From owner-btk-mca@hgmp.mrc.ac.uk Thu May 11 10:51:42 2000 Return-Path: Received: by mercury.hgmp.mrc.ac.uk (Postfix, from userid 110) id 3282417AAB; Thu, 11 May 2000 10:51:41 +0100 (BST) Received: from niobium.hgmp.mrc.ac.uk (niobium [193.62.192.41]) by hgmp.mrc.ac.uk (8.9.3/8.9.3) with ESMTP id JAA06393 for ; Thu, 11 May 2000 09:24:52 +0100 (BST) Received: (from news@localhost) by niobium.hgmp.mrc.ac.uk (8.9.3+Sun/8.8.8) id JAA04149 for btk-mca-list@hgmp.mrc.ac.uk; Thu, 11 May 2000 09:24:50 +0100 (BST) X-Authentication-Warning: niobium.hgmp.mrc.ac.uk: news set sender to using -f From: "Herbert M Sauro" X-Newsgroups: bionet.metabolic-reg Subject: New Metabolic-Reg FAQ Date: Thu, 11 May 2000 09:23:30 +0100 Message-ID: <958033423.26934.0.nnrp-02.c2de3927@news.demon.co.uk> X-NNTP-Posting-Host: fssc.demon.co.uk:194.222.57.39 X-Trace: news.demon.co.uk 958033423 nnrp-02:26934 NO-IDENT fssc.demon.co.uk:194.222.57.39 X-Complaints-To: abuse@demon.net X-Priority: 3 X-MSMail-Priority: Normal X-Newsreader: Microsoft Outlook Express 5.00.2314.1300 X-MimeOLE: Produced By Microsoft MimeOLE V5.00.2314.1300 Lines: 1131 To: btk-mca@hgmp.mrc.ac.uk Sender: owner-btk-mca@hgmp.mrc.ac.uk Precedence: bulk NOTE --------------------- It appears that this FAQ may not have been delivered to metabolic-reg last month so it is being resent in the hope that it will appear this time! --------------------- Here is the release of a new FAQ for the Metabolic-Reg group. Hopefully it will expand in future editions, contributions and comments will be very welcome. Omissions, reports of errors, bad formatting etc. to be sent to the maintainer. FAQ maintainer: Herbert Sauro HSauro@fssc.demon.co.uk ---------------------------------------------------------------------------- ----------------------------------------- [1] About bionet.metabolic-reg FAQ ------------------------------------------------------------------------ This is an updated ASCII version of a html FAQ originally posted by Athel Cornish-Bowden on his web site (and still available at http://ir2lcb.cnrs-mrs.fr/~athel/mcafaq.htm). Many thanks to Athel for allowing us to use his FAQ as the basis for the bionet-metabolic-reg newsgroup FAQ. Readers will discover that this FAQ is currently biased towards questions about metabolic control analysis (MCA) and computational aspect of metabolic systems. However contributions relating to specific regulatory behaviour of metabolic systems is are also very welcome including of course interesting FAQs relating to experimental work. Contributions are welcome !! This FAQ is maintained by Herbert Sauro . The foundation for the FAQ was provided by Athel Cornish-Bowden's Web-site FAQ. Copyright (c) 1998-2000 Herbert Sauro and Athel Cornish-Bowden. This FAQ may be posted to any USENET newsgroup, on-line service, or BBS as long as it is posted in its entirety and includes this copyright statement. This FAQ may not be distributed for financial gain. This FAQ may not be included in commercial collections or compilations without express permission from the author. ************************** [1.1] What's New? April 2000 This text version is new and has numerous new additions and ammendments to the original Web FAQ. ------------------------------------------------------------------------ [1] About Bionet.Metabolic-Reg FAQ [1.1] What's New? [2] Basic Theory of MCA [2.1] So what's the big deal? [2.2] What is Metabolic Control Analysis? [2.3] How is metabolic control analysis related to sensitivity analysis? [2.4] What is a sensitivity? [2.5] What is a control strength? [2.6] What are the main questions that metabolic control analysis sets out to answer? [3] Other approaches [4] Fundamental Concepts of MCA [4.1] What is an elasticity? [4.2] What is an elasticity coefficient? [4.3] What is a control coefficient? [4.4] What is a response coefficient? [4.5] What are local and system properties? [4.6] What are the theorems of Metabolic Control Analysis? [4.7] What are the summation relationships? [4.8] What is the connectivity relationship? [4.9] Why "elasticity" (rather than, say, "order of reaction")? [4.10] How is metabolic control analysis related to classical ideas of metabolic regulation? [4.11] The Two Fundamental Equations of Metabolic Control Analysis [4.12] Why does metabolic control analysis appear to ignore enzyme mechanisms? [4.13] What is the partitioned response relationship? [5] Specific Metabolic Concepts [5.1] How does feedback inhibition affect the distribution of flux control in a pathway? [5.2] How can yields of metabolic processes be improved for biotechnological purposes? [5.2] Why isn't Phosphofructokinase rate-limiting? [5.3] Supply and Demand Theory of Metabolic Systems [5.4] TurboCharging [5.5] How does channelling affect the summation relationships? [5.6] What is a controllability coefficient? [5.7] Is it true that metabolic control analysis assumes that enzymes are regulated solely by changing their concentrations (or V values)? [5.8] How does metabolic control analysis explain the fact that most mutations in diploid organisms are recessive? [5.9] How does metabolic control analysis aid in understanding mitochondrial myopathies and other metabolic diseases? [5.10] Competitive and UnCompetitive inhibition [6] Real-World Metabolic Models [7] Computational Resources [7.1] What programs are available for metabolic modelling? [7.2] Where can I find information on algorithms for metabolic analysis? [7.3] What advantages does modelling have over algebraic analysis? [8] People and References [8.1] Where can I find more detailed information in the printed literature? [8.2] How do I contact people working on metabolic control analysis? [8.3] Where can I find information about meetings related to metabolic control analysis? [8.4] References [8.5] Are there any books devoted to metabolic control analysis? [8.6] Why is the question that interests me not listed? [8.7] Where can I find more detailed information on the web? [9] Acknowledgments [2] Basic Theory ------------------------------------------------------------------------ [2.1] So what's the big deal? Cellular systems such as gene networks, signal transduction schemes and the traditional metabolic pathways are some of the main elements that constitute the insides of cells; they make cells complicated and difficult to understand. The standard biochemistry and molecular biology text books abound with colourful diagrams of how the things we find in cells are connected to another, how one reaction step follows another or how signals are transmitted along cascades of proteins. Whereas physics and chemistry and in fact all the other related sciences rely heavily on quantitative methods and strict mathematical theory, biochemistry and particularly molecular biology stand-out as some of the few sciences that have either rejected the quantitative approach or have yet to embrace it. This newsgroup and by implication this FAQ attempts to answer questions concerning quantitative approaches to describing cellular systems. This is an important new field; if we are ever to find truly rational ways at finding new drug targets or improving commercially important products of living systems then our current obsessive fixation on genes and gene sequences rather that what actually goes on downstream of gene expression will have to change. I mean, I don't think it requires a rocket scientist to realise where most therapeutic drug act and if you want to improve ethanol production in yeast where should one look, in the nucleus or the cytoplasm? No prizes for the correct answer. [2.2] What is metabolic control analysis? Metabolic control analysis is a method for analysing how the control of fluxes and intermediate concentrations in a metabolic pathway is distributed among the different enzymes that constitute the pathway. Instead of assuming the existence of a unique rate-limiting step, it assumes that there is a definite amount of flux control and that this is spread quantitatively among the component enzymes. Metabolic control analysis was formerly (and is sometimes still) known as metabolic control theory, and is closely related to the engineering discipline known as sensitivity analysis. Alternative approaches to studying the kinetic behaviour of multi-enzyme systems are flux-oriented theory and biochemical systems theory. Metabolic Control Analysis can be divided into a number of related areas: a) Structural Analysis b) Perturbation Analysis c) Response Analysis d) Regulation Analysis e) Heuristic Theorem Analysis These areas of study will be expanded in future FAQ releases. ************************** [2.3] What is metabolic control theory (and is it different from metabolic control analysis)? Metabolic control theory is an older term for metabolic control analysis. It is still used by some authors, but started to fall into disuse at the end of the 1980s when some authors began to emphasize that metabolic control analysis is more a method for analysing how control is distributed than a body of theory as such. ************************** [2.4] How is metabolic control analysis related to sensitivity analysis? Sensitivity analysis is a technique in engineering that shares much of the mathematics and concepts of metabolic control analysis. The control coefficients of metabolic control analysis are, in effect, sensitivities as understood by engineers. ************************** [2.5] What is a sensitivity? Sensitivity was the term used originally for what is now called a control coefficient, and it underlines the fact that metabolic control analysis is a form of sensitivity analysis. ************************** [2.6] What is a control strength? Control strength is an older term for what is now called a control coefficient. ************************** [2.7] What are the main questions that metabolic control analysis sets out to answer? Metabolic control analysis begins by recognizing that flux control is not a unique property of one "rate-limiting" enzyme in a pathway but is a distributed property shared among all of the enzymes. It then sets out to quantify the distribution. Similar considerations apply to concentrations of the intermediate metabolites in a pathway, and other variables whose values are set by the properties of the system. Such variables include the transit time (how long does it take on average for a molecule to traverse a system?) and other times, but these have received less attention than fluxes and concentrations. [3] Other Approaches ------------------------------------------------------------------------ [3.1] What is flux-oriented theory? Flux-oriented theory is an approach developed by E. A. Newsholme, B. Crabtree and their associates that can regarded as an alternative to metabolic control analysis for formalizing control relationships in metabolism. Although it has some similarities with metabolic control analysis it differs in important respects. In particular, it incorporates the concept of partially external regulators, whose concentrations are partially variable and partially constant. ************************** [3.2] What is biochemical systems theory? Biochemical systems theory is an approach developed by M. A. Savageau and his associates, who regard it as a general theory of metabolic control that includes metabolic control analysis and flux-oriented theory as special cases. It places much more emphasis on predicting how systems will behave when the conditions are changed than on understanding in physical terms how they are controlled. [4] Fundamental Concepts ------------------------------------------------------------------------ [4.1] What is an elasticity? An elasticity is a local property of an isolated enzyme that expresses how its rate varies with the concentration of any metabolite that affects it: this can be its substrate, product, or any other metabolite. An elasticity of, say, 0.5 with respect to a substrate means that a 2% increase in substrate concentration would increase the rate of the reaction catalysed by the enzyme by 1%, i.e. by 0.5 times 2%. Strictly speaking the definition applies to the limit at infinitesimally small changes, but it applies with reasonable accuracy for small changes, say up to 10 or 20%. It follows that substrate elasticities are positive (except under conditions of substrate inhibition), product elasticities are negative (except in the very rare case of product activation), activator elasticities are positive, and inhibitor elasticities are negative. Simple algebra shows that for an enzyme obeying Michaelis-Menten kinetics under irreversible conditions the substrate elasticity varies from 1 at very low concentrations down to zero at saturation. As this is exactly the behaviour attributed to the order of reaction (or kinetic order) with respect to substrate, one may wonder whether elasticity is just an obscure name for order of reaction: this is discussed elsewhere. Although substrate elasticities are normally between 0 and 1 (and are always numerically small) for irreversible reactions, it is crucial to realize that reversible reactions are very different. Substrate elasticities approach infinity for reactions close to equilibrium, and the passage from positive to negative as a substrate becomes a product when the reaction passes from one side of equilibrium to the other involves crossing infinity, not zero. This property means that it is essential to treat all reactions as reversible in computer simulations of metabolism unless it is absolutely certain that the reverse reaction is completely negligible under all circumstances simulated. ************************** [4.2] What is an elasticity coefficient? An elasticity coefficient is exactly the same as an elasticity; both terms are used. ************************** [4.3] What is a control coefficient? A control coefficient is the system property of an enzyme that expresses how some systemic variable, usually a flux or a metabolite concentration, depends on the activity of the enzyme. If some perturbation of an enzyme activity increases the rate of the isolated reaction by 5%, whereas the same perturbation of the same enzyme when it is embedded in a metabolic system increases the flux by 2%, the enzyme is said to have a flux control coefficient of 2/5, or 0.4. If the same perturbation causes the concentration of the substrate of the enzyme to decrease by 10%, the enzyme has a concentration control coefficient for that metabolite of -10/5, or -2. Notice that there is no mention of the concentration of the enzyme when the control coefficients are defined in this way. However, the rate of an enzyme-catalysed reaction is often found to be directly proportional to the enzyme concentration: if (and only if) this is the case the anonymous "perturbation" referred to in the definition can be a change in the enzyme concentration. This then allows a less abstract and apparently simpler definition of a control coefficient, and such a definition was widely used for a number of years. It is, however, falling into disuse, both because it is not always valid, and because even when it is valid it can encourage the wholly erroneous misconception that metabolic control analysis deals only with effects brought about by changes in enzyme concentration or limiting activity. In the older literature control coefficients were known as sensitivities or control strengths. ************************** [4.4] What is a response coefficient? A response coefficient defines the sensitivity of any system variable to any perturbation. For example, if increasing the concentration of an external inhibitor by 10% causes the flux through a pathway to decrease by 5% one may say that the response coefficient of the flux with respect to the inhibitor concentration is -5/10, or -0.5. ************************** [4.5] What are local and system properties? A major objective of metabolic control analysis is to treat systems as systems, rather than just as collections of components. Nonetheless, the properties of a system are determined by the properties of its components, and one needs a clear way of distinguishing between the two. It is important to understand that both the system and its components are matters of definition. In introductory accounts of metabolic control analysis one usual takes the system to be a pathway of four or five enzymes and the enzyme-catalysed reactions as its components. However, one may later want to expand the system to encompass a larger part of cell metabolism, and then the simpler system may be regarded as a component of the larger one. Moreover, the linear algebra that underlies the mathematical treatment of control analysis means that blocks of reactions behave in the same way as individual reactions. (This is the basis of "top-down analysis", which allows larger systems to be analysed by treating blocks of reactions as if they were single reactions). Thus glycolysis, for example, may be regarded as a complete system in one analysis but as a component of carbohydrate metabolism in another. None of this complicates matters as long as the terms used in an analysis are clearly defined, and one of the main criticisms of flux-oriented theory is that it does not define the limits of the system under study with sufficient precision and consequently allows potentially confusing concepts such as "partially externally regulators". Once the limits of the system are decided it is appropriate to consider system properties that apply complete system in the presence of all its components, whereas local properties are those of the isolated components. Study of isolated enzymes has been the major activity in kinetic investigations for most of this century, but there are important differences between kinetic measurements designed to reveal mechanistic information and those intended to aid in understanding system behaviour. In mechanistic studies one normally tries to make the reaction mixture as simple as possible to minimize ambiguities in the interpretation, and one often creates conditions very different from those in the cell (such as extreme concentrations of effectors) in order to illuminate differences between mechanisms that would be difficult to recognize under more physiological conditions. Neither of these is appropriate for considering the local properties of the component of a system: here the ideal is to mimic the conditions that exist in the complete system as exactly as possible, except that no other catalysts are present. Thus the isolated enzyme should "see" exactly the same concentrations of its substrates, products and any other metabolites that interact with it as it would see in the complete system. ************************** [4.6] What are the theorems of Metabolic Control Analysis? Indeed, what are they? Waiting for a contribution, but try this one: Briefly: The theorems of MCA represent special algebraic relationships between the coefficients of MCA. They originate from the unique structural and kinematic properties of the underlying metabolic system. For this reason they have important heuristic value for gaining insight into the nature and properties of metabolic systems. The theorems are also one of the distinguishing aspects of MCA and makes MCA more that just traditional sensitivity analysis, moreover the theorems are experimentally verifiable properties which makes MCA a credible scientific theory of cellular systems. The theorems of MCA can be classified to into two main groups (other less known groups also exist), the summation theorems, which include the 'classical' summation theorems and the branch theorems; and the all important connectivity theorems which connect local to system properties. ************************** [4.7] What are the summation relationships? The flux control coefficients for any given flux, summed over all the enzymes in the system, add up to 1. In an unbranched system there is only one flux, because in the steady state the rate through every reaction is the same. However, in a branched pathway there can be, and normally are, different fluxes in the different branches. In this case it is important that all of the flux control coefficients in the summation refer to the same flux, and that all of the enzymes in the pathway are included, regardless of whether they occur in the particular branch considered. A similar relationship applies to the concentration control coefficients for any given metabolite. However, in this case the values add up to 0. There are other summation relationships for other system variables. For example, one can define transit time control coefficients for the time required on average for mass to pass through a system, and these control coefficients add up to -1. ************************** [4.8] What is the connectivity relationship? For any metabolite and any flux in a system, one can multiply the flux control coefficient of an enzyme by its elasticity with respect to the metabolite concerned. If one does this for all of the enzymes in the system and adds all the resulting products, they give a sum of zero. This is the general form of the connectivity relationship. For metabolites that have non-zero elasticities for numerous enzymes (i.e. for metabolites that influence the activities of numerous enzymes) the resulting sum contains many terms and is not particularly useful. However, if a metabolite influences only two enzymes, as for example the enzyme that produces it and the enzyme that consumes it, it will have only two non-zero elasticities, and the sum will contain only two terms, each of which must then be minus the other. In this case the connectivity relationship becomes much more useful, as it provides a way of calculating an unknown control coefficient from a known one, provided the relevant elasticities are also known. ************************** [4.9] Why "elasticity" (rather than, say, "order of reaction")? The term "elasticity" comes from the science of econometrics, where one may say, for example, that if the demand for cars decreases by 6% when the price of cars increases by 3% then there is a demand-price elasticity for cars of 2 (= 6/3). In metabolic control analysis one says that there is a substrate elasticity of 2 if the rate of a reaction increases by 6% when the substrate concentration increases by 3%. Note two differences: there is change of sign, so that the econometric elasticity would be -2, not 2, if the conventions of metabolic control analysis applied; second, econometric elasticities are usually greater than 1, whereas in control analysis elasticities in irreversible processes are usually (though not always) between -1 and 1. Given that most biochemists are more familiar with chemistry (in which the order of reaction has much in common with an elasticity) than with econometrics, one may wonder why the less familiar term is retained in metabolic control analysis, especially as biochemical systems theory uses the term "kinetic order" for the corresponding quantity. There are in fact two reasons, though neither is very persuasive. Strictly speaking a chemical order of reaction ought to be an integer, whereas an elasticity is rarely an integer; nonetheless, the use of the "order of reaction" for a non-integral quantity is widespread in biochemistry, and normally causes no problems. Perhaps more important, a kinetic order in biochemical systems theory is a parameter in a power-law equation, and as such must be constant over the range of validity of the equation (because a law has to be expressed in terms of constants if it is to be meaningful). By contrast, metabolic control analysis never assumes that elasticities are constant, and in understanding how systems behave it is important to realize that elasticities (and control coefficients) vary with the conditions. For this reason there may be some merit in retaining a distinct term. ************************** [4.10] How is metabolic control analysis related to classical ideas of metabolic regulation? Because of the abstraction of mechanistic details into the elasticities of metabolic control analysis, the classical concepts of feedback inhibition of the first committed step of a pathway, cooperativity, etc., can seem to be forgotten about, or at least hidden as mathematical details. However, their effects on the distribution of control have been well understood (albeit not much emphasized) since the original paper of Kacser and Burns (1973). ************************** [4.11] The Two Fundamental Equations of Metabolic Control Analysis MCA can boast two fundamental equations that summarise the main ideas of MCA, the first equation is the relationship between the local properties of a system and its global behaviour, in matrix form this equation is: C = inv (E) where C is the matrix of control coefficients and E the matrix of elasticity coefficients (modified with network structural information). The second fundamental equation of MCA is the response relationship, this relates the three most important quantitative measures in MCA into one relation, that is the control coefficient, the response coefficient and the system boundary elasticities. R = C E ************************** [4.12] Why does metabolic control analysis appear to ignore enzyme mechanisms? Metabolic control analysis tends to treat the kinetic properties of the component enzymes as a black box. Some authors have been very critical of this, suggesting that shedding light on mechanism is the only reason for studying kinetics in the first place. However, in reality it is the usual kind of abstraction one finds (and needs) at all level of science. Although wave mechanics is at the basis of all chemistry, it is hardly possible to present a list of typical reactions of aldehydes, for example, in terms of wave equations. Even if it were possible it would not be helpful because it would hide the points of immediate interest in a lot of algebra. At another level, all interactions between living organisms are dependent on the laws of chemistry, but again, it would be neither possible nor, if it were possible, helpful to discuss the political relationships between countries in terms of chemical reactions. Studies of biochemical kinetics have been dominated for nearly a century by an interest in molecular mechanisms, but for understanding how whole pathways behave it has been found useful to decrease the emphasis on mechanism. Thus mechanisms such as cooperative feedback inhibition are not ignored in metabolic control analysis, but they are given less emphasis than in classical studies of metabolic regulation. ************************** [4.13] What is the partitioned response relationship? If an external parameter, such as the concentration of an inhibitor, acts on only one enzyme in a system, the response coefficient for any system variable can be obtained by multiplying the appropriate control coefficient for the enzyme acted on by the elasticity of the same enzyme with respect to the external parameter. (If the external parameter acts on more than one enzyme the response coefficient is the sum of several such terms, one for each affected enzyme. However, this case is inconvenient to apply, and experimentally one normally tries to avoid it by using specific effectors.) [5] Specific Metabolic Concepts ------------------------------------------------------------------------ [5.1] How does feedback inhibition affect the distribution of flux control in a pathway? The effect of feedback inhibition by an end-product of the first committed step in its biosynthesis is to transfer flux control away from that step in order to increase the share of control residing in the reactions that consume the end-product. This can be seen as a means of transferring flux control from supply to demand. ************************** [5.2] How can yields of metabolic processes be improved for biotechnological purposes? Since it became possible (around 1980) to identify the genes responsible for the synthesis of enzymes and to overexpress them in mutant organisms, a major objective of biotechnology has been to identify the rate-limiting enzymes in pathways that lead to commercially important products, so that they can been overexpressed in the hope of increasing the yields of the desired products. Despite enormous financial investment around the world these efforts have been wholly unsuccessful, at least to the present, no examples of successes from them being known. Metabolic control analysis leads one to believe that rate-limiting enzymes as classically conceived do not exist and that therefore one cannot expect any successes in the future from an approach that is fundamentally misconceived. If it is accepted (i) that regulatory mechanisms evolved to serve the needs of the organisms that possess them, and (ii) that their major effect in practice is to transfer flux control away from the regulated enzyme, then it follows that they can be expected to oppose, probably with great efficiency, any attempt to force more material through a pathway. This not only explains why the naive approach is unlikely to work; it also suggests two strategies that may work better: either to select mutants in which the feedback loops are suppressed, or to subvert the feedback loops to biotechnological ends by artificially stimulating demand, e.g. by engineering a leak of the desired product into the medium. ************************** [5.2] Why isn't Phosphofructokinase (PFK) rate-limiting? What? You mean it isn't? Refer to any undergrad text book and you can almost guarantee that PFK will be referred to as *the* rate-limiting step. However ample experimental evidence now shows us that PFK is anything but rate-limiting. Waiting for someone to write a short summary to fill in the details. ************************** [5.3] Supply and Demand Theory of Metabolic Systems Waiting for someone to write a short summary ************************** [5.4] TurboCharging Interesting property of glycolysis. Waiting for someone to write a short summary ************************** [5.5] How does channelling affect the summation relationships? The term channelling refers to mechanisms in which the product of one enzyme is transferred directly to an enzyme that uses it as substrate without necessarily passing through the free solution. This implies the existence of a complex between the two (or more) enzymes involved, a static complex if it has a long life time and exists independently of whether the reaction is proceeding, or a dynamic complex if it is formed transiently during the catalysis. In either case increasing the concentration of one component enzyme of the complex affects the concentrations both of the free component and those of any complexes that it forms with other enzymes. As these various different species may have different kinetic constants for the reactions in which they are involved the rate of the reaction catalysed by the enzyme whose total concentration is varied will not be proportional to that concentration. As long as the summation relationships are expressed in terms of control coefficients that refer to the independent catalysts, in accordance with modern practice, they are not affected by channelling. As it is no longer true that the individual rates are proportional to the concentrations of the individual enzymes, however, the summation relationships no longer apply if the control coefficients refer to enzyme concentrations rather than catalytic activities. With static complexes the deviations may be large, but with dynamic complexes they still usually apply approximately. ************************** [5.6] What is a controllability coefficient? Controllability coefficient was the term used originally for the elasticity to a parameter (rather than to an intermediate metabolite). Not all authors find it useful to make this distinction. Those who do sometimes use the term "kappa elasticity" or "-elasticity" for the old controllability coefficient. What is the top-down approach to metabolic control analysis? In the top-down approach developed by Brown, Hafner and Brand one seeks to allow the analysis of complex metabolic systems by grouping reactions into blocks, which are then treated as if they were single enzymes. ************************** [5.7] Is it true that metabolic control analysis assumes that enzymes are regulated solely by changing their concentrations (or V values)? No! This is a serious misconception that has bedevilled understanding of metabolic control analysis for years. It arose from the once-common practice of defining control coefficients in terms of changes of enzyme concentration. However, the modern practice is to regard "control coefficients" defined in this way as response coefficients (for response to changes in enzyme concentration) that may happen to be numerically equal to control coefficients only because the relevant elasticities are equal to 1. In any case, the partitioned response property means that the magnitude of the response of a system to any effector is determined by the elasticity of the enzyme acted on by the effector with respect to that effector multiplied by the control coefficient for that enzyme. ************************** [5.8] How does metabolic control analysis explain the fact that most mutations in diploid organisms are recessive? In a diploid organism the usual possibilities for the degree of expression of an enzyme are 100% (normal homozygote), 50% (heterozygote) and 0% (abnormal homozygote) of the activity in the normal homozygote. However, the flux control coefficients of most enzymes are close to zero, and although they increase if the enzyme activity is decreased they rarely increase to significant levels if the activity decrease is 50% or less. Thus heterozygotes, with only 50% activity of the affected enzyme, can maintain essentially the same metabolic fluxes as individuals with 100% activity. However, if an enzyme activity falls to zero its flux control coefficient for the flux through its own reaction becomes 1, as the capacity to supply flux through the pathway in question vanishes. Thus although heterozygotes typically display little or no phenotypic difference from normal homozygotes, abnormal homozygotes display the phenotype characteristic of the complete loss of a metabolic pathway. ************************** [5.9] How does metabolic control analysis aid in understanding mitochondrial myopathies and other metabolic diseases? The relatively small number of enzymes that are expressed by mitochondrial genes behave differently from enzymes expressed by nuclear genes when mutations are present. This is because heterogeneity of the mitochondrial population and variations in the numbers of mitochondria in each cell allow the activity of an enzyme present in both normal and mutant forms to vary over the range 0-100% with many intermediate values possible (not just 50%, as for the case of a heterozygote in a diploid organism for an enzyme expressed by a nuclear gene). As with al l enzymes, mitochondrial enzymes typically have small flux control coefficients for any given flux, but these increase as the enzyme activity decreases. The point at which any given enzyme becomes "important" in the sense that variations in activity produce obvious phenotypic effects varies with the enzyme. Thus some mitochondrial enzymes can fall to quite low levels of activity before medical problems arise, whereas others cannot. ************************** [5.10] Competitive and UnCompetitive inhibition Waiting for someone to write a short summary [6] Real-World Metabolic Models ------------------------------------------------------------------------ Yes, there are some, but currently waiting for someone to write a short summary [7] Computational Resources ------------------------------------------------------------------------ [7.1] What programs are available for metabolic modelling? There are currently two software packages that are the preferred tools for modelling metabolic systems, these are Gepasi and Scamp (now being updated to Scamp II - Jarnac). Both systems run under Windows 95/98/NT, Gepasi and Scamp II are currently available free of charge. MetaModel* runs on MS-DOS with very basic hardware requirements (i.e. it will run on any PC-type computer from the past ten years or so). Brief descriptions of these and other programs may be found elsewhere*. I believe there is one metabolic simulation package for the Macintosh, I think it's called KinCyte but I can't find a web site for it. More details of other simulation packages to follow. Contributions here are very welcome ! ************************** [7.2] Where can I find information on computational algorithms for metabolic analysis? Information on computational algorithms used in metabolic analysis is not readily available on the net. There is only one site which currently has any information on algorithms (and not too much either) used in metabolic analysis and that is the site at: http://fssc.demon.co.uk under the biotech page ************************** [7.3] What advantages does modelling have over algebraic analysis? Before metabolic control analysis existed modelling of metabolic systems in the computer was the only realistic way that a biochemist could get any idea of how a complex metabolic system might behave in different conditions. However, it was very demanding, in terms both of computer expertise and indeed of hardware, and as a result its use was confined to a few experts and the insights that came from it were very little diffused in the biochemical world. The situation has now completely changed in that a number of powerful programs are widely available for use on common computer systems without particular expertise in computational or modelling techniques. The question arises, however, of why one might want to model metabolic systems now that metabolic control analysis provides much insight into how they behave, which is valid in general without reference to particular systems. In fact there are several reasons why most people active in control analysis continue to use both analysis and modelling. The most obvious is that it is usually very much faster and easier to obtain specific numerical information about a metabolic system by computer modelling than by algebra, and one can easily set up quite complicated models and ask and answer complicated questions about them. Even if the answers may subsequently be generalized as theorems of metabolic control analysis the insights that allow the algebraic analysis often come in the first place from modelling. [8] People and References ------------------------------------------------------------------------ [8.1] Where can I find more detailed information in the printed literature? The two classic papers that introduced metabolic control analysis are those of Kacser and Burns (1973) and Heinrich and Rapoport (1974). The former has recently been reissued in a revised form (Kacser, Burns and Fell, 1995) that is probably more appropriate for the modern reader, both because it is more easily accessible and because it is expressed in the terminology currently in use. Two recent monographs mainly concerned with metabolic control analysis are those of Fell (1996) and Heinrich and Schuster (1996), of which the former is fairly elementary and the latter fairly advanced. (I have reviewed* both of these.) Chapter 10 of the book on enzyme kinetics by Cornish-Bowden (1995a) is concerned with metabolic control analysis, and is now available as hypertext*. A multiauthor book edited by Cornish-Bowden and Cárdenas (1990) contains an almost complete picture of metabolic control analysis as it was in 1989 (as well as some chapters on biochemical systems theory and a brief account of flux-oriented theory). The issue of the Journal of Theoretical Biology for 7th October 1996 is a special issue in memory of Henrik Kacser, and contains many contributions concerned with current applications of metabolic control analysis. Abstracts* of all of the contributions are available on the web. Two recent reviews of metabolic control analysis are those of Fell (1992) and Cornish-Bowden (1995b). A collection of references to reviews on channelling and related topics is available on the web. ************************** [8.2] How do I contact people working on metabolic control analysis? There is a list on this web-site http://ir2lcb.cnrs-mrs.fr/~athel of names, addresses, telephone and fax numbers, e-mail addresses and URLs of web-sites, for people who are or have been active in the field. ************************** [8.3] Where can I find information about meetings related to metabolic control analysis? There is a web page (http://ir2lcb.cnrs-mrs.fr/~athel) with general information about forthcoming meetings, mainly ones with some relationship with metabolic control analysis. Suggestions for additions to this page are always welcome. The BTK (BioThermoKinetics group) maintains a regular programme of meetings (at two-year intervals) with a substantial content of metabolic control analysis. The 9th BTK meeting will be at Stellenbosch (South Africa) in April 2000. ************************** [8.4] References Only sources specifically referred to are listed here. A longer list is given with the web version of Chapter 10 of Fundamentals of Enzyme Kinetics, and another one forms part of the MCA Web, and other references may be found in the articles listed. G. C. Brown, R. Hafner and M. D. Brand (1990) A 'top-down' approach to the determination of control coefficients in metabolic control theory. Eur. J. Biochem. 188, 321-325 [@] A. Cornish-Bowden (1995a) Fundamentals of Enzyme Kinetics (2nd edn.), pp. 239-270, Portland Press, London [@] A. Cornish-Bowden (1995b) Metabolic control analysis in theory and practice. Adv. Mol. Cell. Biol. 11, 21-64 [@] A. Cornish-Bowden and M. L. Cárdenas, eds. (1990) Control of Metabolic Processes, Plenum Press, New York [@] B. Crabtree and E. A. Newsholme (1987) The derivation and interpretation of control coefficients. Biochem. J. 247, 113-120 [@] D. A. Fell (1992) Metabolic control analysis: a survey of its theoretical and experimental development. Biochem. J. 286, 313-330 [@] D. A. Fell (1996) Understanding the Control of Metabolism, Portand Press, London [@] R. Heinrich and T. A. Rapoport (1974) A linear steady-state treatment of enzymatic chains. Critique of the crossover theorem and a general procedure to identify interaction sites with an effector. Eur. J. Biochem. 42, 89-95 [@] R. Heinrich and S. Schuster (1996) The Regulation of Cellular Systems, Chapman and Hall, New York [@] H. Kacser and J. A. Burns (1973) The control of flux. Symp. Soc. Exp. Biol. 27, 65-104 [@] H. Kacser, J. A. Burns and D. A. Fell (1995) The control of flux. Biochem. Soc. Trans. 23, 341-391 [@] M. A. Savageau (1976) Biochemical Systems Analysis: a Study of Function and Design in Molecular Biology, Addison-Wesley, Reading, Massachusetts. [@] ************************** [8.5] Are there any books devoted to metabolic control analysis? There are two recent books that deal extensively with metabolic control analysis. One is elementary: Understanding the Control of Metabolism, by David Fell, Portland Press, London, 1997. The other is much more advanced: The Regulation of Cellular Systems, by Reinhart Heinrich and Stefan Schuster, Chapman and Hall, New York, 1996. ************************** [8.6] Why is the question that interests me not listed? There are three possible reasons: No one has asked before. The question is not really relevant to metabolic control analysis, or is too specific (e.g. questions like "which enzyme has the highest flux control coefficient in glycolysis in well-fed rats?" are not sufficiently general for this page: they would be better addressed to the BTK-MCA Newsgroup Archive). I don't know the answer. If your question belongs in category 1, or if it belongs in category 3 and you have an answer to suggest, please send me a message, in which you: Specify the question you would like included, and (if you like) Suggest an answer. ************************** [8.7] Where can I find more detailed information on the web? Some possibilities are as follows: Pedro Mendes' MCA Web The web version of Chapter 10 of Fundamentals of Enzyme Kinetics, Douglas Kell's Canon of reviews on metabolic organization, channelling and control. Herbert Sauro's Biotechnology site at http://members.tripod.co.uk/sauro/biotech.htm [9] Acknowledgments ------------------------------------------------------------------------ Many thanks to Athel Cornish-Bowden for permitting me to redistribute and modify his Web-site FAQ for the bionet.metabolic-reg newsgroup. Any errors in this document are the sole responsibility of the maintainer. .