Sunday, March 9, 2008

Protein Synthesis

The cell's ability to synthesize protein is, in essence, the expression of its genetic makeup. Protein synthesis is a sequence of chemical reactions that occur in four distinct stages, i.e., activation of the amino acids that ultimately will be joined together by peptide bonds; initiation of the polypeptide chain at a cell organelle known as the ribosome; elongation of the polypeptide by stepwise addition of single amino acids to the chain; and termination of amino-acid additions and release of the completed protein from the ribosome. The information for the synthesis of specific amino-acid sequences is carried by a nucleic acid molecule called messenger RNA (see nucleic acid). Proteins are needed in the diet mainly for their amino acids, which the body uses to build new proteins (see nutrition).
The mechanism of action of many widely used antibiotics, such as streptomycin, chloramphenicol, and tetracycline, can be understood in terms of their ability to interfere with some stage of protein synthesis in bacteria.

Protein Structure

Every protein molecule has a characteristic three-dimensional shape, or conformation. Fibrous proteins, such as collagen and keratin, consist of polypeptide chains arranged in roughly parallel fashion along a single linear axis, thus forming tough, usually water-insoluble, fibers or sheets. Globular proteins, e.g., many of the known enzymes, show a tightly folded structural geometry approximating the shape of an ellipsoid or sphere.
Because the physiological activity of most proteins is closely linked to their three-dimensional architecture, specific terms are used to refer to different aspects of protein structure. The term primary structure denotes the precise linear sequence of amino acids that constitutes the polypeptide chain of the protein molecule. Automated techniques for amino-acid sequencing have made possible the determination of the primary structure of hundreds of proteins.
The physical interaction of sequential amino-acid subunits results in a so-called secondary structure, which often can either be a twisting of the polypeptide chain approximating a linear helix (α-configuration), or a zigzag pattern (β-configuration). Most globular proteins also undergo extensive folding of the chain into a complex three-dimensional geometry designated as tertiary structure. Many globular protein molecules are easily crystallized and have been examined by X-ray diffraction, a technique that allows the visualization of the precise three-dimensional positioning of atoms in relation to each other in a crystal.
The tertiary structure of several protein molecules has been determined from X-ray diffraction analysis. Two or more polypeptide chains that behave in many ways as a single structural and functional entity are said to exhibit quaternary structure. The separate chains are not linked through covalent chemical bonds but by weak forces of association.
The precise three-dimensional structure of a protein molecule is referred to as its native state and appears, in almost all cases, to be required for proper biological function (especially for the enzymes). If the tertiary or quaternary structure of a protein is altered, e.g., by such physical factors as extremes of temperature, changes in pH, or variations in salt concentration, the protein is said to be denatured; it usually exhibits reduction or loss of biological activity.

Types of Proteins

A protein molecule that consists of but a single polypeptide chain is said to be monomeric; proteins made up of more than one polypeptide chain, as many of the large ones are, are called oligomeric. Based upon chemical composition, proteins are divided into two major classes: simple proteins, which are composed of only amino acids, and conjugated proteins, which are composed of amino acids and additional organic and inorganic groupings, certain of which are called prosthetic groups. Conjugated proteins include glycoproteins, which contain carbohydrates; lipoproteins, which contain lipids; and nucleoproteins, which contain nucleic acids.
Classified by biological function, proteins include the enzymes, which are responsible for catalyzing the thousands of chemical reactions of the living cell; keratin, elastin, and collagen, which are important types of structural, or support, proteins; hemoglobin and other gas transport proteins; ovalbumin, casein, and other nutrient molecules; antibodies, which are molecules of the immune system (see immunity); protein hormones, which regulate metabolism; and proteins that perform mechanical work, such as actin and myosin, the contractile muscle proteins.

Enzymes

One particularly important type of protein is an enzyme, discussed in the essay on that topic. Enzymes make possible a host of bodily processes, in part by serving as catalysts, or substances that speed up a chemical reaction without actually participating in, or being consumed by, that reaction. Enzymes enable complex, life-sustaining reactions in the human body—reactions that would be too slow at ordinary body temperatures—and they manage to do so without forcing the body to undergo harmful increases in temperature. They also are involved in fermentation, a process with applications in areas ranging from baking bread to reducing the toxic content of wastewater. (For much more on these subjects, see Enzymes.)
Inside the body, enzymes and other proteins have roles in digesting foods and turning the nutrients in them—including proteins—into energy. They also move molecules around within our cells to serve an array of needs and allow healthful substances, such as oxygen, to pass through cell membranes while keeping harmful ones out. Proteins in the chemical known as chlorophyll facilitate an exceptionally important natural process, photosynthesis, discussed briefly in Carbohydrates

Protein

Any of a group of complex organic macromolecules that contain carbon, hydrogen, oxygen, nitrogen, and usually sulfur and are composed of one or more chains of amino acids. Proteins are fundamental components of all living cells and include many substances, such as enzymes, hormones, and antibodies, that are necessary for the proper functioning of an organism. They are essential in the diet of animals for the growth and repair of tissue and can be obtained from foods such as meat, fish, eggs, milk, and legumes.

The Structure of Double-Stranded Dna

As mentioned above, the two individual strands are held together by hydrogen bonds between individual T·A and C·G base pairs. In DNA, the distance between the atoms involved is 2.8 to 2.95 angstroms (10−10 meters). While individually weak, the large number of hydrogen bonds along a DNA chain provides sufficient stability to hold the two strands together.
The stabilization of duplex (double-stranded) DNA is also dependent on base stacking. The planar, rigid bases stack on top of one another, much like a stack of coins. Since the two purine.pyrimidine pairs (A.T and C.G) have the same width, the bases stack in a rather uniform fashion. Stacking near the center of the helix affords protection from chemical and environmental attack. Both hydrophobic interactions and van der Waal's forces hold bases together in stacking interactions. About half the stability of the DNA helix comes from hydrogen bonding, while base stacking provides much of the rest.
Double-stranded DNA in its canonical B-form is a right-handed helix formed by two individual DNA strands aligned in an antiparallel fashion (a right-handed helix, when viewed on end, twists clockwise going away from the viewer). Antiparallel DNA has the two strands organized in the opposite polarity, with one strand oriented in the 5′-3′ direction and the other oriented in the 3′-5′ direction.
In the right-handed B-DNA double helix, the stacked base pairs are separated by about 3.24 angstroms with 10.5 base pairs forming one helical turn (360°), which is 35.7 angstroms in length. Two successive base pairs, therefore, are rotated about 34.3° with respect to each other. The width of the helix is 20 angstroms. An idealized model of the double helix is shown in Figure 3. As can be seen, the organization of the bases creates a major groove and a minor groove.
Adenine and thymine are said to be complementary, as are cytosine and guanine. Complementary means "matching opposite." The shapes and charges of adeninne and thymine complement each other, so that they attract one another and link up (as do cytosine and guanine). Indeed, one entire strand of duplex DNA is complementary to the opposing strand. During replication, the two strands unwind, and each serves as a template for formation of new complementary strand, so that replication ends with two exact double-stranded copies.
Alternative Dna Conformations

Nucleosides and Nucleotides

The term "nucleoside" refers to a base and sugar. "Nucleotide," on the other hand, refers to the base, sugar, and phosphate group (Figure 1). A bond, called the glycosidic bond, holds the base to the sugar and the 3′-5′ ("three prime-five prime") phosphodiester bond holds the individual nucleotides together. Nucleotides are joined from the 3′ carbon of the sugar in one nucleotide to the 5′ carbon of the sugar of the adjacent nucleotide. The 3′ and the 5′ ends are chemically very distinct and have different reactive properties. During DNA replication, new nucleotides are added only to the 3′ OH end of a DNA strand. This fact has important implications for replication.

Nucleosides and Nucleotides

The term "nucleoside" refers to a base and sugar. "Nucleotide," on the other hand, refers to the base, sugar, and phosphate group (Figure 1). A bond, called the glycosidic bond, holds the base to the sugar and the 3′-5′ ("three prime-five prime") phosphodiester bond holds the individual nucleotides together. Nucleotides are joined from the 3′ carbon of the sugar in one nucleotide to the 5′ carbon of the sugar of the adjacent nucleotide. The 3′ and the 5′ ends are chemically very distinct and have different reactive properties. During DNA replication, new nucleotides are added only to the 3′ OH end of a DNA strand. This fact has important implications for replication.

Deoxyribose Sugar

In DNA the bases are connected to a β-D-2-deoxyribose sugar with a hydrogen atom at the 2′ ("two prime") position. The sugar is a very dynamic part of the DNA molecule. Unlike the nucleotide bases, which are planar and rigid, the sugar ring is easily bent and twisted into various conformations (which exist in different structural forms of DNA). In canonical B-DNA, the accepted and most common form of DNA, the sugar configuration is known as C2′ endo.

Bases and Base Pairs

The four bases found in DNA are shown in Figures 1 and 2. The purines and pyrimidines are the informational molecules of the genetic blueprint for the cell. The two sides of the helix are held together by hydrogen bonds between base pairs. Hydrogen bonds are weak attractions between a hydrogen atom on one side and an oxygen or nitrogen atom on the other. Hydrogen atoms of amino groups serve as the hydrogen bond donor while the carbonyl oxygens and ring nitrogens serve as hydrogen bond acceptors. The specific location of hydrogen bond donor and acceptor groups gives the bases their specificity for hydrogen bonding in unique pairs. Thymine (T) pairs with adenine (A) through two hydrogen bonds, and cytosine (C) pairs with guanine (G) through three hydrogen bonds (Figure 2). T does not normally pair with G, nor does C normally pair with A.

. The Components of Dna

DNA is composed of purine (adenine and guanine) and pyrimidine (cytosine and thymine) bases, each connected through a ribose sugar to a phosphate backbone. Many variations are possible in the chemical structure of the bases and the sugar, and in the structural relationship of the base to the sugar that result in differences in helical shape and form. The most common DNA helix, B-DNA, is a double helix of two DNA strands with about 10.5 base pairs per helical turn.

DNA

DNA (deoxyribonucleic acid) was discovered in the late 1800s, but its role as the material of heredity was not elucidated for fifty years after that. It occupies a central and critical role in the cell as the genetic information in which all the information required to duplicate and maintain the organism. All information necessary to maintain and propagate life is contained within a linear array of four simple bases: adenine, guanine, thymine, and cytosine.
DNA was first described as a monotonously uniform helix, generally called B-DNA. However, we now know that DNA can adopt many different shapes and conformations. Moreover, many of these alternative shapes have biological importance. Thus, the DNA is not simply an informational repository, from which information flows through RNA into proteins. Rather, structural information exists within the specific sequence patterns of the bases. This structural information dictates the interaction of DNA with proteins to carry out processes of DNA replication, transcription into RNA, and repair of errors or damage to the DNA

Future Potential of Biocomputers

Many examples of simple biocomputers have been designed, but the capabilities of these biocomputers are still largely premature in comparison to commercially available non-bio computers. However, there is definitely great potential in the capabilities that biocomputers may one day acquire. Evidence of the true potential of the computing capabilities of biocomputers exists in the most powerful, complex computational machine known to currently exist: the biocomputer that is the human brain. Certainly, there is plenty of room to improve in the realm of biocomputer computational ability; one may reasonably expect the science of biocomputers to advance greatly in the years to come.

Notable Advancements in Biocomputer Technology

Currently, biocomputers exist with various functional capabilities that include operations of logic and mathematical calculations. T. Knight of the MIT Artificial Intelligence Laboratory first suggested a biochemical computing scheme in which protein concentrations are used as binary signals that ultimately serve to perform logical operations (349).2 At or above a certain concentration of a particular biochemical product in a biocomputer chemical pathway indicates a signal that is either a 1 or a 0, and a concentration below this level indicates the other, remaining signal. Using this method as computational analysis, biochemical computers can perform logical operations in which the appropriate binary output will occur only under specific, logical constraints on the initial conditions. In other words, the appropriate binary output serves as a logically derived conclusion from a set of initial conditions that serve as premises from which the logical conclusion can be made. In addition to these types of logical operations, biocomputers have also been shown to demonstrate other functional capabilities, such as mathematical computations. One such example was provided by W.L. Ditto, who in 1999 created a biocomputer composed of leech neurons at Georgia Tech which was capable of performing simple addition. These are just a few of the notable uses that biocomputers have already been engineered to perform, and the capabilities of biocomputers are becoming increasingly sophisticated. Because of the availability and potential economic efficiency associated with producing biomolecules and biocomputers, as noted above, the advancement of the technology of biocomputers is a popular, rapidly growing subject of research that is likely to see much progress in the future.

Economical Benefit of Biocomputers

A hallmark of all biological organisms and the chemical building blocks that comprise them is the ability to self-replicate and self-assemble into functional components; life could not be sustained if living organisms were not capable of replicating themselves. The economical benefit of biocomputers lies in this potential of all biologically derived systems to self-replicate and self-assemble given appropriate conditions . For instance, all of the necessary proteins for a certain biochemical pathway, which can be modified to serve as a biocomputer, can be synthesized many times over inside a biological cell from a single DNA molecule, which can itself be replicated many times over. This characteristic of biological molecules makes their production highly efficient and relatively inexpensive. Whereas non-biological computer components require extensive production processes, the components of biocomputers can be produced in large quantities from tandem processes occurring in a single, easily attainable, convenient source—the replicating machinery present within any biological cell.

Engineering Biocomputers

The behavior of biologically derived computational systems such as these relies on the particular molecules that make up the system, which are primarily proteins but may also include DNA molecules. Nanobiotechnology provides the means to synthesize the multiple chemical components necessary to create such a system. The chemical nature of a protein is dictated by its sequence of amino acids—the chemical building blocks of proteins. This sequence is in turn dictated by a specific sequence of DNA nucleotides—the building blocks of DNA molecules. Proteins are manufactured in biological systems through the translation of nucleotide sequences by biological molecules called ribosomes, which assemble individual amino acids into polypeptides that form functional proteins based on the nucleotide sequence that the ribosome interprets. What this ultimately means is that one can engineer a biocomputer, i.e. the chemical components necessary to serve as a biological system capable of performing computations, by engineering DNA nucleotide sequences to encode for the necessary protein components. Also, the synthetically designed DNA molecules themselves may function in a particular biocomputer system. Thus, implementing nanobiotechnology to design and produce synthetically designed proteins, as well as the design and synthesis of artificial DNA molecules, can allow the construction of functional biocomputers.

Saturday, March 8, 2008

Ultrasound pulses beef up gene therapy for tumors

High-intensity focused ultrasound emitted in short pulses is a promising, non-invasive procedure for enhancing gene delivery to cancerous cells without destroying healthy tissue, according to a study in the May issue of the journal Radiology.
High-intensity focused ultrasound (HIFU) is more powerful than standard ultrasound. HIFU can destroy tumors through long and continuous exposures that raise the temperature inside cancerous cells, effectively "cooking" them. Under a technique introduced by King C.P. Li, M.D., M.B.A., from the National Institutes of Health (NIH), short pulses of HIFU can be used to prevent exposed tissue from becoming too hot and damaged. Pulsed-HIFU instead renders tissues permeable and helps target them for taking up genes and other therapeutic substances injected into the body.
"Basically, we're using sound waves to open up the tissue by producing gaps between the cells, making it leakier and more prone to taking up various genes, agents and compounds," said Victor Frenkel, Ph.D., a staff scientist for the diagnostic radiology department at the NIH Clinical Center in Bethesda, Md.
Working with lead authors Kristin M. Dittmar, M.D., and Jianwu Xie, M.D., the researchers used pulsed-HIFU on tumors in mice, then immediately injected an easily measurable reporter gene into the vein in their tails. The reporter gene in this study--a fluorescent-green protein found in deep-sea invertebrates--was visible in all sections of the tumors exposed to pulsed-HIFU. Tumors not targeted with pulsed-HIFU showed negligible signs of the gene.

MRI sees gene expression in living animals

In a first, Carnegie Mellon University scientists have "programmed" cells to make their own contrast agents, enabling unprecedented high-resolution, deep-tissue imaging of gene expression. The results, appearing in the April issue of Nature Medicine, hold considerable promise for conducting preclinical studies in the emerging field of molecular therapeutics and for monitoring the delivery of therapeutic genes in patients.
"For 20 years it has been the chemist's job to develop agents that can be used to enhance MRI contrast," said Eric Ahrens, assistant professor of biological sciences in the Mellon College of Science at Carnegie Mellon. "Now, with our approach, we have put this job into the hands of the molecular biologist. Using off-the-shelf molecular biology tools we can now enable living cells to change their MRI contrast via genetic instructions."
"The new imaging method is a platform technology that can be adapted for many tissue types and for a range of preclinical uses in conjunction with emerging molecular therapeutic strategies," Ahrens said.
Ahrens' new approach uses magnetic resonance imaging (MRI) to monitor gene expression in real-time. Because MRI images deep tissues non-invasively and at high resolution, investigators don't need to sacrifice animals and perform laborious and costly analysis.
To trigger living cells into producing their own contrast agent, Ahrens gave them a gene that produces a form of ferritin, a protein that normally stores iron in a non-toxic form. This metalloprotein acts like a nano-magnet and a potent MRI "reporter."
A typical MRI scan detects and analyzes signals given off by hydrogen protons in water molecules after they are exposed to a magnetic field and radiofrequency pulses. These signals are then converted into an image. Ahrens' new MRI reporter alters the magnetic field in its proximity, causing nearby protons to give off a distinctly different signal. The resulting image reveals dark areas that indicate the presence of the MRI reporter.

Computer program helps doctors diagnose lung cancer

CAD software helps distinguish benign, malignant nodules seen on CT scans
Not all masses are cancer. When a person undergoes a scan to identify a lump or nodule, the radiologist looks at the texture, the borders and the shape to determine if it is malignant or just a benign growth.
Researchers at the University of Michigan Comprehensive Cancer Center are developing computer-aided diagnosis (CAD) methods to make that assessment easier. A computer program reads the same scans the radiologist views, and the combined judgment of the computer and radiologist helps detect more cancers, the researchers found.
''Our system is designed to help the radiologist. From our experiences in evaluating CAD for breast cancer, using computer aids significantly improves the performance of the radiologist in predicting malignancies of the masses. Radiologists with computers are able to detect more cancers than radiologists by themselves. We expect that CAD for lung cancer can achieve similar results,'' says Lubomir Hadjiyski, Ph.D., research assistant professor of Radiology at the U-M Medical School. Hadjiyski will present results of the lung cancer study Sunday, Nov. 28, at the Radiological Society of North America's annual meeting in Chicago.
In the study, researchers looked at 41 CT scans that showed nodules in the lungs. Current scans and previous scans were fed through a computer program specially designed by the U-M researchers to evaluate the size, texture, density and change over time of the nodules. Based on that information, the computer determines how likely the nodule is cancerous.
Previous attempts at computer-aided diagnosis have the computer analyze only the current scan. By allowing the computer to read and compare a series of scans, it gets a complete picture and has the same information the radiologist has.

Molecular devices' remarkably precise scans of cellular activity could revolutionize medicine

Each human cell already has all of the tools required to build these biocomputers on its own," says Harvard's Yaakov (Kobi) Benenson, a Bauer Fellow in the Faculty of Arts and Sciences' Center for Systems Biology. "All that must be provided is a genetic blueprint of the machine and our own biology will do the rest. Your cells will literally build these biocomputers for you."
Evaluating Boolean logic equations inside cells, these molecular automata will detect anything from the presence of a mutated gene to the activity of genes within the cell. The biocomputers' "input" is RNA, proteins, and chemicals found in the cytoplasm; "output" molecules indicating the presence of the telltale signals are easily discernable with basic laboratory equipment.
"Currently we have no tools for reading cellular signals," Benenson says. "These biocomputers can translate complex cellular signatures, such as activities of multiple genes, into a readily observed output. They can even be programmed to automatically translate that output into a concrete action, meaning they could either be used to label a cell for a clinician to treat or they could trigger therapeutic action themselves."
Benenson and his colleagues demonstrate in their Nature Biotechnology paper that biocomputers can work in human kidney cells in culture. Research into the system's ability to monitor and interact with intracellular cues such as mutations and abnormal gene levels is still in progress.
Benenson and colleagues including Ron Weiss, associate professor of electrical engineering at Princeton, have also developed a conceptual framework by which various phenotypes could be represented logically.
A biocomputer's calculations, while mathematically simple, could allow researchers to build biosensors or medicine delivery systems capable of singling out very specific types or groups of cells in the human body. Molecular automata could allow doctors to specifically target only cancerous or diseased cells via a sophisticated integration of intracellular disease signals, leaving healthy cells completely unaffected.

In a first, scientists develop tiny implantable biocomputers


This work is a crucial step towards building biological computers, tiny implantable devices that cResearchers at Harvard University and Princeton University have made a crucial step toward building biological computers, tiny implantable devices that can monitor the activities and characteristics of human cells. The information provided by these "molecular doctors," constructed entirely of DNA, RNA, and proteins, could eventually revolutionize medicine by directing therapies only to diseased cells or tissues.

Level Parts of Human Biocomputer

Above and in Biocomputer: Unknown10. Beyond Metaprogramming: Supra-Species-Metaprograms9. To be Metaprogrammed: Supra-Self-Metaprograms8. To Metaprogram: Self-Metaprogram - Awareness7. To Program sets of programs: Metaprograms - Metaprogram Storage6. Detailed instructions: Programs - Program Storage5. Details of instructions: Subroutines - Subroutine Storage4. Signs of activity: Biochemical Activity - Neural Activity - Glial Activity - Vascular Activity3. Brain: Biochemical Brain - Neural Brain - Glial Brain - Vascular Brain2. Body: Biochemical Body - Sensory Body - Motor Body - Vascular Body1. External Reality: Biochemical - Chemical - Physical.

What is Human Biocomputer?

The Human Biocomputer coined by John C. Lilly, refers literally to the "hardware" of the human anatomy. This would include the brain, internal organs, and other human organ systems such as Cardiovascular, Digestive, Endocrine, Immune, Integumentary, Lymphatic, Muscular, Nervous, Reproductive, Respiratory, Skeletal, and Urinary systems. The biocomputer has stored program properties, and self-metaprogramming properties, with limits determinable and to be determined.

Future Potential of Biocomputers

Many examples of simple biocomputers have been designed, but the capabilities of these biocomputers are still largely premature in comparison to commercially available non-bio computers. However, there is definitely great potential in the capabilities that biocomputers may one day acquire. Evidence of the true potential of the computing capabilities of biocomputers exists in the most powerful, complex computational machine known to currently exist: the biocomputer that is the human brain. Certainly, there is plenty of room to improve in the realm of biocomputer computational ability; one may reasonably expect the science of biocomputers to advance greatly in the years to come.

Future Potential of Biocomputers

Many examples of simple biocomputers have been designed, but the capabilities of these biocomputers are still largely premature in comparison to commercially available non-bio computers. However, there is definitely great potential in the capabilities that biocomputers may one day acquire. Evidence of the true potential of the computing capabilities of biocomputers exists in the most powerful, complex computational machine known to currently exist: the biocomputer that is the human brain. Certainly, there is plenty of room to improve in the realm of biocomputer computational ability; one may reasonably expect the science of biocomputers to advance greatly in the years to come.

Notable Advancements in Biocomputer Technology

Currently, biocomputers exist with various functional capabilities that include operations of logic and mathematical calculations. T. Knight of the MIT Artificial Intelligence Laboratory first suggested a biochemical computing scheme in which protein concentrations are used as binary signals that ultimately serve to perform logical operations (349).² At or above a certain concentration of a particular biochemical product in a biocomputer chemical pathway indicates a signal that is either a 1 or a 0, and a concentration below this level indicates the other, remaining signal. Using this method as computational analysis, biochemical computers can perform logical operations in which the appropriate binary output will occur only under specific, logical constraints on the initial conditions. In other words, the appropriate binary output serves as a logically derived conclusion from a set of initial conditions that serve as premises from which the logical conclusion can be made. In addition to these types of logical operations, biocomputers have also been shown to demonstrate other functional capabilities, such as mathematical computations. One such example was provided by W.L. Ditto, who in 1999 created a biocomputer composed of leech neurons at Georgia Tech which was capable of performing simple addition (351).² These are just a few of the notable uses that biocomputers have already been engineered to perform, and the capabilities of biocomputers are becoming increasingly sophisticated. Because of the availability and potential economic efficiency associated with producing biomolecules and biocomputers, as noted above, the advancement of the technology of biocomputers is a popular, rapidly growing subject of research that is likely to see much progress in the future.

Economical Benefit of Biocomputers

A hallmark of all biological organisms and the chemical building blocks that comprise them is the ability to self-replicate and self-assemble into functional components; life could not be sustained if living organisms were not capable of replicating themselves. The economical benefit of biocomputers lies in this potential of all biologically derived systems to self-replicate and self-assemble given appropriate conditions (349).² For instance, all of the necessary proteins for a certain biochemical pathway, which can be modified to serve as a biocomputer, can be synthesized many times over inside a biological cell from a single DNA molecule, which can itself be replicated many times over. This characteristic of biological molecules makes their production highly efficient and relatively inexpensive. Whereas non-biological computer components require extensive production processes, the components of biocomputers can be produced in large quantities from tandem processes occurring in a single, easily attainable, convenient source—the replicating machinery present within any biological cel

Engineering Biocomputers

The behavior of biologically derived computational systems such as these relies on the particular molecules that make up the system, which are primarily proteins but may also include DNA molecules. Nanobiotechnology provides the means to synthesize the multiple chemical components necessary to create such a system. The chemical nature of a protein is dictated by its sequence of amino acids—the chemical building blocks of proteins. This sequence is in turn dictated by a specific sequence of DNA nucleotides—the building blocks of DNA molecules. Proteins are manufactured in biological systems through the translation of nucleotide sequences by biological molecules called ribosomes, which assemble individual amino acids into polypeptides that form functional proteins based on the nucleotide sequence that the ribosome interprets. What this ultimately means is that one can engineer a biocomputer, i.e. the chemical components necessary to serve as a biological system capable of performing computations, by engineering DNA nucleotide sequences to encode for the necessary protein components. Also, the synthetically designed DNA molecules themselves may function in a particular biocomputer system. Thus, implementing nanobiotechnology to design and produce synthetically designed proteins, as well as the design and synthesis of artificial DNA molecules, can allow the construction of functional biocomputers, .

Bioelectronic Computers

Biocomputers can also be constructed to perform electronic computing. Again, like both biomechanical and biochemical computers, computations are performed by interpreting a specific output that is based upon an initial set of conditions that serve as input. In bioelectronic computers, the measured output is the nature of the electrical conductivity that is observed in the bioelectronic computer, which comprises specifically designed biomolecules that conduct electricity in highly specific manners based upon the initial conditions that serve as the input of the bioelectronic system

Bioelectronic Computers

Biocomputers can also be constructed to perform electronic computing. Again, like both biomechanical and biochemical computers, computations are performed by interpreting a specific output that is based upon an initial set of conditions that serve as input. In bioelectronic computers, the measured output is the nature of the electrical conductivity that is observed in the bioelectronic computer, which comprises specifically designed biomolecules that conduct electricity in highly specific manners based upon the initial conditions that serve as the input of the bioelectronic system.

Biomechanical Computers

Biomechanical computers are similar to biochemical computers in that they both perform a specific output that can be interpreted as a functional computation based upon specific initial conditions which serve as input. They differ, however, in what exactly serves as the output signal. In biochemical computers, the presence or concentration of certain chemicals serves as the output signal. In biomechanical computers, however, the mechanical shape of a specific molecule or set of molecules under a set of initial conditions serves as the output. Biomechanical computers rely on the nature of specific molecules to adopt certain physical configurations under certain chemical conditions. The mechanical, three-dimensional structure of the product of the biomechanical computer is detected and interpreted appropriately as a calculated output.

Biochemical Computers

Biochemical computers use the immense variety of feedback loops that are characteristic of biological chemical reactions in order to achieve computational functionality. Feedback loops in biological systems take many forms, and many different factors can provide both positive and negative feedback to a particular biochemical process, causing either an increase in chemical output or a decrease in chemical output, respectively. Such factors may include the quantity of catalytic enzymes present, the amount of reactants present, the amount of products present, and the presence of molecules that bind to and thus alter the chemical reactivity of any of the aforementioned factors. Given the nature of these biochemical systems to be regulated through many different mechanisms, one can engineer a chemical pathway comprising a set of molecular components that react to produce one particular product under one set of specific chemical conditions and another particular product under another set of conditions. The presence of the particular product that results from the pathway can serve as a signal, which can be interpreted, along with other chemical signals, as a computational output based upon the starting chemical conditions of the system, i.e. the input.

Scientific Background

Biocomputers utilize biologically derived materials to perform computational functions. A biocomputer consists of a pathway or series of metabolic pathways involving biological materials that are engineered to behave in a certain manner based upon the conditions (input) of the system. The resulting pathway of reactions that takes place constitutes an output, which is based on the engineering design of the biocomputer and can be interpreted as a form of computational analysis. Three distinguishable types of biocomputers include biochemical computers, biomechanical computers, and bioelectronic computers.

Thursday, March 6, 2008

What is Biocomputers?

Biocomputers utilize systems of biologically derived molecules, such as DNA and proteins, to perform computational calculations involving storing, retrieving, and processing data.
The development of biocomputers has been made possible by the expanding new science of nanobiotechnology. The term nanobiotechnology can be defined in multiple ways; in a more general sense, nanobiotechnology can be defined as any type of technology that utilizes both nano-scale materials, i.e. materials having characteristic dimensions of 1-100 nanometers, as well as biologically based materials (34).4 A more restrictive definition views nanobiotechnology more specifically as the design and engineering of proteins that can then be assembled into larger, functional structures (116-117) (9).³,1 The implementation of nanobiotechnology, as defined in this narrower sense, provides scientists with the ability to engineer biomolecular systems specifically so that they interact in a fashion that can ultimately result in the computational functionality of a computer.
The promising field of biocomputer research utilizes the science behind nano-sized biomaterials to create various forms of computational devices, which may have many potential applications in the future. One day, biocomputers utilizing nanobiotechnology may become the cheapest, most energy-efficient, most powerful, and most economical of any commercially available computer. Already, scientists are making significant headway in the advancement of this science