Proteomics - a term covering several disciplines aimed at understanding and monitoring proteins - is an emerging field. The Human Genome Project uncovered a basic fact about the molecular basis of life - DNA makes RNA which makes protein. All human proteins are determined by the sequence of nucleotides (DNA base), which is now known with 99.6% accuracy. Once scientists discovered that people's genes show small variations (differences or changes) in their nucleotide content, genetic testing for predicting drug response has become possible.
Traditional drugs have targeted proteins for many years. However, even after the human genome was published in 2001, development of drugs based on the vast new data on proteins has been slow because we cannot interpret a lot of these data with our current level of understanding. Proteomics is expected to discover unexpected targets for drug design by determining the function of thousands of unidentified proteins still likely to be found in the human genome.
Work in proteomics includes:
- Developing protein separation and protein profiling techniques;
- Correlating genetic sequence with three-dimensional (3D) protein structure and 3D structure with protein function; and
- Investigating protein-protein interactions.
Proteomics is also expected to provide experimental data to improve computer-modeling programs that predict protein structure from DNA sequence. In other words, it will help us learn to interpret the information contained in the genome.
Protein profiling and separation techniques
Scientists have discovered information about which genes are expressed (expression means that a certain gene is "turned on") in cells under certain experimental conditions by analyzing messenger RNA (mRNA) transcripts on what are commonly called "gene chips.". This information yields clues about which proteins are involved in certain pathways and disease states. However, differences in half-lives of RNA and proteins, and modifications important to protein function, prevent mRNA profiles from being perfectly matched to the actual protein profile of the cells.
If the proteins from one cell population could be compared to those of another cell population, the profile would identify unique expression patterns at the protein level and would provide new ways to identify disease states. This technique is called direct protein expression profiling. It could also help researchers to identify people who would benefit the most from certain treatments and also those who would be most likely to have unwanted side effects. However, to perform these analyses, we need to develop reproducible protein separation techniques that are more efficient.
The 2D PAGE technique
One traditional, commonly used technique to separate proteins is two-dimensional polyacrylamide gel electrophoresis (2D PAGE). Proteins are separated in one dimension according to their size, and in the second dimension according to their charge (their isolectric point). After separation, the gel is stained so that protein spots can be seen.
Spots are then cut out from the gel, and proteins are digested into short peptide fragments and analyzed by mass spectrometry (MS). The MS profile is used to determine the amino acid sequence of the protein. Bioinformatics software is used to link amino acid sequence information to DNA sequence information. The 2D gel patterns and the specific spots can be used to generate expression patterns for analysis, as described above. Expression is the process of converting genetic information into RNA and protein for use in the cell. Expression patterns, easily analysed using microarrays, can provide a lot of information about the roles that genes play in different situations, such as disease and health.
However, there are still some problems for 2D PAGE as a protein separation and expression profiling technique. Perhaps the most important is that 2D PAGE experiments are hard to reproduce. This has prevented 2D gels from becoming a "gene chip" for protein profiling experiments because it is hard to compare data from multiple experiments.
Protein chip techniques
Protein chip technology improves the speed and reproducibility of protein separations over 2D PAGE. The technology is being used to identify protein biomarkers of diseases such as Alzheimer's and ovarian cancer.
Another technique may be a method for high-throughput, sub-milligram capacity protein purification. This allows separations of small samples using traditional chromatography media.
An additional protein separation technique that shows promise is to develop a monoclonal antibody (mAb) for each protein in a cell, and then pattern these mAbs onto different spots on a protein chip. Each mAb binds strongly and specifically to a specific protein and can tell the difference between copies of the same protein that have been modified by different techniques in the laboratory. These modifications can change the function of a protein, but the resulting physical differences are not often identified by 2D PAGE and other techniques. mAbs can also be generated with almost unlimited variety by "shuffling" the DNA sequences that encode them. The human body can generate over 100 million different antibodies through gene shuffling. mAb technology is expected to be able to compare the expression levels of important known proteins, but the technology is still being developed.
What types of organizations are involved in proteomics?
The work of bioinformatics organizations is closely linked to genomics efforts. These organizations provide data-mining and warehousing capabilities to allow the prediction of protein structure and function based on DNA sequence. They make predictions by comparing novel protein sequences to sequences where the protein structure and function are known. This can be done because proteins can be grouped into families that share similar function. However, relationships among proteins can be complex. As the field of bioinformatics matures, it will improve researchers' capability to relate proteins. Today, bioinformatics organizations are focusing mostly on developing software to improve the reliability and usefulness of 2D PAGE data.
High-throughput protein production and structure
Some companies are specializing in high-throughput protein production, since large, pure quantities of proteins that have been identified as important targets by separation and profiling are necessary for scientists to study them. Others are working to determine X-ray crystal structure for every new protein discovered. The structural information is needed for drug design efforts, which depend upon the information for design of small molecules that bind to proteins.
Protein analysis for drug development
Organizations focusing on protein analysis for drug development work closely with pharmaceutical developers to provide information about how proteins react with each other. They also provide insight into biological pathways, allowing discovery of novel drugs and validation of targets for drug design.
Proteomics' main techniques, such as 2D PAGE and X-ray crystallography, are complex and require highly skilled operators. These processes need to be improved and automated so that the field can grow.
Databases containing current information on protein sequence, structure and function are now coming on board, but techniques for linking and interpreting the data produced by genomics and proteomics need to be developed.
However, as the field of proteomics matures, designing more sophisticated experiments to determine protein function and investigating how proteins fit into complex biological pathways will become possible. Proteomics is expected to multiply the number of known drug targets 100-fold. This will encourage the pharmaceutical industry to develop new drugs. Diagnostics should also benefit from protein profiling, but the medical field will need to keep pace to take advantage of the information that will become available.
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