1.
Biochemistry
–
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 kinetics
–
Enzyme kinetics is the study of the chemical reactions that are catalysed by enzymes. In enzyme kinetics, the rate is measured and the effects of varying the conditions of the reaction are investigated. Enzymes are usually protein molecules that manipulate other molecules — the enzymes substrates, kinetic studies on enzymes that only bind one substrate, such as triosephosphate isomerase, aim to measure the affinity with which the enzyme binds this substrate and the turnover rate. Some other examples of enzymes are phosphofructokinase and hexokinase, both of which are important for cellular respiration, when enzymes bind multiple substrates, such as dihydrofolate reductase, enzyme kinetics can also show the sequence in which these substrates bind and the sequence in which products are released. An example of enzymes that bind a single substrate and release multiple products are proteases, others join two substrates together, such as DNA polymerase linking a nucleotide to DNA. Although these mechanisms are often a series of steps, there is typically one rate-determining step that determines the overall kinetics. This rate-determining step may be a reaction or a conformational change of the enzyme or substrates. Knowledge of the structure is helpful in interpreting kinetic data. For example, the structure can suggest how substrates and products bind during catalysis, what changes occur during the reaction, not all biological catalysts are protein enzymes, RNA-based catalysts such as ribozymes and ribosomes are essential to many cellular functions, such as RNA splicing and translation. The main difference between ribozymes and enzymes is that RNA catalysts are composed of nucleotides, whereas enzymes are composed of amino acids, ribozymes also perform a more limited set of reactions, although their reaction mechanisms and kinetics can be analysed and classified by the same methods. The reaction catalysed by an enzyme uses exactly the same reactants, like other catalysts, enzymes do not alter the position of equilibrium between substrates and products. However, unlike uncatalysed chemical reactions, enzyme-catalysed reactions display saturation kinetics, the substrate concentration midway between these two limiting cases is denoted by KM. The two most important kinetic properties of an enzyme are how quickly the enzyme becomes saturated with a substrate. Knowing these properties suggests what an enzyme might do in the cell, Enzyme assays are laboratory procedures that measure the rate of enzyme reactions. Because enzymes are not consumed by the reactions they catalyse, enzyme assays usually follow changes in the concentration of substrates or products to measure the rate of reaction. There are many methods of measurement, spectrophotometric assays are most convenient since they allow the rate of the reaction to be measured continuously. Although radiometric assays require the removal and counting of samples they are extremely sensitive. An analogous approach is to use mass spectrometry to monitor the incorporation or release of stable isotopes as substrate is converted into product, the most sensitive enzyme assays use lasers focused through a microscope to observe changes in single enzyme molecules as they catalyse their reactions
3.
Dean Burk
–
Dean Burk was an American biochemist, a co-discoverer of biotin, medical researcher, and a cancer researcher at the Kaiser Wilhelm Institute and the National Cancer Institute. In 1934, he developed the Lineweaver–Burk plot together with Hans Lineweaver, Dean was the second of four sons born to Frederic Burk, the founder of the San Francisco Normal School, a preparatory school for teachers which eventually became San Francisco State University. He entered the University of California at Davis at the age of 15, a year later, he transferred to the University of California at Berkeley, where he received his B. S. in Entomology in 1923. Four years later he earned a Ph. D. in biochemistry, Burk joined the Department of Agriculture in 1929 working in the Fixed Nitrogen Research Laboratory. In 1939, he joined the Cancer Institute as a senior chemist and he was head of the cytochemistry laboratory when he retired in 1974. He also taught biochemistry at the Cornell University medical school from 1939 to 1941 and he was a research master at George Washington University. Burk was a friend and co-author with Otto Heinrich Warburg. He was a co-developer of the prototype of the Magnetic Resonance Scanner, Burk published more than 250 scientific articles in his lifetime. He later became head of the National Cancer Institutes Cytochemistry Sector in 1938, after retiring from the NCI in 1974, Dean Burk remained active. He devoted himself to his opposition to water fluoridation, according to Burk fluoridation is a form of public mass murder. Dean Burk argued on Dutch television against a water fluoridation proposal which was before the Dutch Parliament in the Netherlands and he also was an avid supporter of laetrile, a cancer treatment now regarded by the medical establishment as ineffective and potentially dangerous. For his work on photosynthesis, Dean Burk received the Hillebrand Prize in 1952, Dean Burk and Otto Heinrich Warburg discovered the photosynthesis I-quantum reaction that splits CO2 activated by respiration. For his techniques to distinguish between cells and those damaged by cancer, Dean Burk was awarded the Gerhard Domagk Prize in 1965
4.
Reaction rate
–
The reaction rate or speed of reaction for a reactant or product in a particular reaction is intuitively defined as how quickly or slowly a reaction takes place. Chemical kinetics is the part of chemistry that studies reaction rates. The concepts of chemical kinetics are applied in many disciplines, such as engineering, enzymology. Consider a typical reaction, a A + b B → p P + q Q The lowercase letters represent stoichiometric coefficients, while the capital letters represent the reactants. Reaction rate usually has the units of mol L−1 s−1, the rate of a reaction is always positive. A negative sign is present to indicate that the reactant concentration is decreasing. )The IUPAC recommends that the unit of time should always be the second. The rate of reaction differs from the rate of increase of concentration of a product P by a constant factor and for a reactant A by minus the reciprocal of the stoichiometric number. The stoichiometric numbers are included so that the rate is independent of which reactant or product species is chosen for measurement. For example, if a =1 and b =3 then B is consumed three times more rapidly than A, but v = -d/dt = -d/dt is uniquely defined. The above definition is valid for a single reaction, in a closed system of constant volume. If water is added to a pot containing salty water, the concentration of salt decreases, although there is no chemical reaction. When applied to the system at constant volume considered previously, this equation reduces to, r = d d t. Here N0 is the Avogadro constant, for a single reaction in a closed system of varying volume the so-called rate of conversion can be used, in order to avoid handling concentrations. It is defined as the derivative of the extent of reaction with respect to time, also V is the volume of reaction and Ci is the concentration of substance i. When side products or reaction intermediates are formed, the IUPAC recommends the use of the rate of appearance and rate of disappearance for products and reactants. Reaction rates may also be defined on a basis that is not the volume of the reactor, when a catalyst is used the reaction rate may be stated on a catalyst weight or surface area basis. If the basis is a specific catalyst site that may be counted by a specified method. The nature of the reaction, Some reactions are faster than others
5.
Concentration
–
In chemistry, concentration is the abundance of a constituent divided by the total volume of a mixture. Several types of mathematical description can be distinguished, mass concentration, molar concentration, number concentration, the term concentration can be applied to any kind of chemical mixture, but most frequently it refers to solutes and solvents in solutions. The molar concentration has variants such as concentration and osmotic concentration. To concentrate a solution, one must add more solute, or reduce the amount of solvent, by contrast, to dilute a solution, one must add more solvent, or reduce the amount of solute. Unless two substances are fully miscible there exists a concentration at which no further solute will dissolve in a solution, at this point, the solution is said to be saturated. If additional solute is added to a solution, it will not dissolve, except in certain circumstances. Instead, phase separation will occur, leading to coexisting phases, the point of saturation depends on many variables such as ambient temperature and the precise chemical nature of the solvent and solute. Concentrations are often called levels, reflecting the mental schema of levels on the axis of a graph. There are four quantities that describe concentration, The mass concentration ρ i is defined as the mass of a constituent m i divided by the volume of the mixture V, ρ i = m i V. The molar concentration c i is defined as the amount of a constituent n i divided by the volume of the mixture V, c i = n i V, however, more commonly the unit mol/L is used. The number concentration C i is defined as the number of entities of a constituent N i in a divided by the volume of the mixture V, C i = N i V. The volume concentration ϕ i is defined as the volume of a constituent V i divided by the volume of the mixture V, ϕ i = V i V. Being dimensionless, it is expressed as a number, e. g.0.18 or 18%, several other quantities can be used to describe the composition of a mixture. Note that these should not be called concentrations, normality is defined as the molar concentration c i divided by an equivalence factor f e q. Since the definition of the equivalence factor depends on context, IUPAC, the SI unit for molality is mol/kg. The mole fraction x i is defined as the amount of a constituent n i divided by the amount of all constituents in a mixture n t o t, x i = n i n t o t. However, the deprecated parts-per notation is used to describe small mole fractions. The mole ratio r i is defined as the amount of a constituent n i divided by the amount of all other constituents in a mixture
6.
Nonlinear regression
–
The data are fitted by a method of successive approximations. The data consist of independent variables, x, and their associated observed dependent variables. Each y is modeled as a variable with a mean given by a nonlinear function f. Systematic error may be present but its treatment is outside the scope of regression analysis, if the independent variables are not error-free, this is an errors-in-variables model, also outside this scope. This function is nonlinear because it cannot be expressed as a combination of the two β s. Other examples of nonlinear functions include exponential functions, logarithmic functions, trigonometric functions, power functions, Gaussian function, some functions, such as the exponential or logarithmic functions, can be transformed so that they are linear. When so transformed, standard linear regression can be performed but must be applied with caution, see Linearization, below, for more details. In general, there is no closed-form expression for the best-fitting parameters, usually numerical optimization algorithms are applied to determine the best-fitting parameters. Again in contrast to linear regression, there may be many local minima of the function to be optimized, in practice, estimated values of the parameters are used, in conjunction with the optimization algorithm, to attempt to find the global minimum of a sum of squares. For details concerning nonlinear data modeling see least squares and non-linear least squares, the assumption underlying this procedure is that the model can be approximated by a linear function. F ≈ f 0 + ∑ j J i j β j where J i j = ∂ f ∂ β j and it follows from this that the least squares estimators are given by β ^ ≈ −1 J T y. The nonlinear regression statistics are computed and used as in linear regression statistics, the linear approximation introduces bias into the statistics. Therefore more caution than usual is required in interpreting statistics derived from a nonlinear model, the best-fit curve is often assumed to be that which minimizes the sum of squared residuals. This is the least squares approach, however, in cases where the dependent variable does not have constant variance, a sum of weighted squared residuals may be minimized, see weighted least squares. Each weight should ideally be equal to the reciprocal of the variance of the observation, some nonlinear regression problems can be moved to a linear domain by a suitable transformation of the model formulation. For example, consider the nonlinear regression problem y = a e b x U with parameters a and b, however, use of a nonlinear transformation requires caution. The influences of the values will change, as will the error structure of the model. These may not be desired effects, for Michaelis–Menten kinetics, the linear Lineweaver–Burk plot 1 v =1 V max + K m V max of 1/v against 1/ has been much used
7.
Y-intercept
–
As such, these points satisfy x =0. If the curve in question is given as y = f, functions which are undefined at x =0 have no y-intercept. If the function is linear and is expressed in slope-intercept form as f = a + b x, some 2-dimensional mathematical relationships such as circles, ellipses, and hyperbolas can have more than one y-intercept. Because functions associate x values to no more than one y value as part of their definition, analogously, an x-intercept is a point where the graph of a function or relation intersects with the x-axis. As such, these points satisfy y=0, the zeros, or roots, of such a function or relation are the x-coordinates of these x-intercepts. Unlike y-intercepts, functions of the form y = f may contain multiple x-intercepts, the x-intercepts of functions, if any exist, are often more difficult to locate than the y-intercept, as finding the y intercept involves simply evaluating the function at x=0. The notion may be extended for 3-dimensional space and higher dimensions, as well as for other coordinate axes, for example, one may speak of the I-intercept of the current-voltage characteristic of, say, a diode
8.
Zero of a function
–
In other words, a zero of a function is an input value that produces an output of zero. A root of a polynomial is a zero of the polynomial function. If the function maps real numbers to real numbers, its zeroes are the x-coordinates of the points where its graph meets the x-axis, an alternative name for such a point in this context is an x-intercept. Every equation in the unknown x may be rewritten as f =0 by regrouping all terms in the left-hand side and it follows that the solutions of such an equation are exactly the zeros of the function f. Every real polynomial of odd degree has an odd number of roots, likewise. Consequently, real odd polynomials must have at least one real root, the fundamental theorem of algebra states that every polynomial of degree n has n complex roots, counted with their multiplicities. The non-real roots of polynomials with real coefficients come in conjugate pairs, vietas formulas relate the coefficients of a polynomial to sums and products of its roots. Computing roots of functions, for polynomial functions, frequently requires the use of specialised or approximation techniques. However, some functions, including all those of degree no greater than 4. In topology and other areas of mathematics, the set of a real-valued function f, X → R is the subset f −1 of X. Zero sets are important in many areas of mathematics. One area of importance is algebraic geometry, where the first definition of an algebraic variety is through zero-sets. For instance, for each set S of polynomials in k, one defines the zero-locus Z to be the set of points in An on which the functions in S simultaneously vanish, that is to say Z =. Then a subset V of An is called an algebraic set if V = Z for some S. These affine algebraic sets are the building blocks of algebraic geometry. Zero Pole Fundamental theorem of algebra Newtons method Sendovs conjecture Mardens theorem Vanish at infinity Zero crossing Weisstein, Eric W. Root
9.
Enzyme inhibitor
–
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
10.
Competitive inhibition
–
Competitive inhibition is a form of enzyme inhibition where binding of the inhibitor to the active site on the enzyme prevents binding of the substrate and vice versa. Most competitive inhibitors function by binding reversibly to the site of the enzyme. As a result, many sources state that this is the feature of competitive inhibitors. This, however, is a misleading oversimplification, as there are possible mechanisms by which an enzyme may bind either the inhibitor or the substrate. For example, allosteric inhibitors may display competitive, non-competitive, or uncompetitive inhibition, in competitive inhibition, at any given moment, the enzyme may be bound to the inhibitor, the substrate, or neither, but it cannot bind both at the same time. In virtually every case, competitive inhibitors bind in the binding site as the substrate. A competitive inhibitor could bind to a site of the free enzyme and prevent substrate binding. For example, strychnine acts as an inhibitor of the glycine receptor in the mammalian spinal cord. Glycine is a major post-synaptic inhibitory neurotransmitter with a receptor site. Strychnine binds to a site that reduces the affinity of the glycine receptor for glycine. In competitive inhibition, the velocity of the reaction is unchanged. The change in K m is parallel to the alteration in K d, any given competitive inhibitor concentration can be overcome by increasing the substrate concentration in which case the substrate will outcompete the inhibitor in binding to the enzyme. V max remains the same because the presence of the inhibitor can be overcome by higher substrate concentrations, K m app, the substrate concentration that is needed to reach V max /2, increases with the presence of a competitive inhibitor. This is because the concentration of substrate needed to reach V max with an inhibitor is greater than the concentration of substrate needed to reach V max without an inhibitor. It is generally assumed that this behavior is indicative of both compounds binding at the site, but that is not strictly necessary. As with the derivation of the Michaelis-Menten equation, assume that the system is at steady-state, D d t = d d t = d d t =0. We can therefore set up a system of equations, where, the initial velocity is defined as V0 = d / d t = k 2, so we need to define the unknown in terms of the knowns, and 0
11.
Non-competitive inhibition
–
Non-competitive inhibition is a type of enzyme inhibition where the inhibitor reduces the activity of the enzyme and binds equally well to the enzyme whether or not it has already bound the substrate. It is important to note that while all non-competitive inhibitors bind the enzyme at allosteric sites —not all inhibitors that bind at allosteric sites are non-competitive inhibitors, in fact, allosteric inhibitors may act as competitive, non-competitive, or uncompetitive inhibitors. Many sources continue to conflate these two terms, or state the definition of allosteric inhibition as the definition for non-competitive inhibition, non-competitive inhibition models a system where the inhibitor and the substrate may both be bound to the enzyme at any given time. Non-competitive inhibition is distinguished from general mixed inhibition in that the inhibitor has an affinity for the enzyme. It differs from competitive inhibition in that the binding of the inhibitor does not prevent binding of substrate and this type of inhibition reduces the maximum rate of a chemical reaction without changing the apparent binding affinity of the catalyst for the substrate. In the presence of an inhibitor, the apparent enzyme affinity is equivalent to the actual affinity. In terms of Michaelis-Menten kinetics, Kmapp = Km and this can be seen as a consequence of Le Chateliers principle because the inhibitor binds to both the enzyme and the enzyme-substrate complex equally so that the equilibrium is maintained. However, since some enzyme is inhibited from converting the substrate to product. Computer docking simulation and constructed mutants substituted indicate that the binding site of 6-hydroxyflavone is the reported allosteric binding site of CYP2C9 enzyme. Berg, Jeremy M. Tymoczko, John L. Stryer, Lubert, Biochemistry, New York City, WH Freeman & Co
12.
Journal of the American Chemical Society
–
The Journal of the American Chemical Society is a weekly peer-reviewed scientific journal that was established in 1879 by the American Chemical Society. The journal has absorbed two other publications in its history, the Journal of Analytical and Applied Chemistry and the American Chemical Journal and it publishes original research papers in all fields of chemistry. Since 2002, the journal is edited by Peter J. Stang, in 2014, the journal moved to a hybrid open access publishing model. The Journal of the American Chemical Society is abstracted and indexed in Chemical Abstracts Service, Scopus, EBSCOhost, Thomson-Gale, ProQuest, PubMed, Web of Science, and SwetsWise. According to the Journal Citation Reports, it had a factor of 12.113 for 2014
13.
PubMed Identifier
–
PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine at the National Institutes of Health maintains the database as part of the Entrez system of information retrieval, from 1971 to 1997, MEDLINE online access to the MEDLARS Online computerized database primarily had been through institutional facilities, such as university libraries. PubMed, first released in January 1996, ushered in the era of private, free, home-, the PubMed system was offered free to the public in June 1997, when MEDLINE searches via the Web were demonstrated, in a ceremony, by Vice President Al Gore. Information about the journals indexed in MEDLINE, and available through PubMed, is found in the NLM Catalog. As of 5 January 2017, PubMed has more than 26.8 million records going back to 1966, selectively to the year 1865, and very selectively to 1809, about 500,000 new records are added each year. As of the date,13.1 million of PubMeds records are listed with their abstracts. In 2016, NLM changed the system so that publishers will be able to directly correct typos. Simple searches on PubMed can be carried out by entering key aspects of a subject into PubMeds search window, when a journal article is indexed, numerous article parameters are extracted and stored as structured information. Such parameters are, Article Type, Secondary identifiers, Language, publication type parameter enables many special features. As these clinical girish can generate small sets of robust studies with considerable precision, since July 2005, the MEDLINE article indexing process extracts important identifiers from the article abstract and puts those in a field called Secondary Identifier. The secondary identifier field is to store numbers to various databases of molecular sequence data, gene expression or chemical compounds. For clinical trials, PubMed extracts trial IDs for the two largest trial registries, ClinicalTrials. gov and the International Standard Randomized Controlled Trial Number Register, a reference which is judged particularly relevant can be marked and related articles can be identified. If relevant, several studies can be selected and related articles to all of them can be generated using the Find related data option, the related articles are then listed in order of relatedness. To create these lists of related articles, PubMed compares words from the title and abstract of each citation, as well as the MeSH headings assigned, using a powerful word-weighted algorithm. The related articles function has been judged to be so precise that some researchers suggest it can be used instead of a full search, a strong feature of PubMed is its ability to automatically link to MeSH terms and subheadings. Examples would be, bad breath links to halitosis, heart attack to myocardial infarction, where appropriate, these MeSH terms are automatically expanded, that is, include more specific terms. Terms like nursing are automatically linked to Nursing or Nursing and this important feature makes PubMed searches automatically more sensitive and avoids false-negative hits by compensating for the diversity of medical terminology. The My NCBI area can be accessed from any computer with web-access, an earlier version of My NCBI was called PubMed Cubby
14.
Enzyme
–
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
15.
Active site
–
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
16.
Catalytic triad
–
A catalytic triad refers to the three amino acid residues that function together at the centre of the active site of some hydrolase and transferase enzymes. An Acid-Base-Nucleophile triad is a motif for generating a nucleophilic residue for covalent catalysis. The nucleophile is most commonly a serine or cysteine amino acid, as well as divergent evolution of function, catalytic triads show some of the best examples of convergent evolution. Chemical constraints on catalysis have led to the same solution independently evolving in at least 23 separate superfamilies. Their mechanism of action is one of the best studied in biochemistry. The enzymes trypsin and chymotrypsin were first purified in the 1930s, a serine in each of trypsin and chymotrypsin was identified as the catalytic nucleophile in the 1950s. The structure of chymotrypsin was solved by X-ray crystallography in the 1960s, other proteases were sequenced and aligned to reveal a family of related proteases, now called the S1 family. Simultaneously, the structures of the evolutionarily unrelated papain and subtilisin proteases were found to contain analogous triads, the charge-relay mechanism for the activation of the nucleophile by the other triad members was proposed in the late 1960s. As more protease structures were solved by X-ray crystallography in the 1970s and 80s, understanding how chemical constraints on evolution led to the convergence of so many enzyme families on the same triad geometries has developed in the 2010s. The massive body of work on the charge-relay, covalent catalysis used by catalytic triads has led to the mechanism being the best characterised in all of biochemistry. Enzymes that contain an catalytic triad use it for one of two types, either to split a substrate or to transfer one portion of a substrate over to a second substrate. Triads are an inter-dependent set of residues in the site of an enzyme. These triad residues act together to make the nucleophile member highly reactive, catalytic triads perform covalent catalysis using a residue as a nucleophile. The reactivity of the residue is increased by the functional groups of the other triad members. The nucleophile is polarised and oriented by the base, which is itself bound, catalysis is performed in two stages. First, the nucleophile attacks the carbonyl carbon and forces the carbonyl oxygen to accept an electron. The build-up of negative charge on this intermediate is stabilized by an oxanion hole within the active site. The intermediate then collapses back to a carbonyl, ejecting the first half of the substrate, the ejection of this first leaving group is often aided by donation of a proton by the base
17.
Oxyanion hole
–
An oxyanion hole is a pocket in the active site of an enzyme that stabilizes transition state negative charge on a deprotonated oxygen or alkoxide. The pocket typically consists of backbone amides or positively charged residues, stabilising the transition state lowers the activation energy necessary for the reaction, and so promotes catalysis. Additionally, it may allow for insertion or positioning of a substrate, enzymes that catalyse multi-step reactions can have multiple oxyanion holes that stabilise different transition states in the reaction. Enzyme catalysis Active site Transition state Serine proteases#Catalytic mechanism Albert Lehninger, et al
18.
Enzyme promiscuity
–
Enzyme promiscuity is the ability of an enzyme to catalyse a fortuitous side reaction in addition to its main reaction. Although enzymes are remarkably specific catalysts, they can often perform side reactions in addition to their main and these promiscuous activities are usually slow relative to the main activity and are under neutral selection. An example of this is the atrazine chlorohydrolase from Pseudomonas sp, ADP which evolved from melamine deaminase, which has very small promiscuous activity towards atrazine, a man-made chemical. Enzymes are evolved to catalyse a reaction on a particular substrate with a high catalytic efficiency. Several theoretical models exist to predict the order of duplication and specialisation events, on the other, enzymes may evolve an increased secondary activity with little loss to the primary activity with little adaptive conflict. A study of three distinct hydrolases has shown the main activity is robust towards change, whereas the activities are more plastic. Specifically, selecting for an activity that is not the activity, does not initially diminish the main activity. The most recent and most clear cut example of evolution is the rise of bioremediating enzymes in the past 60 years. Due to the low number of amino acid changes, these provide an excellent model to investigate enzyme evolution in nature. This issue can be resolved thanks to ancestral reconstruction and this variability in ancestral specificity has not only been observed between different genes, but also within the same gene family. Antithetically, the ancestor before the split had a more pronounced isomaltose-like glucosidase activity. Roy Jensen in 1976 theorised that primordial enzymes had to be highly promiscuous in order for networks to assemble in a patchwork fashion. This primordial catalytic versatility was later lost in favour of highly catalytic specialised orthologous enzymes, as a consequence, many central-metabolic enzymes have structural homologues that diverged before the last universal common ancestor. Promiscuity is however not only a primordial trait, in fact it is very widespread property in modern genomes, a series of experiments have been conducted to assess the distribution of promiscuous enzyme activities in E. coli. In E. coli 21 out of 104 single-gene knockouts tested could be rescued by overexpressing a noncognate E. coli protein, similarly, overexpressing the ORF collection allowed E. coli to gain over an order of magnitude in resistance in 86 out 237 toxic environment. Homologues are sometimes known to display promiscuity towards each others main reactions, despite the divergence the homologues have a varying degree of reciprocal promiscuity, the differences in promiscuity are due to mechanisms involved, particularly the intermediate required. Examples of these are enzymes for primary and secondary metabolism in plants, a promiscuous activity is a non-native activity the enzyme did not evolve to do, but arises due to an accommodating conformation of the active site. When the specificity of enzyme was probed, it was found that it was selective against natural amino acids that were not phenylalanine
19.
Diffusion limited enzyme
–
A Diffusion limited enzyme is an enzyme which catalyses a reaction so efficiently that the rate limiting step is that of substrate diffusion into the active site, or product diffusion out. This is also known as kinetic perfection or catalytic perfection, since the rate of catalysis of such enzymes is set by the diffusion-controlled reaction, it therefore represents an intrinsic, physical constraint on evolution. Diffusion limited perfect enzymes are very rare, most enzymes catalyse their reactions to a rate that is 1, 000-10,000 times slower than this limit. This is due to both the limitations of difficult reactions, and the evolutionary limitations that such high reaction rates do not confer any extra fitness. The theory of diffusion-controlled reaction was utilized by R. A. Alberty, Gordon Hammes, and Manfred Eigen to estimate the upper limit of enzyme-substrate reaction, according to their estimation, the upper limit of enzyme-substrate reaction was 109 M−1 s−1. To address such a paradox, Prof, the new upper limit found by Chou et al. for enzyme-substrate reaction was further discussed and analyzed by a series of follow-up studies. Kinetically perfect enzymes have a specificity constant, kcat/Km, on the order of 108 to 109 M−1 s−1, the rate of the enzyme-catalysed reaction is limited by diffusion and so the enzyme processes the substrate well before it encounters another molecule. Some enzymes operate with kinetics which are faster than diffusion rates, several mechanisms have been invoked to explain this phenomenon. Some proteins are believed to accelerate catalysis by drawing their substrate in, some invoke a quantum-mechanical tunneling explanation whereby a proton or an electron can tunnel through activation barriers, although proton tunneling remains a somewhat controversial idea. It is worth noting that there are not many kinetically perfect enzymes and this can be explained in terms of natural selection. An increase in speed may be favoured as it could confer some advantage to the organism. However, when the catalytic speed outstrips diffusion speed there is no advantage to increase the speed even further. The diffusion limit represents a physical constraint on evolution. Increasing the catalytic speed past the speed will not aid the organism in any way
20.
Cofactor (biochemistry)
–
A cofactor is a non-protein chemical compound or metallic ion that is required for a proteins biological activity to happen. These proteins are enzymes, and cofactors can be considered helper molecules that assist in biochemical transformations. A coenzyme that is tightly or even covalently bound is termed a prosthetic group, the two subcategories under coenzyme are cosubstrates and prosthetic groups. Cosubstrates are transiently bound to the protein and will be released at some point, the prosthetic groups, on the other hand, are bound permanently to the protein. Both of them have the function, which is to facilitate the reaction of enzymes. Additionally, some sources also limit the use of the cofactor to inorganic substances. An inactive enzyme without the cofactor is called an apoenzyme, while the enzyme with cofactor is called a holoenzyme. Some enzymes or enzyme complexes require several cofactors, organic cofactors are often vitamins or made from vitamins. Many contain the nucleotide adenosine monophosphate as part of their structures, such as ATP, coenzyme A, FAD and this common structure may reflect a common evolutionary origin as part of ribozymes in an ancient RNA world. It has been suggested that the AMP part of the molecule can be considered to be a kind of handle by which the enzyme can grasp the coenzyme to switch it between different catalytic centers. Cofactors can be divided into two groups, organic cofactors, such as flavin or heme, and inorganic cofactors, such as the metal ions Mg2+, Cu+, Mn2+. Organic cofactors are sometimes divided into coenzymes and prosthetic groups. The term coenzyme refers specifically to enzymes and, as such, on the other hand, prosthetic group emphasizes the nature of the binding of a cofactor to a protein and, thus, refers to a structural property. Different sources give different definitions of coenzymes, cofactors. It should be noted that terms are often used loosely. However, the author could not arrive at a single all-encompassing definition of a coenzyme, the study of these cofactors falls under the area of bioinorganic chemistry. In nutrition, the list of essential trace elements reflects their role as cofactors, in humans this list commonly includes iron, magnesium, manganese, cobalt, copper, zinc, and molybdenum. Although chromium deficiency causes impaired glucose tolerance, no human enzyme that uses this metal as a cofactor has been identified, iodine is also an essential trace element, but this element is used as part of the structure of thyroid hormones rather than as an enzyme cofactor
21.
Enzyme catalysis
–
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
22.
Allosteric regulation
–
In biochemistry, allosteric regulation is the regulation of an enzyme by binding an effector molecule at a site other than the enzymes active site. The site to which the effector binds is termed the allosteric site, Allosteric sites allow effectors to bind to the protein, often resulting in a conformational change involving protein dynamics. Effectors that enhance the activity are referred to as allosteric activators. Allosteric regulations are an example of control loops, such as feedback from downstream products or feedforward from upstream substrates. Long-range allostery is especially important in cell signaling, Allosteric regulation is also particularly important in the cells ability to adjust enzyme activity. The term allostery comes from the Greek allos, other, and stereos and this is in reference to the fact that the regulatory site of an allosteric protein is physically distinct from its active site. Most allosteric effects can be explained by the concerted MWC model put forth by Monod, Wyman, and Changeux, or by the model described by Koshland, Nemethy. Both postulate that enzyme subunits exist in one of two conformations, tensed or relaxed, and that relaxed subunits bind substrate more readily than those in the tense state, the two models differ most in their assumptions about subunit interaction and the preexistence of both states. Thus, all subunits must exist in the same conformation, the model further holds that, in the absence of any ligand, the equilibrium favors one of the conformational states, T or R. The equilibrium can be shifted to the R or T state through the binding of one ligand to a site that is different from the active site. The sequential model of allosteric regulation holds that subunits are not connected in such a way that a change in one induces a similar change in the others. Thus, all enzyme subunits do not necessitate the same conformation, moreover, the sequential model dictates that molecules of a substrate bind via an induced fit protocol. In general, when a subunit randomly collides with a molecule of substrate, while such an induced fit converts a subunit from the tensed state to relaxed state, it does not propagate the conformational change to adjacent subunits. Instead, substrate-binding at one subunit only slightly alters the structure of other subunits so that their sites are more receptive to substrate. A morpheein is a structure that can exist as an ensemble of physiologically significant. Transitions between alternate morpheein assemblies involve oligomer dissociation, conformational change in the state, and reassembly to a different oligomer. The required oligomer disassembly step differentiates the morpheein model for allosteric regulation from the classic MWC, porphobilinogen synthase is the prototype morpheein. Ensemble models like the Ensemble Allosteric Model and Allosteric Ising Model assume that each domain of the system can adopt two states similar to the MWC model, molecular dynamics simulations can be used to estimate a systemss statistical ensemble so that it can be analyzed with the allostery landscape model
23.
Cooperativity
–
This is referred to as cooperative binding. We also see cooperativity in large chain molecules made of identical subunits. This is referred to as subunit cooperativity, when a substrate binds to one enzymatic subunit, the rest of the subunits are stimulated and become active. Ligands can either have positive cooperativity, negative cooperativity, or non-cooperativity, an example of positive cooperativity is the binding of oxygen to hemoglobin. One oxygen molecule can bind to the iron of a heme molecule in each of the four chains of a hemoglobin molecule. The oxygen affinity of 3-oxy-hemoglobin is ~300 times greater than that of deoxy-hemoglobin and this behavior leads the affinity curve of hemoglobin to be sigmoidal, rather than hyperbolic as with the monomeric myoglobin. By the same process, the ability for hemoglobin to lose oxygen increases as fewer oxygen molecules are bound, an example of this occurring is the relationship between glyceraldehyde-3-phosphate and the enzyme glyceraldehyde-3-phosphate dehydrogenase. Homotropic cooperativity refers to the fact that the causing the cooperativity is the one that will be affected by it. Heterotropic cooperativity is where a third party substance causes the change in affinity, for example, unwinding of DNA involves cooperativity, Portions of DNA must unwind in order for DNA to carry out replication, transcription and recombination. The cooperative unit size is the number of adjacent bases that tend to unwind as a unit due to the effects of positive cooperativity. This phenomenon applies to other types of molecules as well, such as the folding and unfolding of proteins. Subunit cooperativity is measured on the relative scale known as Hills Constant, a simple and widely used model for molecular interactions is the Hill Equation. This provides a way to quantify cooperative binding by describing the fraction of saturated ligand binding sites as a function of the ligand concentration, in all of the above types of cooperativity, entropy plays a role. For example, in the case of oxygen binding to hemoglobin and this represents a state of higher entropy compared to a fourth oxygen having one available binding site. Thus, in transition from the unbound to the bound state, the first oxygen must overcome a larger entropy change than the last oxygen in order to bind to the hemoglobin
24.
Protein superfamily
–
A protein superfamily is the largest grouping of proteins for which common ancestry can be inferred. Usually this common ancestry is inferred from structural alignment and mechanistic similarity, sequence homology can then be deduced even if not apparent. Superfamilies typically contain several protein families which show sequence similarity within each family, the term protein clan is commonly used for protease superfamilies based on the MEROPS protease classification system. Superfamilies of proteins are identified using a number of methods, closely related members can be identified by different methods to those needed to group the most evolutionarily divergent members. Historically, the similarity of different amino acid sequences has been the most common method of inferring homology, amino acid sequence is typically more conserved than DNA sequence, so is a more sensitive detection method. Since some of the amino acids have similar properties, conservative mutations that interchange them are often neutral to function, the most conserved sequence regions of a protein often correspond to functionally important regions like catalytic sites and binding sites, since these regions are less tolerant to sequence changes. Using sequence similarity to infer homology has several limitations, there is no minimum level of sequence similarity guaranteed to produce identical structures. Over long periods of evolution, related proteins may show no sequence similarity to one another. Sequences with many insertions and deletions can also sometimes be difficult to align, in the PA clan of proteases, for example, not a single residue is conserved through the superfamily, not even those in the catalytic triad. Conversely, the families that make up a superfamily are defined on the basis of their sequence alignment. Nevertheless, sequence similarity is the most commonly used form of evidence to infer relatedness, in the absence of structural information, sequence similarity constrains the limits of which proteins can be assigned to a superfamily. Structure is much more conserved than sequence, such that proteins with highly similar structures can have entirely different sequences. Over very long timescales, very few residues show detectable amino acid sequence conservation, however secondary structural elements. Conformational changes of the structure may also be conserved, as is seen in the serpin superfamily. Consequently, protein structure can be used to detect homology between proteins even when no evidence of relatedness remains in their sequences. Structural alignment programs, such as DALI, use the 3D structure of a protein of interest to find proteins with similar folds, however, on rare occasions, related proteins may evolve to be structurally dissimilar and relatedness can only be inferred by other methods. The catalytic mechanism of enzymes within a superfamily is typically conserved, catalytic residues also tend to occur in the same order in the protein sequence. However, mechanism alone is not sufficient to infer relatedness, since some catalytic mechanisms have been convergently evolved multiple times independently, protein superfamilies represent the current limits of our ability to identify common ancestry
25.
Protein family
–
A protein family is a group of evolutionarily-related proteins. In many cases a protein family has a gene family. The term protein family should not be confused with family as it is used in taxonomy, proteins in a family descend from a common ancestor and typically have similar three-dimensional structures, functions, and significant sequence similarity. The most important of these is sequence similarity since it is the strictest indicator of homology, there is a fairly well developed framework for evaluating the significance of similarity between a group of sequences using sequence alignment methods. Families are sometimes grouped together into larger clades called superfamilies based on structural and mechanistic similarity, currently, over 60,000 protein families have been defined, although ambiguity in the definition of protein family leads different researchers to wildly varying numbers. Other terms such as class, group, clan and sub-family have been coined over the years. A common usage is that superfamilies contain families which contain sub-families, hence a superfamily, such as the PA clan of proteases, has far lower sequence conservation than one of the families it contains, the C04 family. It is unlikely that an exact definition will be agreed and to it is up to the reader to discern exactly how these terms are being used in a particular context, since that time, it was found that many proteins comprise multiple independent structural and functional units or domains. Due to evolutionary shuffling, different domains in a protein have evolved independently and this has led, in recent years, to a focus on families of protein domains. A number of resources are devoted to identifying and cataloging such domains. Regions of each protein have differing functional constraints, for example, the active site of an enzyme requires certain amino acid residues to be precisely oriented in three dimensions. On the other hand, a protein–protein binding interface may consist of a surface with constraints on the hydrophobicity or polarity of the amino acid residues. These blocks are most commonly referred to as motifs, although other terms are used. Again, a number of online resources are devoted to identifying and cataloging protein motifs. According to current consensus, protein families arise in two ways, firstly, the separation of a parent species into two genetically isolated descendent species allows a gene/protein to independently accumulate variations in these two lineages. This results in a family of proteins, usually with conserved sequence motifs. Secondly, a gene duplication may create a copy of a gene. Because the original gene is able to perform its function
26.
Transferase
–
A transferase is any one of a class of enzymes that enact the transfer of specific functional groups from one molecule to another. They are involved in hundreds of different biochemical pathways throughout biology, transferases are involved in myriad reactions in the cell. Transferases are also utilized during translation, in this case, an amino acid chain is the functional group transferred by a peptidyl transferase. Group would be the group transferred as a result of transferase activity. The donor is often a coenzyme, some of the most important discoveries relating to transferases occurred as early as the 1930s. Earliest discoveries of transferase activity occurred in other classifications of enzymes, including Beta-galactosidase, protease, prior to the realization that individual enzymes were capable of such a task, it was believed that two or more enzymes enacted functional group transfers. This observance was later verified by the discovery of its reaction mechanism by Braunstein and their analysis showed that this reversible reaction could be applied to other tissues. This assertion was validated by Rudolf Schoenheimers work with radioisotopes as tracers in 1937 and this in turn would pave the way for the possibility that similar transfers were a primary means of producing most amino acids via amino transfer. Another such example of early research and later reclassification involved the discovery of uridyl transferase. In 1953, the enzyme UDP-glucose pyrophosphorylase was shown to be a transferase, when it was found that it could reversibly produce UTP and G1P from UDP-glucose, another example of historical significance relating to transferase is the discovery of the mechanism of catecholamine breakdown by catechol-O-methyltransferase. This discovery was a part of the reason for Julius Axelrod’s 1970 Nobel Prize in Physiology or Medicine. Classification of transferases continues to this day, with new ones being discovered frequently, an example of this is Pipe, a sulfotransferase involved in the dorsal-ventral patterning of Drosophilia. Initially, the mechanism of Pipe was unknown, due to a lack of information on its substrate. Research into Pipes catalytic activity eliminated the likelihood of it being a heparan sulfate glycosaminoglycan, further research has shown that Pipe targets the ovarian structures for sulfation. Pipe is currently classified as a Drosophilia heparan sulfate 2-O-sulfotransferase, systematic names of transferases are constructed in the form of donor, acceptor grouptransferase. For example, a DNA methyltransferase is a transferase that catalyzes the transfer of a group to a DNA acceptor. In practice, many molecules are not referred to using this terminology due to more prevalent common names, in the EC system of classification, the accepted name for RNA Polymerase is DNA-directed RNA polymerase. Described primarily based on the type of biochemical group transferred, transferases can be divided into ten categories and these categories comprise over 450 different unique enzymes
27.
Isomerase
–
Isomerases are a general class of enzymes which convert a molecule from one isomer to another. Isomerases can either facilitate intramolecular rearrangements in which bonds are broken, the general form of such a reaction is as follows, A–B → B–A There is only one substrate yielding one product. This product has the molecular formula as the substrate but differs in bond connectivity or spatial arrangements. Isomerases catalyze reactions across many biological processes, such as in glycolysis, Isomerases catalyze changes within one molecule. They convert one isomer to another, meaning that the end product has the molecular formula. Isomers themselves exist in many varieties but can generally be classified as structural isomers or stereoisomers, structural isomers have a different ordering of bonds and/or different bond connectivity from one another, as in the case of hexane and its four other isomeric forms. Stereoisomers have the same ordering of bonds and the same connectivity. For example, 2-butene exists in two forms, cis-2-butene and trans-2-butene. The sub-categories of isomerases containing racemases, epimerases and cis-trans isomers are examples of enzymes catalyzing the interconversion of stereoisomers, intramolecular lyases, oxidoreductases and transferases catalyze the interconversion of structural isomers. The prevalence of each isomer in nature depends in part on the isomerization energy, isomers close in energy can interconvert easily and are often seen in comparable proportions. Isomerases can increase the rate by lowering the isomerization energy. Calculating isomerase kinetics from experimental data can be more difficult than for other enzymes because the use of product inhibition experiments is impractical, There are also practical difficulties in determining the rate-determining step at high concentrations in a single isomerization. Instead, tracer perturbation can overcome these technical difficulties if there are two forms of the unbound enzyme and this technique uses isotope exchange to measure indirectly the interconversion of the free enzyme between its two forms. The radiolabeled substrate and product diffuse in a time-dependent manner, when the system reaches equilibrium the addition of unlabeled substrate perturbs or unbalances it. As equilibrium is established again, the substrate and product are tracked to determine energetic information. This technique was adopted to study the profile of proline racemase. Generally, the names of isomerases are formed as substrate isomerase, enzyme-catalyzed reactions each have a uniquely assigned classification number. Isomerase-catalyzed reactions have their own EC category, EC5, Isomerases are further classified into six subclasses, This category includes and epimerases)
![V={\frac {V_{{\max }}[S]}{K_{m}+[S]}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/8fa5b35e10661c7592ae5bc59429f1033a4acbf8)
![{1 \over V}={{K_{m}+[S]} \over V_{{\max }}[S]}={K_{m} \over V_{\max }}{1 \over [S]}+{1 \over V_{\max }}](https://wikimedia.org/api/rest_v1/media/math/render/svg/262e1440a8ad30a692b153178eabbf6e7f45d48f)
