactions.
On a large scale, this strategy has been used in two formats. In the array method, yeast clones containing ORFs as fusions to DNA or activation domains are arrayed onto a grid and the ORFs to be tested (as reciprocal fusions) are screened against the entire grid to identify interacting clones. In the library screening method, one set of ORFs are first pooled to generate a library and then the reciprocal ORF–fusions are mated with the library one by one or several at a time.
Such analyses on a genome-wide scale have already been reported in Saccharomyces cerevisiae and to a more limited extent in Caenorhabditis elegans. In yeast, the array method was performed on 192 ORFs and the library screening method for 87% of the yeast genome. Together, this experiment resulted in 957 putative interac-tions. Another group analysed the results of 10% of an exhaustive library screen in yeast, resulting in 183 putative interactions. The vast majority of the interactions found in these two large-scale studies were new. Several of these interactions seem plausible based on previous genetic or biochemical studies, whereas the relevance of most others cannot easily be determined. Therefore, such studies provide only potential interactions that have to be confirmed or eliminated by further biological experimentation. The main advantage of these methods is that they can be performed with a high throughput and in an automated manner. A recently described modification of the yeast two-hybrid method, termed ‘reverse’ two hybrid, can be used for identification of compounds and peptides that disrupt protein–protein interactions. This can lead to development of drugs that have activities in vivo as opposed to drug screens that are conventionally done in vitro.
The following references may tell you a lot about this technology and its application in proteomics:
Proteomics & Disease
Proteomics is providing a better understanding of pathomechanisms of human diseases. Analysis of different levels of gene expression in healthy and diseased tissues by proteomic approaches is as important as the detection of mutations and polymorphisms at the genomic level and may be of more value in designing a rational therapy. Protein distribution / characterization in body tissues and fluids, in health as well as in disease, is the basis of the use of proteomic technologies for molecular diagnostics. Proteomics will play an important role in medicine of the future which will be personalized and will combine diagnostics with therapeutics.
Cancer
Although studies concerned with the identification of novel antigens or markers for diagnostic, prognostic, or therapeutic use have been paramount, molecules and processes implicated in carcinogenesis per se are increasingly being investigated. Most tumour markers in current use were identified from protein-based approaches, from the identification in the 1800s of an abnormal urinary precipitate in myeloma (Bence-Jones protein) to the generation of tumour-specific antibodies against epithelial cancer cell lines. Genetic markers, detected cytogenetically or by mutation detection, are also now entering clinical practice, but some changes likely to be important in carcinogenesis, diagnosis, and prognosis, such as abnormal expression of proto-oncogenes, may not be associated with a detectable genetic lesion. For proteins implicated in cancer, the use of multiple antibodies allows simultaneous characterisation of several proteins acting in a network. For example, overexpression and many post-translational modifications (largely phosphorylations) of several oncogene products and cell-cycle proteins such as p53 can be detected in transformed liver cells. Aberrant glycosylation of many proteins with a known cancer association has been described, and proteomics-based approaches are ideally placed to characterise such post-translational modifications, although much work still needs to be done to assess their clinical significance.
Heart disease
The pathogenesis of the cardiac dysfunction is still largely unknown, but a proteomics-based approach in characterising overall changes in protein expression in heart disease and heart failure may provide new insights into the cellular mechanisms involved in cardiac dysfunction, together with new diagnostic markers and therapeutic opportunities. Federated two-dimensional electrophoresis databases of human cardiac proteins have been established (www.expasy.ch/ch2d/2d-index.html), and several hundred cardiac proteins have been identified.
Infectious diseases
Identification of proteins produced by microorganisms is facilitated by the small number of genes and the completion of genome sequencing for many micro-organisms. The main aim of most studies has been the search for new diagnostic markers, candidate antigens for vaccines, and determinants of virulence. For some of the microorganisms studied, two-dimensional electrophoresis databases are available on the internet (www.expasy.ch/).
Proteomics & Drug Development
Drug development is generally based around the desire to upregulate or downregulate a specific activity implicated in disease pathogenesis or in treatment-associated side-effects. Most drugs exert their effects on proteins. The strategy of working forward from the gene has been used: a specific genetic lesion is identified and the resultant changes in protein structure, function, or expression are elucidated, so that a drug to counteract or correct such aberrations can be rationally designed. The identification on bioactivity grounds of a protein that is pivotal in a biological process has led to the specific design of drugs to manipulate these properties.
The challenge in proteomics-based approaches still lies in identifying the target molecules.Only a few thousand human genes are likely to be suitable targets, and with any single company only able to work on a few hundred, selection is of key importance. Cell-mapping proteomics has a more defined goal of studying protein-protein interactions by systematically characterising the components of protein complexes and building up a map of cellular pathways and interactions that may be important either in a disease process or in the mechanism of action of a drug. By use of specific antibodies or artificially introduced tags, specific proteins can be isolated and any associated proteins can be identified rapidly by mass spectrometry. Targeting of analysis to multiprotein complexes may reveal likely functions of specific proteins more rapidly and indicate appropriate biological studies.
In addition to target selection, equally important in progress to clinical use are target validation and toxicity studies.
Some of the studies of protein expression in relation to genes that have shown an impact on drug discovery are as follows:
Secreted proteins
Identification and functional analysis of secreted proteins is being carried out at Genetics Institute. The cloning and expression of genes encoding this subset of proteins has enabled study of these factors in functional assays. Data from such studies will be important for the identification of novel protein therapeutics and targets.
CD-Tagging
CD-tagging (Jarvik et al. 1996) provides a unique means to investigate each member of the proteome and follow its various activities at the molecular and cellular levels. This technology is being developed by Sequel Genetics. With CD-tagging, a special CD-cassette is inserted into the cell‘s genome. When the insertion occurs in the proper orientation in an intron in an expressed gene, the result is the addition of a unique guest exon to the mRNA and the addition of a unique guest peptide to the encoded protein.
CD-tagging has the following features:
§ Intron-rich genomes such as that of the human are preferred targets.
§ Tagged genes, transcripts and proteins generally retain normal function
§ High throughput.
§ Genes and proteins are identified and analyzed in their natural cellular environment
§ Tagged genes and cDNAs are readily amplified and sequenced.
§ Tagged proteins are localized and tracked at the cellular and subcellular levels.
§ Tagged proteins are purified directly from tagged cells for biochemical analysis.
§ Tissue specificity for transcript and protein expression is readily assessed.
§ Gene function is assessed via modulation of gene function in vivo.
§ Transgenic organisms carrying knockout mutations are rapidly created using proprietary ancillary technology.
To facilitate detection of tagged proteins, the system presently uses two kinds of tags -epitope tags recognized by existing high titer antibodies, and naturally fluorescent GFP tags. Not only can tagged proteins be observed and studied in vivo with these tags, but they can also be readily affinity-purified for biochemical examination or for use in biochemical or functional assays. Further, once a tagged cell of interest has been identified, analysis of the gene that is tagged is straightforward, since one can use the unique tag sequences in the mRNA and DNA to recover and sequence the DNA or RNA.
Although CD-tagging is superficially similar to a number of other tagging methods, it has a number of distinct and unique advantages. Most importantly, the CD-tagged gene is generally regulated normally, since the tag is inserted into the natural gene that retains its own regulatory elements. This is in distinct contrast to standard cDNA-based methods in which epitope-tagged proteins are expressed from heterologous promoter, typically strong promoters of viral origin, with attendant loss of all natural regulation. And the tagging methods that generally do preserve normal regulation, in particular gene trapping and enhancer trapping, have severe limitations at the protein level. In the case of gene trapping, a fusion is produced that lacks much of the sequence of the native protein; not surprisingly, protein function is usually severely compromised. With enhancer traps the situation is even worse, since the reporter and the target gene are expressed separately and so there is no direct means to detect the target gene product. CD-tagged proteins, in contrast, can be observed or purified on the basis of their tags, and at the same time all of the native protein sequence is retained. Although in some cases the tag may interrupt a functional domain of the protein and alter its normal activity or localization, in general the tagged protein retains appropriate localization potential and biological activity.
Transcription-aided drug design
Transcription-aided drug design (TADD) is in development at the department of pharmacology of the University of Pennsylvania. The aim is to assess mRNA or protein level changes which result from a disease state in specific subclasses of cells. An assay has been developed to detect relative levels of phosphorylated versus non-phosphorylated Tau protein (abnormal in Alzheimer‘s disease) in single live neurons and is being extended to quantify protein interactions. This assay has been extended to assess multiple transcription factors to characterize the ability of the cells to transcriptionally respond to specific modulators. The aim is to design drugs to revert abnormal function to normal by manipulating the system using mRNA levels as a guide.