1.
Biochemistry
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Biochemistry, sometimes called biological chemistry, is the study of chemical processes within and relating to living organisms. By controlling information flow through biochemical signaling and the flow of energy through metabolism. Biochemistry is closely related to biology, the study of the molecular mechanisms by which genetic information encoded in DNA is able to result in the processes of life. Depending on the definition of the terms used, molecular biology can be thought of as a branch of biochemistry, or biochemistry as a tool with which to investigate. The chemistry of the cell depends on the reactions of smaller molecules. These can be inorganic, for water and metal ions, or organic, for example the amino acids. The mechanisms by which cells harness energy from their environment via chemical reactions are known as metabolism, the findings of biochemistry are applied primarily in medicine, nutrition, and agriculture. In medicine, biochemists investigate the causes and cures of diseases, in nutrition, they study how to maintain health and study the effects of nutritional deficiencies. In agriculture, biochemists investigate soil and fertilizers, and try to discover ways to improve crop cultivation, crop storage and pest control. However, biochemistry as a scientific discipline has its beginning sometime in the 19th century, or a little earlier. Gowland Hopkins on enzymes and the nature of biochemistry. The term biochemistry itself is derived from a combination of biology, the German chemist Carl Neuberg however is often cited to have coined the word in 1903, while some credited it to Franz Hofmeister. Then, in 1828, Friedrich Wöhler published a paper on the synthesis of urea and these techniques allowed for the discovery and detailed analysis of many molecules and metabolic pathways of the cell, such as glycolysis and the Krebs cycle. Another significant historic event in biochemistry is the discovery of the gene and this part of biochemistry is often called molecular biology. In the 1950s, James D. Watson, Francis Crick, Rosalind Franklin, in 1958, George Beadle and Edward Tatum received the Nobel Prize for work in fungi showing that one gene produces one enzyme. In 1988, Colin Pitchfork was the first person convicted of murder with DNA evidence, mello received the 2006 Nobel Prize for discovering the role of RNA interference, in the silencing of gene expression. Around two dozen of the 92 naturally occurring elements are essential to various kinds of biological life. Most rare elements on Earth are not needed by life, while a few common ones are not used, most organisms share element needs, but there are a few differences between plants and animals
2.
Enzyme
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Enzymes /ˈɛnzaɪmz/ are macromolecular biological catalysts. Enzymes accelerate, or catalyze, chemical reactions, the molecules at the beginning of the process upon which enzymes may act are called substrates and the enzyme converts these into different molecules, called products. Almost all metabolic processes in the cell need enzymes in order to occur at rates fast enough to sustain life, the set of enzymes made in a cell determines which metabolic pathways occur in that cell. The study of enzymes is called enzymology, enzymes are known to catalyze more than 5,000 biochemical reaction types. Most enzymes are proteins, although a few are catalytic RNA molecules, enzymes specificity comes from their unique three-dimensional structures. Like all catalysts, enzymes increase the rate of a reaction by lowering its activation energy, some enzymes can make their conversion of substrate to product occur many millions of times faster. An extreme example is orotidine 5-phosphate decarboxylase, which allows a reaction that would take millions of years to occur in milliseconds. Chemically, enzymes are like any catalyst and are not consumed in chemical reactions, enzymes differ from most other catalysts by being much more specific. Enzyme activity can be affected by other molecules, inhibitors are molecules that decrease enzyme activity, many drugs and poisons are enzyme inhibitors. An enzymes activity decreases markedly outside its optimal temperature and pH, some enzymes are used commercially, for example, in the synthesis of antibiotics. French chemist Anselme Payen was the first to discover an enzyme, diastase and he wrote that alcoholic fermentation is an act correlated with the life and organization of the yeast cells, not with the death or putrefaction of the cells. In 1877, German physiologist Wilhelm Kühne first used the term enzyme, the word enzyme was used later to refer to nonliving substances such as pepsin, and the word ferment was used to refer to chemical activity produced by living organisms. Eduard Buchner submitted his first paper on the study of yeast extracts in 1897, in a series of experiments at the University of Berlin, he found that sugar was fermented by yeast extracts even when there were no living yeast cells in the mixture. He named the enzyme that brought about the fermentation of sucrose zymase, in 1907, he received the Nobel Prize in Chemistry for his discovery of cell-free fermentation. Following Buchners example, enzymes are usually named according to the reaction they carry out, the biochemical identity of enzymes was still unknown in the early 1900s. Sumner showed that the enzyme urease was a protein and crystallized it. These three scientists were awarded the 1946 Nobel Prize in Chemistry, the discovery that enzymes could be crystallized eventually allowed their structures to be solved by x-ray crystallography. This high-resolution structure of lysozyme marked the beginning of the field of structural biology, an enzymes name is often derived from its substrate or the chemical reaction it catalyzes, with the word ending in -ase
3.
Active site
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In biology, the active site is the region of an enzyme where substrate molecules bind and undergo a chemical reaction. The active site consists of residues that form bonds with the substrate. The active site is usually a groove or pocket of the enzyme which can be located in a tunnel within the enzyme. An active site can catalyse a reaction repeatedly as its residues are not altered at the end of the reaction, usually, an enzyme molecule has only one active site, and the active site fits with one specific type of substrate. An active site contains a site that binds the substrate. Residues in the site form hydrogen bonds, hydrophobic interactions. In order to function, the site needs to be in a specific conformation. A tighter fit between a site and the substrate molecule is believed to increase efficiency of a reaction. Most enzymes have deeply buried active sites, which can be accessed by a substrate via access channels, there are two proposed models of how enzymes fit to their specific substrate, the lock and key model and the induced fit model. Emil Fischers lock and key model assumes that the site is a perfect fit for a specific substrate. Daniel Koshlands theory of enzyme-substrate binding is that the active site, the induced fit model is a development of the lock-and-key model and assumes that an active site is flexible and it changes shape until the substrate is completely bound. The substrate is thought to induce a change in the shape of the active site, the hypothesis also predicts that the presence of certain residues in the active site will encourage the enzyme to locate the correct substrate. Conformational changes may occur as the substrate is bound. After the products of the move away from the enzyme. Once the substrate is bound and oriented in the active site, the residues of the catalytic site are typically very close to the binding site, and some residues can have dual-roles in both binding and catalysis. Catalytic residues of the site interact with the substrate to lower the energy of a reaction. They do this by a number of different mechanisms, firstly, they can act as donors or acceptors of protons or other groups on the substrate to facilitate the reaction. They can also form electrostatic interactions to stabilise charge buildup on the state or leaving group
4.
Protein dynamics
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Proteins are generally thought to adopt unique structures determined by their amino acid sequences, as outlined by Anfinsens dogma. However, proteins are not strictly static objects, but rather populate ensembles of conformations, transitions between these states occur on a variety of length scales and time scales, and have been linked to functionally relevant phenomena such as allosteric signaling and enzyme catalysis. The study of dynamics is most directly concerned with the transitions between these states, but can also involve the nature and equilibrium populations of the states themselves. Portions of protein structures often deviate from the equilibrium state, some such excursions are harmonic, such as stochastic fluctuations of chemical bonds and bond angles. Others are anharmonic, such as sidechains that jump between separate discrete energy minima, or rotamers, evidence for local flexibility is often obtained from NMR spectroscopy. Flexible and potentially disordered regions of a protein can be detected using the random coil index, flexibility in folded proteins can be identified by analyzing the spin relaxation of individual atoms in the protein. Many residues are in spatial proximity in protein structures. This is true for most residues that are contiguous in the primary sequence, because of this proximity, these residuess energy landscapes become coupled based on various biophysical phenomena such as hydrogen bonds, ionic bonds, and van der Waals interactions. Transitions between states for such sets of residues therefore become correlated and this is perhaps most obvious for surface-exposed loops, which often shift collectively to adopt different conformations in different crystal structures. However, coupled conformational heterogeneity is also evident in secondary structure. For example, consecutive residues and residues offset by 4 in the sequence often interact in α helices. When these coupled residues form pathways linking functionally important parts of a protein, the presence of multiple domains in proteins gives rise to a great deal of flexibility and mobility, leading to protein domain dynamics. Domain motions can be inferred by comparing different structures of a protein and they can also be suggested by sampling in extensive molecular dynamics trajectories and principal component analysis. The phosphoinositide domain swivels between two states in order to bring a group from the active site of the nucleotide binding domain to that of the phosphoenolpyruvate/pyruvate domain. The phosphate group is moved over a distance of 45 Å involving a domain motion of about 100 degrees around a single residue. In enzymes, the closure of one domain onto another captures a substrate by an induced fit, a detailed analysis by Gerstein led to the classification of two basic types of domain motion, hinge and shear. Only a relatively small portion of the chain, namely the inter-domain linker, a study by Hayward found that the termini of α-helices and β-sheets form hinges in a large number of cases. Many hinges were found to two secondary structure elements acting like hinges of a door, allowing an opening and closing motion to occur
5.
Feedback
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Feedback occurs when outputs of a system are routed back as inputs as part of a chain of cause-and-effect that forms a circuit or loop. The system can then be said to feed back into itself and this makes reasoning based upon cause and effect tricky, and it is necessary to analyze the system as a whole. This action of feeding back of the signal output to input gave rise to the use of the term feedback as a distinct word by 1920. Over the years there has been dispute as to the best definition of feedback. According to Ashby, mathematicians and theorists interested in the principles of feedback mechanisms prefer the definition of circularity of action, for those with more practical aims, feedback should be a deliberate effect via some more tangible connection. Object to the definition, pointing out that this would force them to say that feedback was present in the ordinary pendulum. Between its position and its momentum—a feedback that, from the point of view, is somewhat mystical. He emphasizes that the information by itself is not feedback unless translated into action, there are two types of feedback, positive feedback and negative feedback. As an example of feedback, the diagram might represent a cruise control system in a car, for example. The controlled system is the car, its input includes the combined torque from the engine, the cars speed is measured by a speedometer. The error signal is the departure of the speed as measured by the speedometer from the target speed and this measured error is interpreted by the controller to adjust the accelerator, commanding the fuel flow to the engine. The resulting change in torque, the feedback, combines with the torque exerted by the changing road grade to reduce the error in speed. The terms positive and negative were first applied to prior to WWII. The idea of positive feedback was already current in the 1920s with the introduction of the regenerative circuit, harold Stephen Blacks classic 1934 paper first details the use of negative feedback in electronic amplifiers. According to Black, Positive feed-back increases the gain of the amplifier, according to Mindell confusion in the terms arose shortly after this. In contrast, Nyquist and Bode, when built on Black’s work. Black had trouble convincing others of the utility of his invention in part because confusion existed over basic matters of definition, the terms positive and negative feedback are defined in different ways within different disciplines. The altering of the gap between reference and actual values of a parameter, based on whether the gap is widening or narrowing
6.
Feed forward (control)
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In a feed-forward system, the control variable adjustment is not error-based. Instead it is based on knowledge about the process in the form of a model of the process. In contrast cruise control adjusts the output in response to the load that it encounters and these systems could relate to control theory, physiology or computing. With feed-forward control, the disturbances are measured and accounted for before they have time to affect the system, in the house example, a feed-forward system may measure the fact that the door is opened and automatically turn on the heater before the house can get too cold. The difficulty with feed-forward control is that the effects of the disturbances on the system must be accurately predicted, for instance, if a window was opened that was not being measured, the feed-forward-controlled thermostat might still let the house cool down. The term has specific meaning within the field of CPU-based automatic control, open-loop control and feedback control, often based on canned PID control algorithms, are much more widely used. There are three types of systems, open loop, feed-forward, and feedback. In comparison, power steering has access to an auxiliary power source. When the steering wheel is turned, a valve is opened which allows fluid under pressure to turn the driving wheels, a sensor monitors that pressure so that the valve only opens enough to cause the correct pressure to reach the wheel turning mechanism. This is feed-forward control where the output of the system, the change in direction of travel of the vehicle, plays no part in the system. If you include the driver in the system, then he does provide a path by observing the direction of travel. In that case you have a system, and the block labeled System in Figure is a feed-forward system. In other words, systems of different types can be nested, Feedforward control is distinctly different from open loop control and teleoperator systems. Feedforward control requires a model of the plant and the plants relationship to any inputs or feedback the system might receive. Neither open loop control nor teleoperator systems require the sophistication of a model of the physical system or plant being controlled. Control based on operator input without integral processing and interpretation through a model of the system is a teleoperator system and is not considered feedforward control. Historically, the use of the term “feedforward” is found in works by D. M. MacKay as early as 1956, while MacKay’s work is in the field of biological control theory, he speaks only of feedforward systems. MacKay does not mention “Feedforward Control” or allude to the discipline of “Feedforward Controls. ”MacKay, the discipline of “feedforward controls” was largely developed by professors and graduate students at Georgia Tech, MIT, Stanford and Carnegie Mellon
7.
Cell signaling
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Cell signaling is part of any communication process that governs basic activities of cells and coordinates all cell actions. The ability of cells to perceive and correctly respond to their microenvironment is the basis of development, tissue repair, errors in signaling interactions and cellular information processing are responsible for diseases such as cancer, autoimmunity, and diabetes. By understanding cell signaling, diseases may be treated effectively and, theoretically. Traditional work in biology has focused on studying individual parts of cell signaling pathways, systems biology research helps us to understand the underlying structure of cell signaling networks and how changes in these networks may affect the transmission and flow of information. Such networks are complex systems in their organization and may exhibit a number of emergent properties including bistability and ultrasensitivity, analysis of cell signaling networks requires a combination of experimental and theoretical approaches including the development and analysis of simulations and modeling. Long-range allostery is often a significant component of signaling events. Cell signaling has been most extensively studied in the context of human diseases, however, cell signaling may also occur between the cells of two different organisms. In many mammals, early embryo cells exchange signals with cells of the uterus, in the human gastrointestinal tract, bacteria exchange signals with each other and with human epithelial and immune system cells. For the yeast Saccharomyces cerevisiae during mating, some cells send a signal into their environment. The mating factor peptide may bind to a surface receptor on other yeast cells. Cell signaling can be classified to be mechanical and biochemical based on the type of the signal, mechanical signals are the forces exerted on the cell and the forces produced by the cell. These forces can both be sensed and responded by the cells, biochemical signals are the biochemical molecules such as proteins, lipids, ions and gases. These signals can be categorized based on the distance between signaling and responder cells, Signaling within, between, and amongst cells is subdivided into the following classifications, Intracrine signals are produced by the target cell that stay within the target cell. Autocrine signals are produced by the cell, are secreted. Sometimes autocrine cells can target cells close by if they are the type of cell as the emitting cell. An example of this are immune cells and these signals are transmitted along cell membranes via protein or lipid components integral to the membrane and are capable of affecting either the emitting cell or cells immediately adjacent. Paracrine signals target cells in the vicinity of the emitting cell, endocrine cells produce hormones that travel through the blood to reach all parts of the body. Cells communicate with each other via direct contact, over short distances, some cell–cell communication requires direct cell–cell contact
8.
Cell (biology)
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The cell is the basic structural, functional, and biological unit of all known living organisms. A cell is the smallest unit of life that can replicate independently, the study of cells is called cell biology. Cells consist of cytoplasm enclosed within a membrane, which contains many such as proteins. Organisms can be classified as unicellular or multicellular, while the number of cells in plants and animals varies from species to species, humans contain more than 10 trillion cells. Most plant and animal cells are only under a microscope. The cell was discovered by Robert Hooke in 1665, who named the unit for its resemblance to cells inhabited by Christian monks in a monastery. Cells emerged on Earth at least 3.5 billion years ago, Cells are of two types, eukaryotic, which contain a nucleus, and prokaryotic, which do not. Prokaryotes are single-celled organisms, while eukaryotes can be either single-celled or multicellular, prokaryotic cells were the first form of life on Earth, characterised by having vital biological processes including cell signaling and being self-sustaining. They are simpler and smaller than eukaryotic cells, and lack membrane-bound organelles such as the nucleus, prokaryotes include two of the domains of life, bacteria and archaea. The DNA of a prokaryotic cell consists of a chromosome that is in direct contact with the cytoplasm. The nuclear region in the cytoplasm is called the nucleoid, most prokaryotes are the smallest of all organisms ranging from 0.5 to 2.0 µm in diameter. Though most prokaryotes have both a cell membrane and a wall, there are exceptions such as Mycoplasma and Thermoplasma which only possess the cell membrane layer. The envelope gives rigidity to the cell and separates the interior of the cell from its environment, the cell wall consists of peptidoglycan in bacteria, and acts as an additional barrier against exterior forces. It also prevents the cell from expanding and bursting from osmotic pressure due to a hypotonic environment, some eukaryotic cells also have a cell wall. Inside the cell is the region that contains the genome, ribosomes. The genetic material is found in the cytoplasm. Prokaryotes can carry extrachromosomal DNA elements called plasmids, which are usually circular, linear bacterial plasmids have been identified in several species of spirochete bacteria, including members of the genus Borrelia notably Borrelia burgdorferi, which causes Lyme disease. Though not forming a nucleus, the DNA is condensed in a nucleoid, plasmids encode additional genes, such as antibiotic resistance genes
9.
Greek language
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Greek is an independent branch of the Indo-European family of languages, native to Greece and other parts of the Eastern Mediterranean. It has the longest documented history of any living language, spanning 34 centuries of written records and its writing system has been the Greek alphabet for the major part of its history, other systems, such as Linear B and the Cypriot syllabary, were used previously. The alphabet arose from the Phoenician script and was in turn the basis of the Latin, Cyrillic, Armenian, Coptic, Gothic and many other writing systems. Together with the Latin texts and traditions of the Roman world, during antiquity, Greek was a widely spoken lingua franca in the Mediterranean world and many places beyond. It would eventually become the official parlance of the Byzantine Empire, the language is spoken by at least 13.2 million people today in Greece, Cyprus, Italy, Albania, Turkey, and the Greek diaspora. Greek roots are used to coin new words for other languages, Greek. Greek has been spoken in the Balkan peninsula since around the 3rd millennium BC, the earliest written evidence is a Linear B clay tablet found in Messenia that dates to between 1450 and 1350 BC, making Greek the worlds oldest recorded living language. Among the Indo-European languages, its date of earliest written attestation is matched only by the now extinct Anatolian languages, the Greek language is conventionally divided into the following periods, Proto-Greek, the unrecorded but assumed last ancestor of all known varieties of Greek. The unity of Proto-Greek would have ended as Hellenic migrants entered the Greek peninsula sometime in the Neolithic era or the Bronze Age, Mycenaean Greek, the language of the Mycenaean civilisation. It is recorded in the Linear B script on tablets dating from the 15th century BC onwards, Ancient Greek, in its various dialects, the language of the Archaic and Classical periods of the ancient Greek civilisation. It was widely known throughout the Roman Empire, after the Roman conquest of Greece, an unofficial bilingualism of Greek and Latin was established in the city of Rome and Koine Greek became a first or second language in the Roman Empire. The origin of Christianity can also be traced through Koine Greek, Medieval Greek, also known as Byzantine Greek, the continuation of Koine Greek in Byzantine Greece, up to the demise of the Byzantine Empire in the 15th century. Much of the written Greek that was used as the language of the Byzantine Empire was an eclectic middle-ground variety based on the tradition of written Koine. Modern Greek, Stemming from Medieval Greek, Modern Greek usages can be traced in the Byzantine period and it is the language used by the modern Greeks, and, apart from Standard Modern Greek, there are several dialects of it. In the modern era, the Greek language entered a state of diglossia, the historical unity and continuing identity between the various stages of the Greek language is often emphasised. Greek speakers today still tend to regard literary works of ancient Greek as part of their own rather than a foreign language and it is also often stated that the historical changes have been relatively slight compared with some other languages. According to one estimation, Homeric Greek is probably closer to demotic than 12-century Middle English is to modern spoken English, Greek is spoken by about 13 million people, mainly in Greece, Albania and Cyprus, but also worldwide by the large Greek diaspora. Greek is the language of Greece, where it is spoken by almost the entire population
10.
Enzyme inhibitor
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An enzyme inhibitor is a molecule that binds to an enzyme and decreases its activity. Since blocking an enzymes activity can kill a pathogen or correct a metabolic imbalance and they are also used in pesticides. The binding of an inhibitor can stop a substrate from entering the active site and/or hinder the enzyme from catalyzing its reaction. Inhibitor binding is reversible or irreversible. Irreversible inhibitors usually react with the enzyme and change it chemically and these inhibitors modify key amino acid residues needed for enzymatic activity. In contrast, reversible inhibitors bind non-covalently and different types of inhibition are produced depending on whether these inhibitors bind to the enzyme, many drug molecules are enzyme inhibitors, so their discovery and improvement is an active area of research in biochemistry and pharmacology. A medicinal enzyme inhibitor is often judged by its specificity and its potency, a high specificity and potency ensure that a drug will have few side effects and thus low toxicity. Enzyme inhibitors also occur naturally and are involved in the regulation of metabolism, for example, enzymes in a metabolic pathway can be inhibited by downstream products. This type of negative feedback slows the production line when products begin to build up and is an important way to maintain homeostasis in a cell, other cellular enzyme inhibitors are proteins that specifically bind to and inhibit an enzyme target. This can help control enzymes that may be damaging to a cell, a well-characterised example of this is the ribonuclease inhibitor, which binds to ribonucleases in one of the tightest known protein–protein interactions. Natural enzyme inhibitors can also be poisons and are used as defences against predators or as ways of killing prey, reversible inhibitors attach to enzymes with non-covalent interactions such as hydrogen bonds, hydrophobic interactions and ionic bonds. Multiple weak bonds between the inhibitor and the active site combine to produce strong and specific binding, in contrast to substrates and irreversible inhibitors, reversible inhibitors generally do not undergo chemical reactions when bound to the enzyme and can be easily removed by dilution or dialysis. There are four kinds of reversible enzyme inhibitors and they are classified according to the effect of varying the concentration of the enzymes substrate on the inhibitor. In competitive inhibition, the substrate and inhibitor cannot bind to the enzyme at the same time, as shown in the figure on the right. This usually results from the inhibitor having an affinity for the site of an enzyme where the substrate also binds. This type of inhibition can be overcome by high concentrations of substrate. However, the apparent Km will increase as it takes a higher concentration of the substrate to reach the Km point, competitive inhibitors are often similar in structure to the real substrate. In uncompetitive inhibition, the inhibitor binds only to the substrate-enzyme complex and this type of inhibition causes Vmax to decrease and Km to decrease
11.
Monod-Wyman-Changeux model
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In biochemistry, the Monod-Wyman-Changeux model describes allosteric transitions of proteins made up of identical subunits. It was proposed by Jean-Pierre Changeux based on his PhD experiments, and described by Jacques Monod, Jeffries Wyman and it stands in opposition to the sequential model. The ratio of the different conformational states is determined by thermal equilibrium and this model, alternatively termed the MWC model, is defined by the following rules, An allosteric protein is an oligomer of protomers that are symmetrically related. Each protomer can exist in two states, designated T and R, these states are in equilibrium whether or not ligand is bound to the oligomer. The ligand can bind to a protomer in either conformation, only the conformational change alters the affinity of a protomer for the ligand. The regulators merely shift the equilibrium toward one state or another, for instance, an agonist will stabilize the active form of a pharmacological receptor. Phenomenologically, it looks as if the agonist provokes the conformational transition, one crucial feature of the model is the dissociation between the binding function, and the state function, cf below. In the models said of induced-fit, those functions are identical, in the historical model, each allosteric unit, called a protomer, can exist in two different conformational states - designated R or T states. In any one molecule, all protomers must be in the same state and that is to say, all subunits must be in either the R or the T state. Proteins with subunits in different states are not allowed by this model, the R state has a higher affinity for the ligand than the T state. Because of that, although the ligand may bind to the subunit when it is in either state, the MWC model proved very popular in enzymology, and pharmacology, although it has been shown inappropriate in a certain number of cases. The best example of an application of the model is the regulation of hemoglobin function. Extension of the model have been proposed for lattices of proteins, for instance by Changeux, Thiery, Tung and Kittel, by Wyman or by Duke, Le Novere, allosteric interactions interpreted in terms of quaternary structure. Brookhaven Symposia in Biology,17, 232-249, Monod J. Wyman J. and Changeux J. -P. On the nature of transitions, a plausible model. On the cooperativity of biological membranes, PNAS57, 335-341 Wyman J. Possible allosteric effects in extended biological systems. Extensions of the model for haemoglobin. Duke TA, Le Novere N, Bray D, conformational spread in a ring of proteins, a stochastic approach to allostery
12.
Jean-Pierre Changeux
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Changeux is known by the non-scientific public for his ideas regarding the connection between mind and physical brain. Changeux was born in Domont, France and he entered the École Normale Supérieure in 1955, where he obtained a Bachelors degree in 1957 and a Masters degree in 1958. He also received his agrégation in natural science the same year and he began his scientific career during his ENS years during summer internships in Banyuls-sur-Mer where he identified a new genus of parasitic Copepod. He pursued PhD studies at the Pasteur Institute under the direction of Jacques Monod and Francois Jacob, Changeux then left France for postdoctoral studies first at the University of California Berkeley then at Columbia University College of Physicians and Surgeons, New-York. He returned to France as attaché to the chair of Molecular Biology held by Jacques Monod, in 1972, he became director of the Unit of Molecular Neurobiology at the Pasteur Institute, where he received a professorship in 1975. In 1975, Changeux was elected professor at the Collège de France, chair of Cell Communications, Changeux is author of more than 600 scientific articles and several books, technical or for general audience. All his scientific career, Changeux has been faithful to a handful of scientific questions, at molecular, cellular, if one needs to seek a unifying theme to all of them, it is the conviction that selection is the basis of life processes, rather than instruction. This work led to the development of the model of concerted transitions for allosteric proteins, the main ideas behind this theory are, 1) proteins can exist under various conformations in thermal equilibrium in the absence of regulators. The resulting model explains the observed cooperativity without a change of biophysical parameters. This conceptual framework is still the model used to explain the function of cooperative proteins such as hemoglobin. More than forty years of research would follow, mainly focussed on nicotinic acetylcholine receptors, in 1967, Changeux extended the MWC model to bi-dimensional lattice of receptors. He then applied this idea to the membrane of electric organs. The transitions between the states followed different kinetics, and those kinetics plus the differential affinities sufficed to explain the shape of the post-synaptic potential. In addition to the modulation of the channel gating by the agonists. The concept of an allosteric pharmacology for ion channels was developed over the years, the isolation of the receptor was also later reported by Ricardo Miledi. The improvements of methods developed in the group allowed the proposition that the receptor was a pentameric protein. The group of Changeux was among the firsts to elucidate the structure of the subunits of the receptor, in parallel with the group of Shosaku Numa. Throughout the 1980s and 1990s, molecular biology technics were used to decipher the tertiary and quaternary structures of the receptor
13.
Protein subunit
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In structural biology, a protein subunit is a single protein molecule that assembles with other protein molecules to form a protein complex. Some naturally occurring proteins have a small number of subunits and therefore described as oligomeric. Others may consist from a large number of subunits and therefore described as multimeric, for example microtubules. The subunits of a protein may be identical, homologous or totally dissimilar. In some protein assemblies, one subunit may be a subunit that enzymatically catalyzes a reaction. Although telomerase has telomerase reverse transcriptase as a subunit, regulation is accomplished by factors outside of the protein. An enzyme composed of regulatory and catalytic subunits when assembled is often referred to as a holoenzyme. For example, class I phosphoinositide 3-kinase is composed of a catalytic subunit. One subunit is made of one polypeptide chain, a polypeptide chain has one gene coding for it – meaning that a protein must have one gene for each unique subunit. A subunit is often named with a Greek or Roman letter, for example, ATP synthase has a type of subunit called α. Three of these are present in the ATP synthase molecule, and is therefore designated α3, larger groups of subunits can also the specified, like α3β3-hexamer and c-ring. A subunit vaccine presents an antigen to the system without introducing viral particles. One method of production involves isolation of a protein from a virus. A weakness of this technique is that proteins can be denatured. The recombinant vector that is genomically modified will express the antigen, the antigen is extracted from the vector. Just like the highly successful subunit vaccines, the antigen will be of little to no risk to the patient. Vi capsular polysaccharide vaccine is another subunit vaccine, in this case and it is also called a conjugate vaccine, in which a polysaccharide antigen has been covalently attached to a carrier protein for T-cell-dependent antigen processing. Protein quaternary structure Allostery Cooperativity Monomer Dilip Gore, Reecha Pandit, in silico Identification of Cell Surface Antigens in Neisseria meningitidis
14.
Protein structure
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Protein structure is the three-dimensional arrangement of atoms in a protein molecule. Proteins are polymers — specifically polypeptides — formed from sequences of amino acids, a single amino acid monomer may also be called a residue indicating a repeating unit of a polymer. Proteins form by amino acids undergoing condensation reactions, in which the amino acids lose one water molecule per reaction in order to attach to one another with a peptide bond. By convention, a chain under 30 amino acids is often identified as a peptide, to understand the functions of proteins at a molecular level, it is often necessary to determine their three-dimensional structure. Protein structures range in size from tens to several amino acids. By physical size, proteins are classified as nanoparticles, between 1–100 nm, very large aggregates can be formed from protein subunits. For example, many thousands of actin molecules assemble into a microfilament, a protein may undergo reversible structural changes in performing its biological function. The alternative structures of the protein are referred to as different conformational isomers, or simply, conformations. There are four levels of protein structure. Each α-amino acid consists of a backbone that is present in all the amino acid types, an exception from this rule is proline. Because the carbon atom is bound to four different groups it is chiral, glycine however, is not chiral since its side chain is a hydrogen atom. A simple mnemonic for correct L-form is CORN, when the Cα atom is viewed with the H in front, the primary structure of a protein refers to the linear sequence of amino acids in the polypeptide chain. The primary structure is held together by covalent bonds such as peptide bonds, the two ends of the polypeptide chain are referred to as the carboxyl terminus and the amino terminus based on the nature of the free group on each extremity. Counting of residues always starts at the N-terminal end, which is the end where the group is not involved in a peptide bond. The primary structure of a protein is determined by the corresponding to the protein. A specific sequence of nucleotides in DNA is transcribed into mRNA, the sequence of amino acids in insulin was discovered by Frederick Sanger, establishing that proteins have defining amino acid sequences. The sequence of a protein is unique to that protein, and defines the structure, the sequence of a protein can be determined by methods such as Edman degradation or tandem mass spectrometry. Often, however, it is directly from the sequence of the gene using the genetic code
15.
Ligand (biochemistry)
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In biochemistry and pharmacology, a ligand is a substance that forms a complex with a biomolecule to serve a biological purpose. In protein-ligand binding, the ligand is usually a molecule which produces a signal by binding to a site on a target protein, the binding typically results in a change of conformation of the target protein. In DNA-ligand binding studies, the ligand can be a molecule, ion. The relationship between ligand and binding partner is a function of charge, hydrophobicity, and molecular structure, the instance of binding occurs over an infinitesimal range of time and space, so the rate constant is usually a very small number. Binding occurs by intermolecular forces, such as bonds, hydrogen bonds. The association of docking is actually reversible through dissociation, measurably irreversible covalent bonding between a ligand and target molecule is atypical in biological systems. In contrast to the definition of ligand in metalorganic and inorganic chemistry, in biochemistry it is whether the ligand generally binds at a metal site. In general, the interpretation of ligand is contextual with regards to what sort of binding has been observed, the etymology stems from ligare, which means to bind. Ligand binding to a receptor protein alters the chemical conformation by affecting the shape orientation. The conformation of a receptor protein composes the functional state, ligands include substrates, inhibitors, activators, and neurotransmitters. The rate of binding is called affinity, and this measurement typifies a tendency or strength of the effect, binding affinity is actualized not only by host-guest interactions, but also by solvent effects that can play a dominant, steric role which drives non-covalent binding in solution. The solvent provides an environment for the ligand and receptor to adapt. Radioligands are radioisotope labeled compounds are used in vivo as tracers in PET studies, the interaction of most ligands with their binding sites can be characterized in terms of a binding affinity. In general, high-affinity binding results in a degree of occupancy for the ligand at its receptor binding site than is the case for low-affinity binding. A ligand that can bind to a receptor, alter the function of the receptor, high-affinity ligand binding implies that a relatively low concentration of a ligand is adequate to maximally occupy a ligand-binding site and trigger a physiological response. The lower the Ki concentration is, the more likely there will be a reaction between the pending ion and the receptive antigen. In the example shown to the right, two different ligands bind to the receptor binding site. Only one of the agonists shown can maximally stimulate the receptor and, thus, an agonist that can only partially activate the physiological response is called a partial agonist
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Enzyme catalysis
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Enzyme catalysis is the increase in the rate of a chemical reaction by the active site of a protein. The protein catalyst may be part of a complex, and/or may transiently or permanently associate with a Cofactor. Catalysis of biochemical reactions in the cell is vital due to the very low rates of the uncatalysed reactions at room temperature and pressure. A key driver of protein evolution is the optimization of such catalytic activities via protein dynamics, the mechanism of enzyme catalysis is similar in principle to other types of chemical catalysis. By providing an alternative reaction route the enzyme reduces the required to reach the highest energy transition state of the reaction. The reduction of activation increases the amount of reactant molecules that achieve a sufficient level of energy, such that they reach the activation energy. As with other catalysts, the enzyme is not consumed during the reaction but is recycled such that a single enzyme performs many rounds of catalysis, the favored model for the enzyme-substrate interaction is the induced fit model. The advantages of the induced fit mechanism arise due to the effect of strong enzyme binding. There are two different mechanisms of substrate binding, uniform binding, which has strong binding, and differential binding. The stabilizing effect of uniform binding increases both substrate and transition state binding affinity, while differential binding increases only transition state binding affinity, both are used by enzymes and have been evolutionarily chosen to minimize the activation energy of the reaction. It is important to clarify, however, that the induced fit concept cannot be used to rationalize catalysis and that is, the chemical catalysis is defined as the reduction of Ea‡ relative to Ea‡ in the uncatalyzed reaction in water. The induced fit only suggests that the barrier is lower in the form of the enzyme. Induced fit may be beneficial to the fidelity of molecular recognition in the presence of competition, →→→editor These conformational changes also bring catalytic residues in the active site close to the chemical bonds in the substrate that will be altered in the reaction. After binding takes place, one or more mechanisms of catalysis lowers the energy of the transition state. This effect is analogous to an increase in concentration of the reagents. The binding of the reagents to the enzyme gives the reaction intramolecular character, however, the situation might be more complex, since modern computational studies have established that traditional examples of proximity effects cannot be related directly to enzyme entropic effects. Also, the original proposal has been found to largely overestimate the contribution of orientation entropy to catalysis. Histidine is often the residue involved in these reactions, since it has a pKa close to neutral pH
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Morpheein
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Morpheeins are proteins that can form two or more different homo-oligomers, but must come apart and change shape to convert between forms. The alternate shape may reassemble to a different oligomer, the shape of the subunit dictates which oligomer is formed. Each oligomer has a number of subunits. Morpheeins can interconvert between forms under physiological conditions and can exist as an equilibrium of different oligomers and these oligomers are physiologically relevant and are not misfolded protein, this distinguishes morpheeins from prions and amyloid. The different oligomers have distinct functionality, interconversion of morpheein forms can be a structural basis for allosteric regulation. A mutation that shifts the equilibrium of morpheein forms can serve as the basis for a conformational disease. Features of morpheeins can be exploited for drug discovery, the dice image represents a morpheein equilibrium containing two different monomeric shapes that dictate assembly to a tetramer or a pentamer. The one protein that is established to function as a morpheein is porphobilinogen synthase, conformational differences between subunits of different oligomers and related functional differences of a morpheein provide a starting point for drug discovery. Protein function is dependent on the form, therefore, the protein’s function can be regulated by shifting the equilibrium of forms. A small molecule compound can shift the equilibrium either by blocking or favoring formation of one of the oligomers, the equilibrium can be shifted using a small molecule that has a preferential binding affinity for only one of the alternate morpheein forms. An inhibitor of porphobilinogen synthase with this mechanism of action has been documented, the morpheein model of allosteric regulation has similarities to and differences from other models. The concerted model of allosteric regulation requires all subunits to be in the conformation or state within an oligomer like the morpheein model. However, neither this nor the sequential model takes into account that the protein may dissociate to interconvert between oligomers. It is generally taught that an amino acid sequence will have only one physiologically relevant quaternary structure. The morpheein model does not require changes in the basic protein fold. The conformational differences that accompany conversion between oligomers may be similar to the motions necessary for function of some proteins. The term conformational disease generally encompasses mutations that result in misfolded proteins that aggregate, such as Alzheimer’s, in light of the discovery of morpheeins, however, this definition could be expanded to include mutations that shift an equilibrium of alternate oligomeric forms of a protein. An example of such a disease is ALAD porphyria, which results from a mutation of porphobilinogen synthase that causes a shift in its morpheein equilibrium
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Porphobilinogen synthase
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Porphobilinogen synthase synthesizes porphobilinogen through the asymmetric condensation of two molecules of aminolevulinic acid. All natural tetrapyrroles, including hemes, chlorophylls and vitamin B12, porphobilinogen synthase is the prototype morpheein. The * represents a reorientation between two domains of each subunit that occurs in the state because it is sterically forbidden in the larger multimers. PBGS is encoded by a gene and each PBGS multimer is composed of multiple copies of the same protein. Each PBGS subunit consists of a ~300 residue αβ-barrel domain, which houses the enzymes active site in its center, allosteric regulation of PBGS can be described in terms of the orientation of the αβ-barrel domain with respect to the N-terminal arm domain. Each N-terminal arm has up to two interactions with subunits in a PBGS multimer. One of these interactions helps to stabilize a conformation of the active site lid. The other interaction restricts solvent access from the end of the αβ-barrel. As a nearly universal enzyme with a conserved active site. To the contrary, allosteric sites can be much more variable than active sites. Phylogenetic variation in PBGS allostery leads to the framing of discussion of PBGS allosteric regulation in terms of intrinsic and extrinsic factors, the allosteric magnesium ion lies at the highly hydrated interface of two pro-octamer dimers. It appears to be easily dissociable, and it has shown that hexamers accumulate when magnesium is removed in vitro. Inspection of the PBGS 6mer* reveals a surface cavity that is not present in the 8mer, small molecule binding to this phylogenetically variable cavity has been proposed to stabilize 6mer* of the targeted PBGS and consequently inhibit activity. Such allosteric regulators are known as morphlocks because they lock PBGS in a specific morpheein form, a deficiency of porphobilinogen synthase is usually acquired and can be caused by heavy metal poisoning, especially lead poisoning, as the enzyme is very susceptible to inhibition by heavy metals. Hereditary insufficiency of porphobilinogen synthase is called porphobilinogen synthase deficiency poprhyria and it is an extremely rare cause of porphyria, with less than 10 cases ever reported. All disease associated protein variants favor hexamer formation relative to the wild type human enzyme, lead poisoning works on the cellular level by binding to this enzyme, rendering it useless. Delta-Aminolevulinic Acid Dehydratase at the US National Library of Medicine Medical Subject Headings http, //www. omim. org/entry/125270. search=pbgs&highlight=pbgs
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Statistical ensemble (mathematical physics)
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In mathematical physics, especially as introduced into statistical mechanics and thermodynamics by J. In other words, an ensemble is a probability distribution for the state of the system. The concept of an equilibrium or stationary ensemble is crucial to many applications of statistical ensembles, although a mechanical system certainly evolves over time, the ensemble does not necessarily have to evolve. In fact, the ensemble will not evolve if it contains all past, such a statistical ensemble, one that does not change over time, is called stationary and can said to be in statistical equilibrium. The word ensemble is used for a smaller set of possibilities sampled from the full set of possible states. For example, a collection of walkers in a Markov chain Monte Carlo iteration is called an ensemble in some of the literature, the term ensemble is often used in physics and the physics-influenced literature. In probability theory, the probability space is more prevalent. The study of thermodynamics is concerned with systems which appear to human perception to be static, and these systems can be described by statistical ensembles that depend on a few observable parameters, and which are in statistical equilibrium. Gibbs noted that different macroscopic constraints lead to different types of ensembles, the system must remain totally isolated in order to stay in statistical equilibrium. Canonical ensemble or NVT ensemble—a statistical ensemble where the energy is not known exactly, in place of the energy, the temperature is specified. The canonical ensemble is appropriate for describing a system which is in, or has been in. In order to be in equilibrium the system must remain totally closed. Grand canonical ensemble or µVT ensemble—a statistical ensemble where neither the energy nor particle number are fixed, in their place, the temperature and chemical potential are specified. The grand canonical ensemble is appropriate for describing a system, one which is in, or has been in. The ensemble remains in equilibrium if the system comes into weak contact with other systems that are described by ensembles with the same temperature. The calculations that can be made using each of these ensembles are explored further in their respective articles, other thermodynamic ensembles can be also defined, corresponding to different physical requirements, for which analogous formulae can often similarly be derived. The precise mathematical expression for an ensemble has a distinct form depending on the type of mechanics under consideration. In the classical case the ensemble is a probability distribution over the microstates, in quantum mechanics this notion, due to von Neumann, is a way of assigning a probability distribution over the results of each complete set of commuting observables
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Molecular dynamics
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Molecular dynamics is a computer simulation method for studying the physical movements of atoms and molecules, and is thus a type of N-body simulation. The atoms and molecules are allowed to interact for a period of time. The method was developed within the field of theoretical physics in the late 1950s but is applied today mostly in chemical physics, materials science. Following the earlier successes of Monte Carlo simulations, the method was developed by Fermi, Pasta, in 1957, Alder and Wainwright used an IBM704 computer to simulate perfectly elastic collisions between hard spheres. In 1960, Gibson et al. simulated radiation damage of solid copper by using a Born-Mayer type of repulsive interaction along with a surface force. In 1964, Rahman published landmark simulations of liquid argon that used a Lennard-Jones potential, calculations of system properties, such as the coefficient of self-diffusion, compared well with experimental data. Even before it became possible to simulate molecular dynamics with computers, the idea was to arrange them to replicate the properties of a liquid. I took a number of balls and stuck them together with rods of a selection of different lengths ranging from 2.75 to 4 inches. I tried to do this in the first place as casually as possible, working in my own office, being interrupted every five minutes or so and not remembering what I had done before the interruption. In physics, MD is used to examine the dynamics of atomic-level phenomena that cannot be observed directly, such as thin film growth and it is also used to examine the physical properties of nanotechnological devices that have not been or cannot yet be created. In principle MD can be used for ab initio prediction of protein structure by simulating folding of the chain from random coil. The results of MD simulations can be tested through comparison to experiments that measure molecular dynamics, michael Levitt, who shared the Nobel Prize awarded in part for the application of MD to proteins, wrote in 1999 that CASP participants usually did not use the method due to. A central embarrassment of molecular mechanics, namely that energy minimization or molecular dynamics generally leads to a model that is less like the experimental structure, limits of the method are related to the parameter sets used, and to the underlying molecular mechanics force fields. The neglected contributions include the conformational entropy of the polypeptide chain, Another important factor are intramolecular hydrogen bonds, which are not explicitly included in modern force fields, but described as Coulomb interactions of atomic point charges. This is an approximation because hydrogen bonds have a partially quantum mechanical and chemical nature. Furthermore, electrostatic interactions are calculated using the dielectric constant of vacuum. Using the macroscopic dielectric constant at short distances is questionable. Finally, van der Waals interactions in MD are usually described by Lennard-Jones potentials based on the Fritz London theory that is applicable in vacuum
. PMID 27766843.
