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    Proteomics Experiments and Studies

    • The Minimum Information About a Proteomics Experiment (MIAPE) [View Experiment]
    • The pitfalls of proteomics experiments without the correct use of bioinformatics tools [View Experiment]
    • Sources of Variability in a Proteomic Experiment [View Experiment]
    • Reproducibility Of 2D Gel-based Proteomics Experiments [View Experiment]
    • ICPL Labeling in Functional Proteomics Experiments: Substrate Identification of the Extracellular Protease ADAMTS1 using SDS-PAGE LC-MS/MS [View Experiment]
    • Using Ontologies in Proteus for Modeling Data Mining Analysis of Proteomics Experiments [View Experiment]
    • Bone Proteomics [View Experiment]
    • Thesis: A platform for the integration of genomic and proteomic data [View Experiment]
    • Dissertation: Design and Validation of Proteome Measurements [View Experiment]
    • Dissertation: Annotating Proteomic Mass Spectrometry Data for Qualitative and Quantitative Experiments [View Experiment]
    Proteomics Background Information


    Proteomics is the large-scale study of proteins, particularly their structures and functions.

    Protein-protein docking is the determination of the molecular structure of complexes formed by two or more proteins without the need for experimental measurement.

    Protein-protein interaction prediction is a field combining bioinformatics and structural biology in an attempt to identify and catalog interactions between pairs or groups of proteins.

    Protein structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry. Its aim is the prediction of the three-dimensional structure of proteins from their amino acid sequences, sometimes including additional relevant information such as the structures of related proteins. In other words, it deals with the prediction of a protein's tertiary structure from its primary structure.

    In protein structure prediction, homology modeling, also known as comparative modeling, is a class of methods for constructing an atomic-resolution model of a protein from its amino acid sequence (the "query sequence" or "target").

    Protein Threading is a method for the computational prediction of protein structure from protein sequence.

    Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the local secondary structures of proteins and RNA sequences based only on knowledge of their primary structure - amino acid or nucleotide sequence, respectively.


    Proteomics is the large-scale study of proteins, particularly their structures and functions. Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells. The term "proteomics" was coined to make an analogy with genomics, the study of the genes. The word "proteome" is a blend of "protein" and "genome". The proteome is the entire complement of proteins, 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.

    Complexity of the Problem

    Proteomics is often considered the next step in the study of biological systems, after genomics. It is much more complicated than genomics, mostly because while an organism's genome is constant - with exceptions such as the addition of genetic material caused by a virus, or the rapid mutations, transpositions, and expansions that can occur in a tumor - the proteome differs from cell to cell. This is because distinct genes are expressed in distinct cell types, meaning 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 even this should be confirmed by confirming the proteins are there).

    Examples of Post-translational Modifications


    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 signalling many enzymes and structural proteins can undergo phosphorylation. The addition of a phosphate to particular amino acids - most commonly tyrosine, which is accomplished by tyrosine kinases, or to serine & threonine, which is mediated by serine/threonine kinases - causes a protein to become a target for binding or interacting with a distinct set of other proteins that recognize the phosphorylated domain.

    Protein phosphorylation is one of the most-studied protein modification, and thus many "proteomic" efforts are geared to determining the set of phosphorylated proteins in a particular cell or tissue-type, under particular circumstances - because this will alert the scientist to the signaling pathways that may be active in that instance.


    Ubiquitin is a small peptide 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.

    Additional modifications

    To list all the protein modifications that might be studied in a "Proteomics" project is to recapitulate a discussion of most of biochemistry; therefore for now a short list might help 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 study protein structure and function.

    Distinct Proteins are Made under Distinct Settings

    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 get quite complex very quickly, even if the object of the study is very restricted. In the more ambitious settings, such as when a biomarker for a tumor is sought - and thus the proteomics scientist is obliged to study sera samples from multiple cancer patients - the amount of compexity that must be dealt with is as great as in any moder biological project.

    Rationale for Proteomics

    The key requirement in understanding protein function is to learn to correlate the vast array of potential protein modifications to particular phenotypic settings, and then determine if a particular post-translational modification is required for a function to occur.

    Limitations to Genomic Study

    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. Finally, many proteins form complexes with other proteins or RNA molecules, and only function in the presence of these other molecules.

    Methods of studying proteins

    Determining proteins which are post-translationally modified

    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 electropheresed 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".

    Determining the existence of proteins in complex mixtures

    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.

    Establishing protein-protein interactions

    Most proteins function in collaboration with other proteins, and one goal of proteomics is to identify which proteins interact. This is especially useful in determing potential partners in cell signalling 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, and combinations of experimental methods such as phage display and computational methods.

    Practical Applications of Proteomics

    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:

    Alzheimer's Disease

    In Alzheimer’s disease, elevations in beta secretase create amyloid/beta-protein, which causes plaque to build up in the patient's brain, which causes dementia. 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

    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.

    For more information: https://en.wikipedia.org/wiki/Proteomics

    Source: Wikipedia (All text is available under the terms of the GNU Free Documentation License and Creative Commons Attribution-ShareAlike License.)

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