Amino acids

Related Terms

Amino acids, bioinformatics, clinical proteomics, disease proteomics, electrophoresis, functional genomics, mass spectrometry, population proteomics, protein expression profiling, proteins, proteome, two-dimensional electrophoresis.

Background

The word "proteome" is a combination of the words "protein" and "genome." Proteomics is the study of the proteome, or the complete set of proteins produced by a cell, tissue, or organism. Proteomics uses protein sequences, expression, and structure to determine how different proteins relate, interact, and function in an organism. Essentially, the field of proteomics studies the structure and function of proteins, which are essential for cellular and bodily functions.
Proteins are large molecules made up of smaller molecules called amino acids. There are 20 different amino acids, often referred to as the "building blocks" of proteins. Amino acids are linked together to form a chain held together by peptide bonds, which are chemical bonds formed between two molecules. Combined in chains with different sequences, they make up as many as two million different proteins in the human body, each of which has its own function.
Almost 20% of the adult human body is made up of proteins, which play a number of important roles, including providing structure for the body, carrying substances to the cells, facilitating chemical reactions, and enabling bodily functions such as muscle contracture and immune function.
The sequence of the human genome, which is all of the genes that make up all human beings, usually does not change, and with few exceptions, all cell types in the body contain the same genome. However, not all of the genes are active in each cell to the same degree in every individual. The identity of different cell types, such as muscle, blood, or nerve cells, largely depends on the genes that are active, or expressed, in those cells.
When genes are expressed, deoxyribonucleic acid (DNA), the so-called "building block of life," is copied into ribonucleic acid (RNA). One of the many functions of RNA is to serve as the template for protein production. Although the DNA sequence is mostly unchanging, the profile of genes that are active (referred to as the "expression profile") is constantly changing as the cells respond to signals. As a result, the proteome is also constantly changing in response to signals that come from inside and outside the cells.
The proteome also changes with different states of health and disease and depending on the stage of cell development. Exposure to chemicals or drugs may also change the proteome. Because of this continual state of change, it is important to understand that reference to a proteome is valid only at a particular point in time. Furthermore, the proteome of a cell can have important implications for that cell at any given point in time.
Like the human genome, scientists are trying to map the human proteome in order to identify novel families of proteins, interactions among proteins, and various signaling pathways that determine their function. While the field of genomics studies the products of genes (i.e., proteins), the field of proteomics works backward to determine which gene is responsible for a product.

Methods

General: The purpose of proteomics is to understand how proteins function in and around the cells. Part of what makes proteomics a challenging field is the number of proteins that need to be identified and understood.
To study proteins, researchers must determine sequences of amino acids. To do this, proteins must be separated into smaller segments. These smaller segments are measured by a piece of equipment known as a mass spectrometer. Because each amino acid has a unique mass, this process can help scientists identify which amino acids occur in which order.
Techniques used in proteomics include two-dimensional electrophoresis, imaging, mass spectrometry, bioinformatics, and protein expression profiling.
Two-dimensional electrophoresis (2-DE): Two-dimensional electrophoresis uses an electric current applied to a gel matrix to separate proteins and allow for analysis of these proteins.
Imaging: Involves creating a picture of the electrophoresis gel obtained using the two-dimensional electrophoresis method so that the information on the gel can be measured.
Mass spectrometry: This analytical technique measures the ratio of mass to charge of various particles. It is most often used to determine the amino acid composition of a protein sample by generating a "mass spectrum" that represents the masses of sample components. Proteins separated by 2D gel electrophoresis may be analyzed by a mass spectrometer. Mass spectrometry can also be used in intact tissue samples, which would allow imaging of protein expression in normal and diseased tissues.
Bioinformatics: Bioinformatics derives data from a computer analysis of biological information, such as information stored in the proteome at a specific point in time. Bioinformatics research involves the development of methods for storage, retrieval, and analysis of data. This field integrates concepts from information technology, statistics, math, chemistry, biochemistry, physics, and linguistics.
Protein expression profiling: Protein expression profiling is the measurement of the activity of proteins during any one period of time in order to gain an understanding of which proteins are being made or functioning in a cell or tissue sample.

Research

Disease proteomics: Proteomics can be used to identify markers of disease by examining protein expression in diseased and healthy tissues. Proteomics has been used to understand such disease states as cancer, heart disease, infectious diseases, and even alcoholism.
Population proteomics: Proteomics can be used to identify and understand protein diversity among human populations in order to understand diversity in health and disease. Current research in population proteomics is conducted using HapMap, which is an international effort to identify and catalog genetic similarities and differences among human beings.
Toxicoproteomics: Toxicoproteomics is the application of proteomics to the field of toxicology, which is the study of the adverse effects of chemicals on living organisms. The main goals of toxicoproteomics are to identify key proteins that may become changed during exposure to a particular chemical; to determine the pathways that are affected downstream from this initial protein; and to develop markers that will enable researchers to eventually predict toxicity.
Clinical proteomics: Clinical proteomics uses the protein analysis techniques from proteomics to identify protein expression patterns that may indicate disease states. Many researchers believe that changes in protein expression may be the most accurate way to determine the course of a disease state.
Systems biology: Proteomics is used in conjunction with a variety of data from other technologies, such as genomics, to understand the result of complex interactions in normally and abnormally functioning biological systems.
Pharmacology/drug design: Proteomics is used in pharmacology research and drug design to allow for identification of drug targets within a cell and to provide a more defined understanding of how drugs interact with proteins. This helps researchers develop drugs that produce the desired effect by being more available within the body, and by producing fewer side effects in the patient.

Implications

Information gathered as a result of proteomics will be used in the creation of new drugs, new ways of diagnosing disease, and treatment of disease at the molecular level. Drugs developed on the basis of proteomics research may alter the shape of a defective protein or mimic a missing protein in order to improve health outcomes. The potential exists to create drugs that are personalized for individuals and that cause fewer side effects.
By identifying unique patterns of protein expression associated with states of health and disease, also known as biomarkers, researchers may develop new means of diagnosing and managing disease.
Proteomics has been used to understand various disease states, including cancer, heart disease, and diabetes. Proteomics also has implications for biotechnology and agriculture.
Useful biomarkers for proteomics analysis can be easily obtained from blood or urine, are sensitive enough so that disease states can be identified accurately within an affected individual, are specific enough so that tests will not yield a false-positive result, and bring about a recognizable benefit, such as the improvement in quality of life.

Limitations

Although a vast array of research has been conducted in the field of proteomics, it is a fairly new field of research; the major challenges facing proteomics research are the complexity and size of the human proteome.

Future research

Information gathered as a result of proteomics will be used in the creation of new drugs, ways of diagnosing disease, and the treatment of disease at the molecular level. Drugs developed on the basis of proteomics research may alter the shape of a defective protein or mimic a missing protein in order to improve health outcomes. The potential exists to create drugs that are personalized for individuals and that bring with them fewer side effects.
The field of clinical proteomics aims to apply the information gained from proteomics to the practical setting of patient care. This may greatly advance a clinician's ability to diagnose a patient and to provide him or her with a personalized treatment plan. Future research will likely focus on identifying new disease targets.

Author information

This information has been edited and peer-reviewed by contributors to the Natural Standard Research Collaboration (www.naturalstandard.com).

Bibliography

Conrad DH, Goyette J, Thomas PS. Proteomics as a method for early detection of cancer: a review of proteomics, exhaled breath condensate, and lung cancer screening. J Gen Intern Med 2008;23 Suppl 1:78-84.
Dominguez DC, Lopes R, Torres ML. Introduction to proteomics. Clin Lab Sci 2007;20(4):234-8.
Dominguez DC, Lopes R, Torres ML. Proteomics technology. Clin Lab Sci 2007;20(4):239-44.
Dominguez DC, Lopes R, Torres ML. Proteomics: clinical applications. Clin Lab Sci. 2007;20(4):245-8.
Gesslbauer B, Krenn E, Zanzmaier C, et al. Lessons from the stem cell proteome. Curr Stem Cell Res Ther 2006;1(3):395-409.
Grant SG, Blackstock WP. Proteomics in neuroscience: from protein to network. J Neurosci 2001 Nov 1;21(21):8315-8.
Kohn EC, Azad N, Annunziata C, et al. Proteomics as a tool for biomarker discovery. Dis Markers 2007;23(5-6):411-7.
Mann M, Jensen ON. Proteomic analysis of post-translational modifications. Nat Biotechnol 2003 Mar;21(3):255-61.
National Human Genome Research Institute (NHGRI). .
Natural Standard: The Authority on Integrative Medicine. .
Petricoin EF, Zoon KC, Kohn EC, et al. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov 2002 Sep;1(9):683-95.
Wulfkuhle JD, Liotta LA, Petricoin EF. Proteomic applications for the early detection of cancer. Nat Rev Cancer 2003 Apr;3(4):267-75.