| AnswerNote: proteomics |
Proteomics is a term in the study of genetics which refers to all the proteins expressed by a genome; proteomics involves the identification of proteins in the body and the determination of their role in physiological and pathophysiological functions.
Last updated: January 29, 2006.
| 5min Related Video: proteomics |
Dictionary:
pro·te·o·mics (prō'tē-ō'mĭks)  |
| Oncology Encyclopedia: Proteomics |
Key Terms: Biomarker, Biopsy, Laser capture microdissection microscope, Mass spectroscopy, Mass-to-charge ratio, Phosphorylation, Prostate specific antigen, Protein array.
Definition
Proteomics is the systematic study of all of the proteins in a cell, tissue, or organism.
Description
The term proteome was coined in 1994 to describe all of the proteins in a given cell, tissue, or organism. Proteomes are extremely complex and differ among individuals, cell types, and within the same cell depending on cell activity, stimuli, and disease. There are estimated to be between one and ten million different proteins in the human body. Relatively few of these proteins have been identified.
Proteomics is being developed for use in cancer diagnosis and treatment. A protein pattern or array from blood or a cancer cell eventually may be the primary means of diagnosing cancer. Although significant advances have been made in clinical studies, as of 2005, proteomics was not yet available in clinical settings.
Proteomics technology for cancer diagnosis and treatment identifies biomarkers—proteins and protein patterns in blood, urine, and tissue that can be used to detect:
It is expected that proteomics will be used to:
Proteomics has led to the identification of many biomarker proteins and the discovery of many new proteins in the blood. As of 2005, proteomics has been used to identify hundreds of proteins in the ovary, prostate, breast, and esophagus that increase or decrease as cells begin to grow abnormally.
Procedures
Progress in proteomics has been made possible by the development of new technologies including:
A mass spectrometer consists of:
The result is a mass spectrum or chart with a series of spikes or peaks, each representing a charged protein fragment from the sample. The height of each peak represents the amount of that particular protein or fragment that is present in the sample. The size of the peaks and the distance between them is the protein pattern or array of the entire sample. Each spectrum may have more than 15,000 data points—one for every protein and protein fragment—with their molecular weight and intensity values reflecting their relative abundance in the sample.
Computers rapidly analyze the MS data searching for subtle differences among multiple protein patterns and for proteins that might serve as biomarkers. Once potential biomarkers are identified, the computer is trained to sort through the patterns of thousands of proteins for the few small protein biomarkers that can distinguish between cancer and control samples or between cancer protein patterns before and after treatment.
MS-based proteomic analysis is very fast. The entire process—from collecting a few drops of blood to the spectral analysis—can occur in less than one minute. Extremely small amounts of protein can be detected and hundreds of samples can be analyzed sequentially.
Laser capture microdissection microscopes enable scientists to use tissue removed from a patient by a biopsy to isolate pure samples of normal cells, precancerous cells, and tumor cells from a single tissue of a single patient. Analysis of the protein patterns from these cells enable researchers to study:
Initially, researchers are concentrating on ovarian and prostate cancers, which usually are not detected in early stages when the cancer is progressing without symptoms. By using proteomics for early detection, tumors may be treated before they spread (metastasize) to other parts of the body. Scientists also are studying the most common, solid human tumors including breast, colon, lung, and pancreatic cancers.
Cancers
Ovarian Cancer
More than 80% of ovarian cancers are not diagnosed until they have reached an advanced stage when the five-year-survival rate is 20% or less. However in the 20% of women whose ovarian cancer is diagnosed at an early stage, the prognosis is excellent, with a five-year-survival rate of over 95%.
In 2002 researchers used MS-based proteomics to examine the protein patterns in blood serum, obtained with a finger prick, from 50 patients with stage-I ovarian cancer and 66 controls who were either healthy or had a benign (non-cancerous) condition such as ovarian cysts, fibroids, endometriosis, or general inflammatory disease. Such conditions are much more common than ovarian cancer but may have symptoms that suggest the possibility of cancer. Out of the complex patterns of tens of thousands of serum proteins, the computer identified a specific combination of five proteins that could distinguish between the cancer patients and the controls. Using this identified sub-pattern, all of the cancer patients tested positive—a 100% sensitivity. Among the controls, 5% were false positives demonstrating a specificity of 95%.
In 2004, using higher-resolution MS, a different protein pattern, and a larger group of patients and controls, researchers were able to achieve 100% sensitivity and specificity for diagnosing ovarian cancer. However validation of the procedure on a large clinical sample is needed before a commercial test becomes available. These clinical studies are being carried out in high-risk clinics, in which many women are considering prophylactic oophorectomies—removal of the ovaries—to prevent ovarian cancer, because they have a family history of the disease or carry mutations in the BRCA genes that greatly increase their risk for breast and ovarian cancers.
As of 2005, a clinical trial also was underway comparing proteomics with standard CA-125 blood tests that use a single protein as a biomarker for ovarian cancer. The blood protein CA-125 may be elevated in women with benign conditions as well as ovarian cancer. Another ongoing clinical trial is attempting to use proteomics to predict the early recurrence of ovarian cancer.
The small low-level proteins that have proven useful for the proteomics of ovarian cancer have been found to accumulate on large carrier blood proteins such as albumin. Scientists have found that by extracting the carrier-protein fraction of the blood they can obtain much higher quantities of these biomarkers.
Prostate Cancer
Prostate specific antigen (PSA) levels are used as a preliminary screen for prostate cancer. However 70–75% of men who undergo biopsies because of abnormal PSA levels do not have cancer. It has been difficult to rule-out cancer without a biopsy in patients with slightly elevated PSA levels (4–10 nanograms per ml). MS-based proteomics of the blood proteins in 167 patients with prostate cancer, 77 patients with benign prostate hyperplasia, and 82 healthy males correctly classified 96% of the samples as either prostate cancer or non-cancer including benign prostate hyperplasia. Most of the cancers were correctly identified and the specificity was 71%, meaning that were a number of false positives. The test was effective in men with normal, slightly elevated, and high PSA levels. Thus proteomics may prove useful for choosing whether to perform a biopsy and may reduce the incidence of unnecessary biopsies.
Molecules called phosphates commonly are added to or removed from proteins to change their activity or function. Specific changes in phosphorylated proteins—those with attached phosphates—are believed to be important for prostate cancer progression. Researchers are studying whether changes in phosphorylation, as detected by MS-based proteomics, can be used as biomarkers for diagnosing the progression of prostate and other cancers.
Breast Cancer
Proteomic studies on breast cancer have found a combination of three blood proteins that may be useful for discriminating between women with breast cancer, women with benign breast disease, and healthy women. About 70–80% of breast cancers originate in the mammary ducts—the thin tubes that lead to the nipples. Nipple aspirate fluid from these ducts has a higher concentration of breast-specific proteins than blood. Possible tumor-marker proteins from this fluid are being studied by proteomics.
A 2003 proteomics study successfully identified fluctuating levels of specific active proteins inside breast and ovarian tumor cells. This may help determine early in treatment whether a particular drug is effective in a given patient.
About 25–30% of women with breast cancer have high levels of the protein Her-2/neu on the surfaces of their cancer cells. The cancer drug Herceptin is an anti-body that attaches to Her-2/neu and prevents the protein from promoting cancer cell growth. Ongoing proteomics studies are monitoring key signaling systems in cells that may be influenced by Herceptin and other cancer drugs that target specific molecules. Proteomics has been used to measure the levels of active and inactive signaling proteins in isolated cancer cells obtained from tumor biopsies before and at various times after drug treatment. It has been found that breast cancer patients with a poor prognosis have more of the active form of the protein AKT that promotes cell survival. Herceptin lowers this AKT levels, promoting tumor cell death.
Other Cancers
A 2004 proteomics study found a protein pattern that may predict which people with familial adenomatous polyposis (FAP)—an inherited condition that often leads to colon cancer—will respond to the preventive drug celecoxib. Protein patterns from patients before and after drug treatment distinguished between those in which celecoxib decreased the number of colon polyps that are characteristic of FAB and those who did not respond to the drug. One particular protein peak appeared only in patterns from non-responsive patients. A few protein peaks changed significantly in all patients following treatment with celecoxib.
Scientists are searching for blood protein patterns that may predict a person's risk for prostate cancer, pancreatic cancer, and melanoma. Protein patterns have been found in tumor tissue from lung and bladder cancers that may be able to discriminate between cancerous and healthy tissues.
As of 2005 proteomics clinical trials were testing blood protein patterns to:
Resources
Books
Baxevanis, Andreas D., and B. F. Francis Ouellette, editors. Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. 3rd ed. Hoboken, NJ: John Wiley, 2005.
Clark, David P. Molecular Biology. Boston: Elsevier Academic Press, 2005.
Fuchs, Jurgen, and Maurizio Podda, editors. Encyclopedia of Medical Genomics and Proteomics. New York: Dekker, 2005.
Periodicals
Aebersold, R., and M. Mann. 'Mass Spectrometry-Based Proteomics.' Nature 422 (2003): 198–207.
Petricoin, E. F., et al. 'Use of Proteomic Patterns in Serum to Identify Ovarian Cancer.' Lancet 369 (2002): 772–7.
Rosenblatt, Kevin P., et al. 'Serum Proteomics in Cancer Diagnosis and Management.' Annual Review of Medicine 55 (2004): 97.
Zhu, W., et al. 'Detection of Cancer-Specific Markers Amid Massive Mass Spectral Data.' Proceedings of the National Academy of Sciences 100 (2003): 14666–71.
Organizations
American Cancer Society. PO Box 102454, Atlanta, GA 30368-2454. 800-ACS-2345.
Proteomics Program, Center for Cancer Research, National Cancer Institute. Public Inquiries Office, Suite 30361, 6116 Executive Blvd., MSC-8322, Bethesda, MD 20892-8322. 301-451-4347.
Other
NCI-CCR Initiatives: Proteomics. Center for Cancer Research, National Cancer Institute. [cited March 30, 2005].
NCI Press Office Staff. 'Proteomics: Research for the 21st Century.' BenchMarks 2, no. 2. February 7, 2002. National Cancer Institute. [cited March 30, 2005].
'Protein Patterns in Blood May Predict Prostate Cancer Diagnosis.' News. October 15, 2002. National Cancer Institute. [cited March 30, 2005].
'Protein Patterns May Identify Ovarian Cancer.' News. February 7, 2002. National Cancer Institute. [cited March 30, 2005].
'Proteomics Shows Promise in Colon Cancer Chemoprevention Study.' News. April 15, 2004. National Cancer Institute. [cited March 30, 2005].
'Proteomics Research Aids Cancer Diagnosis and Treatment.' News. April 9, 2003. National Cancer Institute. [cited March 30, 2005].
'Questions and Answers: Proteomics and Cancer.' News. April 30, 2004. National Cancer Institute. [cited March 30, 2005].
Understanding Cancer Series: Molecular Diagnostics. January 28, 2005. National Cancer Institute. [cited March 30, 2005].
—Margaret Alic, Ph.D.
| Genetics Encyclopedia: Proteomics |
Proteomics is the science of studying the multitude of proteomes found in living organisms. A proteome is the entire collection of proteins expressed by a genome or in a tissue. The contents of a proteome can differ in various tissue types, and it can change as a result of aging, disease, drug treatment, or environmental effects.
This is contrary to the concept of a genome, which is an organism's complete collection of DNA. A genome's composition remains more or less constant from tissue to tissue, except for mutations and polymorphisms that can occur.
The word "proteome" was first coined in late 1994. By 1997 there were a number of research conferences focusing on proteomics.
According to the first draft of the human genome, based on the work by the Human Genome Project and by Celera Inc., there are only between thirty thousand and seventy thousand genes in the human genome, many fewer than had been estimated previously. However, as of 2002 there were still groups that believed that there are at least 120,000 genes. Regardless of which of these estimates proves more accurate, the number of potential proteins in the human proteome is quite large. Although the first draft of the human genome reduced the estimates for the total number of human genes, it also predicted a greater amount of alternative splicing of genes, and therefore more distinct protein products per gene, than had been anticipated.
At its simplest level, proteomics is the study of protein expression in a proteome, or trying to understand the relative levels (amounts) of each protein within the mixture. Proteomics attempts to characterize proteins, compare variations in their expression levels in normal and disease states, study their interactions with other proteins, and identify their functional roles.
Unlike the traditional approach of studying individual proteins one at a time, proteomics uses an automated, high-throughput approach. High-throughput refers to the number of items (in this case, proteins) that can be analyzed or studied per unit of time. New technologies and substantial bioinformatics tools are required to compare entire proteomes. Expansion of the field of proteomics into the realm of "big science" (meaning many dollars invested by a large number of companies and universities) is several years behind the expansion of genomics. This is primarily because proteins are more difficult to work with in a laboratory setting than are nucleic acids such as DNA.
The development of protein analysis technologies is more difficult than the development of DNA analysis technologies for three reasons. First, the basic alphabet for encoding proteins consists of twenty amino acids, whereas there are only four different nucleotides, the alphabet of DNA. Second, the messenger RNA (mRNA) for some genes can be differentially spliced, meaning that multiple messages can be made from a single gene, resulting in multiple, distinct protein products. Finally, many proteins are modified once they have been synthesized. This is known as post-translational modification. There are a number of types of post-translational modifications, such as the addition of sugar, phosphate, sulfate, lipid, acetyl, or methyl groups. Each of these modifications has the ability to change the functional activity of a protein.
The above issues have made the elucidation of reliable, high-throughput techniques for characterizing proteins, including their expression levels, on a proteome-wide level a major challenge. Hence, techniques for doing, for example, high-throughput DNA sequencing and gene expression studies have been developed and commercialized on a large scale sooner than similar protein analysis techniques. This is not to imply that all of the techniques involved in proteomics are new. Some, such as two-dimensional gel electrophoresis, have been around since the 1970s. However, the need to adapt these techniques to a large "proteome" scale brings with it a unique set of challenges.
For researchers involved in areas such as drug discovery, proteomics approaches will need to be used to obtain a greater understanding of disease mechanisms and drugs' mechanisms of action. Large-scale studies looking at gene expression via quantification of mRNA abundance are already possible and well commercialized. These technologies are very powerful, and the highest throughput approaches are capable of analyzing tens of thousands of genes per experiment. Sophisticated bioinformatics systems have been, and continue to be, developed to analyze these vast amounts of data. However, studies have shown that mRNA levels do not necessarily correlate well with protein levels.
Researchers must understand proteins and their roles, since proteins are the functional units within cells. As of 2002, the vast majority of drug targets were proteins. There are a handful of drugs, including some chemotherapeutic agents, that bind to DNA, but most drugs bind to specific protein targets. In the cases where the target is a protein, the drugs themselves are primarily small inorganic molecules or, in some cases, small proteins, such as hormones, that bind to a larger protein target in the body. Some drugs are actually therapeutic proteins that are delivered to the site of the disease.
Laboratory Techniques
The primary attributes used to identify proteins include the protein's mass and apparent mass, its isoelectric point, and its N-and C-terminal sequence tags. A protein's mass and its apparent mass are probably the most common characteristics used. Protein mass is determined by adding the total mass of all the amino acids in the protein to the mass of any molecules added through post-translational modification. A protein's isoelectric point is the pH at which it is neutrally charged. A protein's N-and C-terminal sequence tags are short sequences of amino acids on either end of the protein. Since there are twenty different possible amino acids at each position in a protein, a peptide of only four or five amino acids in length is likely to be unique to a specific protein. There are 160,000 (204) combinations of sequences that are four amino acids long.
The most commonly used laboratory techniques in proteomics are two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spec-trometry. These techniques have been modified for use in proteomics. Both can be used in combination with more traditional protein separation techniques, including column chromatography.
Starting in the late 1990s, several companies also started developing "protein chips," another strategy for studying proteomes and other complex protein mixtures. These chips allow a researcher to collect minute quantities of proteins that bind to specific molecules on their surface. By 2001, some companies announced they were developing "antibody chips" onto which antibodies will be attached. The antibodies can then be used as probes to capture and quantify specific proteins found in complex mixtures.
The use of 2-D PAGE allows the simultaneous separation of thousands of proteins, and the technique is still a key tool in proteomics technologies. The first dimension of protein separation on the gel is by isoelectric focusing, in which proteins are separated along a pH gradient until they reach a stationary position, where their net charge is zero.
The second dimension of separation on the gel is by molecular mass. Sodium dodecyl sulphate (SDS) is applied, and it binds to all the proteins. This provides the proteins with a uniform charge along their length, so that they will migrate across the gel according to their molecular mass when a current is applied. After the 2-D PAGE is run, the gel is stained. The result is a two-dimensional map consisting of hundreds or thousands of protein spots.
Since the early use of 2-D PAGE in the early 1970s, a number of modifications have been made to make gels more reproducible and more amenable to the higher-throughput use necessary for proteomics applications. However, 2-D PAGE is still something of an art form, and high-quality, reproducible results are difficult to obtain except in the hands of very experienced users. The technology needs to be further simplified to allow casual and novice users to obtain reproducible, quality results.
Mass spectrometry is an analytical technique that very accurately measures the mass of proteins and peptides. There are two common types of mass spectrometry. The first type, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, can be used to analyze proteins that are embedded in solid samples and measures their mass in a flight tube. The second type, electrospray ionization mass spectrometry, can be used to analyze proteins that are in a liquid solution and measures their mass in either a flight tube or in a device known as a quadrupole. There are also other variations on these techniques.
Mass spectrometry is commonly used for peptide mass fingerprinting. In this process, a protein sample is isolated by 2-D PAGE and cut with an enzyme that specifically targets particular amino acids. Mass spectrometry is used to measure the masses of the resulting cut pieces, or peptides. These masses can be thought of as a fingerprint that can be compared to the fingerprints of proteins whose amino acid sequences have already been analyzed and stored in a database.
To determine the fingerprints of proteins that have already been sequenced, a computer program determines the amino acid composition, and thus the masses, of the pieces that would result if those proteins were also cut by the same enzyme. A list of proteins is generated from the database, sorted by how many peptides they share with the unknown experimental protein.
There are also technologies, including the yeast two-hybrid system, that can be used to study interactions between proteins. These approaches complement 2-D PAGE and mass spectrometry data by helping to elucidate functional cellular pathways.
Databases and Computational Approaches
There is an ever-increasing number of protein and proteome databases being developed. The most comprehensive information about specific proteins is found in databases that store protein sequences. One of the first and probably the best known such database is SWISS-PROT, which was created in 1986.
SWISS-PROT is a curated database that provides not only protein sequences but also such information as descriptions of a protein's function, its domain structure, and post-translational modifications, as well as links to other related databases. Other sequence-based protein databases include the Yeast Proteome Database and Human PSD.
There are also a number of widely used pattern and profile databases that are used to reveal relationships among proteins based on the presence of particular groups of amino acids in the proteins' sequences. Such groups, known as patterns, motifs, domains, signatures, or fingerprints, are found in specific regions of proteins that are important to some function of the protein. They could be in an area that performs some type of enzymatic activity or that is the site of a certain post-translational modification. Both their sequence and structure are typically well conserved. Some of the best known pattern and profile databases are: PROSITE, Pfam, PRINTS, and BLOCKS.
Bibliography
Wilkins, Marc R., et al. eds. Proteome Research: New Frontiers in Functional Genomics.New York: Springer-Verlag, 1997.
—Anthony J. Recupero
| Biology Q&A: What is proteomics? |
Proteomics is the study of proteins encoded by a genome. This
field extends the Human Genome Project and is a far more complex study than
finding where genes are located on chromosomes. Proteins are dynamic molecules
that can change according to the needs of a cell, and complete understanding of
cell metabolism requires that scientists understand all of the proteins
involved as well as their genes.
Previous question:
What is bioterrorism?
Next question:
What is a nucleotide analog?
| Science Dictionary: proteomics |
A new and evolving field of science that seeks to specify all the proteins produced by a cell in all types of situations and environments and to understand how they function. Because proteins are the product of information coded for in DNA, proteomics is closely allied to the study of the genome.
| Veterinary Dictionary: proteomics |
The comprehensive analysis of the identity, interactions and locations of proteins within a cell.
| Wikipedia: Proteomics |
Proteomics is the large-scale study of proteins, particularly their structures and functions.[1][2] Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells. The term "proteomics" was first coined in 1997[3] to make an analogy with genomics, the study of the genes. The word "proteome" is a blend of "protein" and "genome", and was coined by Marc Wilkins in 1994 while working on the concept as a PhD student.[4][5] The proteome is the entire complement of proteins,[4] including the modifications made to a particular set of proteins, produced by an organism or system. This will vary with time and distinct requirements, or stresses, that a cell or organism undergoes.
Contents |
After genomics, proteomics is often considered the next step in the study of biological systems. It is much more complicated than genomics mostly because while an organism's genome is more or less constant, the proteome differs from cell to cell and from time to time. This is because distinct genes are expressed in distinct cell types. This means that even the basic set of proteins which are produced in a cell needs to be determined.
In the past this was done by mRNA analysis, but this was found not to correlate with protein content.[6][7] It is now known that mRNA is not always translated into protein,[8] and the amount of protein produced for a given amount of mRNA depends on the gene it is transcribed from and on the current physiological state of the cell. Proteomics confirms the presence of the protein and provides a direct measure of the quantity present.
More importantly though, any particular protein may go through a wide variety of alterations which will have critical effects to its function. For example during cell signaling many enzymes and structural proteins can undergo phosphorylation. The addition of a phosphate to particular amino acids—most commonly serine and threonine[9] mediated by serine/threonine kinases, or more rarely tyrosine mediated by tyrosine kinases—causes a protein to become a target for binding or interacting with a distinct set of other proteins that recognize the phosphorylated domain.
Because protein phosphorylation is one of the most-studied protein modifications many "proteomic" efforts are geared to determining the set of phosphorylated proteins in a particular cell or tissue-type under particular circumstances. This alerts the scientist to the signaling pathways that may be active in that instance.
Ubiquitin is a small protein that can be affixed to certain protein substrates by enzymes called E3 ubiquitin ligases. Determining which proteins are poly-ubiquitinated can be helpful in understanding how protein pathways are regulated. This is therefore an additional legitimate "proteomic" study. Similarly, once it is determined what substrates are ubiquitinated by each ligase, determining the set of ligases expressed in a particular cell type will be helpful.
Listing all the protein modifications that might be studied in a "Proteomics" project would require a discussion of most of biochemistry; therefore, a short list will serve here to illustrate the complexity of the problem. In addition to phosphorylation and ubiquitination, proteins can be subjected to methylation, acetylation, glycosylation, oxidation, nitrosylation, etc. Some proteins undergo ALL of these modifications, which nicely illustrates the potential complexity one has to deal with when studying protein structure and function.
Even if one is studying a particular cell type, that cell may make different sets of proteins at different times, or under different conditions. Furthermore, as mentioned, any one protein can undergo a wide range of post-translational modifications.
Therefore a "proteomics" study can become quite complex very quickly, even if the object of the study is very restricted. In more ambitious settings, such as when a biomarker for a tumor is sought - when the proteomics scientist is obliged to study sera samples from multiple cancer patients - the amount of complexity that must be dealt with is as great as in any modern biological project.
Scientists are very interested in proteomics because it gives a much better understanding of an organism than genomics. First, the level of transcription of a gene gives only a rough estimate of its level of expression into a protein. An mRNA produced in abundance may be degraded rapidly or translated inefficiently, resulting in a small amount of protein. Second, as mentioned above many proteins experience post-translational modifications that profoundly affect their activities; for example some proteins are not active until they become phosphorylated. Methods such as phosphoproteomics and glycoproteomics are used to study post-translational modifications. Third, many transcripts give rise to more than one protein, through alternative splicing or alternative post-translational modifications. Fourth, many proteins form complexes with other proteins or RNA molecules, and only function in the presence of these other molecules. Finally, protein degradation rate plays an important role in protein content.[10]
One way in which a particular protein can be studied is to develop an antibody which is specific to that modification. For example, there are antibodies which only recognize certain proteins when they are tyrosine-phosphorylated; also, there are antibodies specific to other modifications. These can be used to determine the set of proteins that have undergone the modification of interest.
For sugar modifications, such as glycosylation of proteins, certain lectins have been discovered which bind sugars. These too can be used.
A more common way to determine post-translational modification of interest is to subject a complex mixture of proteins to electrophoresis in "two-dimensions", which simply means that the proteins are electrophoresed first in one direction, and then in another... this allows small differences in a protein to be visualized by separating a modified protein from its unmodified form. This methodology is known as "two-dimensional gel electrophoresis".
Recently, another approach has been developed called PROTOMAP which combines SDS-PAGE with shotgun proteomics to enable detection of changes in gel-migration such as those caused by proteolysis or post translational modification.
Classically, antibodies to particular proteins or to their modified forms have been used in biochemistry and cell biology studies. These are among the most common tools used by practicing biologists today.
For more quantitative determinations of protein amounts, techniques such as ELISAs can be used.
For proteomic study, more recent techniques such as Matrix-assisted laser desorption/ionization have been employed for rapid determination of proteins in particular mixtures.
Most proteins function in collaboration with other proteins, and one goal of proteomics is to identify which proteins interact. This is especially useful in determining potential partners in cell signaling cascades.
Several methods are available to probe protein-protein interactions. The traditional method is yeast two-hybrid analysis. New methods include protein microarrays, immunoaffinity chromatography followed by mass spectrometry, dual polarisation interferometry and experimental methods such as phage display and computational methods.
One of the most promising developments to come from the study of human genes and proteins has been the identification of potential new drugs for the treatment of disease. This relies on genome and proteome information to identify proteins associated with a disease, which computer software can then use as targets for new drugs. For example, if a certain protein is implicated in a disease, its 3D structure provides the information to design drugs to interfere with the action of the protein. A molecule that fits the active site of an enzyme, but cannot be released by the enzyme, will inactivate the enzyme. This is the basis of new drug-discovery tools, which aim to find new drugs to inactivate proteins involved in disease. As genetic differences among individuals are found, researchers expect to use these techniques to develop personalized drugs that are more effective for the individual.
A computer technique which attempts to fit millions of small molecules to the three-dimensional structure of a protein is called "virtual ligand screening". The computer rates the quality of the fit to various sites in the protein, with the goal of either enhancing or disabling the function of the protein, depending on its function in the cell. A good example of this is the identification of new drugs to target and inactivate the HIV-1 protease. The HIV-1 protease is an enzyme that cleaves a very large HIV protein into smaller, functional proteins. The virus cannot survive without this enzyme; therefore, it is one of the most effective protein targets for killing HIV.
Understanding the proteome, the structure and function of each protein and the complexities of protein-protein interactions will be critical for developing the most effective diagnostic techniques and disease treatments in the future.
An interesting use of proteomics is using specific protein biomarkers to diagnose disease. A number of techniques allow to test for proteins produced during a particular disease, which helps to diagnose the disease quickly. Techniques include western blot, immunohistochemical staining, enzyme linked immunosorbent assay (ELISA) or mass spectrometry. The following are some of the diseases that have characteristic biomarkers that physicians can use for diagnosis.
In Alzheimer’s disease, elevations in beta secretase create amyloid/beta-protein, which causes plaque to build up in the patient's brain, which is thought to play a role in dementia.[citation needed] Targeting this enzyme decreases the amyloid/beta-protein and so slows the progression of the disease. A procedure to test for the increase in amyloid/beta-protein is immunohistochemical staining, in which antibodies bind to specific antigens or biological tissue of amyloid/beta-protein.
Heart disease is commonly assessed using several key protein based biomarkers. Standard protein biomarkers for CVD include interleukin-6, interleukin-8, serum amyloid A protein, fibrinogen, and troponins. cTnI cardiac troponin I increases in concentration within 3 to 12 hours of initial cardiac injury and can be found elevated days after an acute myocardial infarction. A number of commercial antibody based assays as well as other methods are used in hospitals as primary tests for acute MI.
 |
Wikibooks has more on the topic of |
 |
At Wikiversity you can learn more and teach others about Proteomics at: |
|
|||||
This entry is from Wikipedia, the leading user-contributed encyclopedia. It may not have been reviewed by professional editors (see full disclaimer)
 | Alternative Splicing |
| Bioinformatics |
| Gel Electrophoresis |
 | What is proteomic? Read answer... |
| What are Proteomics applications? Read answer... |
| What are proteomic tools and their applications? Read answer... |
 | What is the role of proteomics in biological research? |
| Plasma proteomics healthenvronment disease? |
| What are proteomics tools and their applications? |
Copyrights:
 |
 | AnswerNote. © 1999-2009 by Answers Corporation. All rights reserved. Read more |
 |
| Dictionary. The American Heritage® Dictionary of the English Language, Fourth Edition Copyright © 2007, 2000 by Houghton Mifflin Company. Updated in 2009. Published by Houghton Mifflin Company. All rights reserved. Read more |
 |
| Oncology Encyclopedia. Gale Encyclopedia of Cancer. Copyright © 2006 by The Gale Group, Inc. All rights reserved. Read more |
 |
| Genetics Encyclopedia. Genetics. Copyright © 2003 by The Gale Group, Inc. All rights reserved. Read more |
 |
| Biology Q&A. The Handy Biology Answer Book. 2004 ©Visible Ink Press. All rights reserved. Read more |
 |
| Science Dictionary. The New Dictionary of Cultural Literacy, Third Edition Edited by E.D. Hirsch, Jr., Joseph F. Kett, and James Trefil. Copyright © 2002 by Houghton Mifflin Company. Published by Houghton Mifflin. All rights reserved. Read more |
 |
| Veterinary Dictionary. Saunders Comprehensive Veterinary Dictionary 3rd Edition. Copyright © 2007 by D.C. Blood, V.P. Studdert and C.C. Gay, Elsevier. All rights reserved. Read more |
 |
| Wikipedia. This article is licensed under the Creative Commons Attribution/Share-Alike License. It uses material from the Wikipedia article "Proteomics". Read more |
Mentioned in
