[{"@context":"http:\/\/schema.org\/","@type":"BlogPosting","@id":"https:\/\/wiki.edu.vn\/en\/wiki41\/elasticity-coefficient-wikipedia\/#BlogPosting","mainEntityOfPage":"https:\/\/wiki.edu.vn\/en\/wiki41\/elasticity-coefficient-wikipedia\/","headline":"Elasticity coefficient – Wikipedia","name":"Elasticity coefficient – Wikipedia","description":"before-content-x4 Elasticity coefficients are used in physics, economics, chemistry, or more generally in mathematics as a definition of point elasticity:","datePublished":"2020-03-09","dateModified":"2020-03-09","author":{"@type":"Person","@id":"https:\/\/wiki.edu.vn\/en\/wiki41\/author\/lordneo\/#Person","name":"lordneo","url":"https:\/\/wiki.edu.vn\/en\/wiki41\/author\/lordneo\/","image":{"@type":"ImageObject","@id":"https:\/\/secure.gravatar.com\/avatar\/c9645c498c9701c88b89b8537773dd7c?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/c9645c498c9701c88b89b8537773dd7c?s=96&d=mm&r=g","height":96,"width":96}},"publisher":{"@type":"Organization","name":"Enzyklop\u00e4die","logo":{"@type":"ImageObject","@id":"https:\/\/wiki.edu.vn\/wiki4\/wp-content\/uploads\/2023\/08\/download.jpg","url":"https:\/\/wiki.edu.vn\/wiki4\/wp-content\/uploads\/2023\/08\/download.jpg","width":600,"height":60}},"image":{"@type":"ImageObject","@id":"https:\/\/wikimedia.org\/api\/rest_v1\/media\/math\/render\/svg\/1ac83d8b290ebc73a56a8a1b5e16af64522017eb","url":"https:\/\/wikimedia.org\/api\/rest_v1\/media\/math\/render\/svg\/1ac83d8b290ebc73a56a8a1b5e16af64522017eb","height":"","width":""},"url":"https:\/\/wiki.edu.vn\/en\/wiki41\/elasticity-coefficient-wikipedia\/","wordCount":13922,"articleBody":"     (adsbygoogle = window.adsbygoogle || []).push({});before-content-x4Elasticity coefficients are used in physics, economics, chemistry, or more generally in mathematics as a definition of point elasticity: the article below applies to chemical\/biochemical elasticity coefficients. For the ratio between the initial and final velocities in a collision, see Coefficient of restitution. For others, see ElasticityThe rate of a chemical reaction is influenced by many different factors, such as temperature, pH, reactant, and product concentrations and other effectors. The degree to which these factors change the reaction rate is described by the elasticity coefficient. This coefficient is defined as follows:\u03b5siv=(\u2202v\u2202sisiv)sj,sk,\u2026=\u2202ln\u2061v\u2202ln\u2061si\u2248v%si%{displaystyle varepsilon _{s_{i}}^{v}=left({frac {partial v}{partial s_{i}}}{frac {s_{i}}{v}}right)_{s_{j},s_{k},ldots }={frac {partial ln v}{partial ln s_{i}}}approx {frac {v%}{s_{i}%}}}       (adsbygoogle = window.adsbygoogle || []).push({});after-content-x4where v{displaystyle v} denotes the reaction rate and        (adsbygoogle = window.adsbygoogle || []).push({});after-content-x4s{displaystyle s} denotes the substrate concentration. Be aware that the notation will use lowercase roman letters, such as s,{displaystyle s,} to indicate concentrations.The partial derivative in the definition indicates that the elasticity is measured with respect to changes in a factor S while keeping all other factors constant. The most common factors include substrates, products, and effectors. The scaling of the coefficient ensures that it is dimensionless and independent of the units used to measure the reaction rate and magnitude of the factor. The elasticity coefficient is an integral part of metabolic control analysis and was introduced in the early 1970s and possibly earlier by Henrik Kacser and Burns[1] in Edinburgh and Heinrich and Rapoport[2] in Berlin.The elasticity concept has also been described by other authors, most notably Savageau[3] in Michigan and Clarke[4] at Edmonton. In the late 1960s Michael Savageau[3] developed an innovative approach called biochemical systems theory that uses power-law expansions to approximate the nonlinearities in biochemical kinetics. The theory is very similar to metabolic control analysis and has been very successfully and extensively used to study the properties of different feedback and other regulatory structures in cellular networks. The power-law expansions used in the analysis invoke coefficients called kinetic orders, which are equivalent to the elasticity coefficients.       (adsbygoogle = window.adsbygoogle || []).push({});after-content-x4Bruce Clarke[4] in the early 1970s, developed a sophisticated theory on analyzing the dynamic stability in chemical networks. As part of his analysis, Clarke also introduced the notion of kinetic orders and a power-law approximation that was somewhat similar to Savageau’s power-law expansions. Clarke’s approach relied heavily on certain structural characteristics of networks, called extreme currents (also called elementary modes in biochemical systems).  Clarke’s kinetic orders are also equivalent to elasticities.Elasticities can also be usefully interpreted as the means by which signals propagate up or down a given pathway.[5]The fact that different groups independently introduced the same concept implies that elasticities, or their equivalent, kinetic orders, are most likely a fundamental concept in the analysis of complex biochemical or chemical systems.Table of ContentsCalculating elasticity coefficients[edit]Algebraic calculation of elasticity coefficients[edit]Numerical calculation of elasticity coefficients[edit]Interpretation of the log form[edit]Differentiating in log space[edit]Elasticity matrix[edit]See also[edit]References[edit]Further reading[edit]Calculating elasticity coefficients[edit]Elasticity coefficients can be calculated either algebraically or by numerical means.Algebraic calculation of elasticity coefficients[edit]Given the definition of the elasticity coefficient in terms of a partial derivative, it is possible, for example, to determine the elasticity of an arbitrary rate law by differentiating the rate law by the independent variable and scaling. For example, the elasticity coefficient for a mass-action rate law such as:v=k\u00a0s1n1s2n2{displaystyle v=k s_{1}^{n_{1}}s_{2}^{n_{2}}}where v{displaystyle v} is the reaction rate, k{displaystyle k} the reaction rate constant, si{displaystyle s_{i}} is the ith chemical species involved in the reaction and ni{displaystyle n_{i}} the ith reaction order, then the elasticity, \u03b5s1v{displaystyle varepsilon _{s_{1}}^{v}} can be obtained by differentiating the rate law with respect to s1{displaystyle s_{1}} and scaling:\u03b5s1v=\u2202v\u2202s1s1v=n1\u00a0k\u00a0s1n1\u22121s2n2s1k\u00a0s1n1s2n2=n1{displaystyle varepsilon _{s_{1}}^{v}={frac {partial v}{partial s_{1}}}{frac {s_{1}}{v}}=n_{1} k s_{1}^{n_{1}-1}s_{2}^{n_{2}}{frac {s_{1}}{k s_{1}^{n_{1}}s_{2}^{n_{2}}}}=n_{1}}That is, the elasticity for a mass-action rate law is equal to the order of reaction of the species.For example the elasticity of A in the reaction 2A\u21ccC{displaystyle 2Arightleftharpoons C} where the rate of reaction is given by: v=kA2{displaystyle v=kA^{2}}, the elasticity can be evaluated using:\u03b5av=\u2202v\u2202aav=2kaaka2=2{displaystyle varepsilon _{a}^{v}={frac {partial v}{partial a}}{frac {a}{v}}={frac {2kaa}{ka^{2}}}=2}Elasticities can also be derived for more complex rate laws such as the Michaelis\u2013Menten rate law. Ifv=VmaxsKm+s{displaystyle v={frac {V_{max }s}{K_{m}+s}}}then it can be easily shown than\u03b5sv=KmKm+s{displaystyle varepsilon _{s}^{v}={frac {K_{m}}{K_{m}+s}}}This equation illustrates the idea that elasticities need not be constants (as with mass-action laws) but can be a function of the reactant concentration. In this case, the elasticity approaches unity at low reactant concentration (s) and zero at high reactant concentration.  A. The slope of the reaction rate versus the reactant concentration scaled by both the reactant concentration and reaction rate yields the elasticity. If the log of the reaction rate and the log of the reactant concentration is plotted, the elasticity can be read directly from the slope of the curve. Curves were generated by assuming v = S\/(2 + S)For the reversible Michaelis\u2013Menten rate law:v=Vmax\/Km1(s\u2212p\/Keq)1+s\/Km1+p\/Km2{displaystyle v={frac {V_{max }\/K_{m_{1}}(s-p\/K_{text{eq}})}{1+s\/K_{m_{1}}+p\/K_{m_{2}}}}}where Vmax{displaystyle V_{max }} is the forward Vmax{displaystyle V_{max}}, Km1{displaystyle K_{m_{1}}} the forward Km{displaystyle K_{m}}, Keq{displaystyle K_{eq}} the equilibrium constant  and Km2{displaystyle K_{m_{2}}} the reverse Km{displaystyle K_{m}}, two elasticity coefficients can be calculated, one with respect to substrate, S, and another with respect to product, P. Thus:\u03b5sv=11\u2212\u0393\/Keq\u2212s\/Km11+s\/Km1+p\/Km2{displaystyle varepsilon _{s}^{v}={frac {1}{1-Gamma \/K_{text{eq}}}}-{frac {s\/K_{m_{1}}}{1+s\/K_{m_{1}}+p\/K_{m_{2}}}}}\u03b5pv=\u2212\u0393\/Keq1\u2212\u0393\/Keq\u2212p\/Km21+s\/Km1+p\/Km2{displaystyle varepsilon _{p}^{v}={frac {-Gamma \/K_{text{eq}}}{1-Gamma \/K_{text{eq}}}}-{frac {p\/K_{m_{2}}}{1+s\/K_{m_{1}}+p\/K_{m_{2}}}}}where \u0393{displaystyle Gamma } is the mass-action ratio, that is \u0393=p\/s{displaystyle Gamma =p\/s}. Note that when p = 0, the equations reduce to the case for the irreversible Michaelis\u2013Menten law.As a final example, consider the Hill equation:v=Vmax(s\/Ks)n1+(s\/Ks)n{displaystyle v={frac {V_{max }(s\/K_{s})^{n}}{1+(s\/K_{s})^{n}}}}where n is the Hill coefficient and Ks{displaystyle K_{s}} is the half-saturation coefficient (cf. Michaelis\u2013Menten rate law), then the elasticity coefficient is given by:\u03b5sv=n1+(s\/Ks)n{displaystyle varepsilon _{s}^{v}={frac {n}{1+(s\/K_{s})^{n}}}}Note that at low  concentrations of S the elasticity approaches\u00a0n. At high concentrations of S the elasticity approaches zero. This means the elasticity is bounded between zero and the Hill coefficient.Numerical calculation of elasticity coefficients[edit]Elasticities coefficient can also be computed numerically, something that is often done in simulation software.[6]For example, a small change (say 5%) can be made to the chosen reactant concentration, and the change in the reaction rate recorded. To illustrate this, assume that the reference reaction rate is vo{displaystyle v_{o}}, and the reference reactant concentration, so{displaystyle s_{o}}. If we increase the reactant concentration by \u0394so{displaystyle Delta s_{o}} and record the new reaction rate as v1{displaystyle v_{1}}, then the elasticity can be estimated by using Newton’s difference quotient:\u03b5sv\u2243v1\u2212vo\u0394sosovo=v1\u2212vovo\/s1\u2212soso{displaystyle varepsilon _{s}^{v}simeq {frac {v_{1}-v_{o}}{Delta s_{o}}}{frac {s_{o}}{v_{o}}}={frac {v_{1}-v_{o}}{v_{o}}}\/{frac {s_{1}-s_{o}}{s_{o}}}}A much better estimate for the elasticity can be obtained by doing two separate perturbations in so{displaystyle s_{o}}. One perturbation to increase so{displaystyle s_{o}} and another to decrease so{displaystyle s_{o}}. In each case, the new reaction rate is recorded; this is called the two-point estimation method. For example, if v1{displaystyle v_{1}} is the reaction ratewhen we increase so{displaystyle s_{o}}, and v2{displaystyle v_{2}} is the reaction rate when we decrease so{displaystyle s_{o}}, thenwe can use the following two-point formula to estimate the elasticity:\u03b5sv\u224312v1\u2212v2s1\u2212so(sovo){displaystyle varepsilon _{s}^{v}simeq {frac {1}{2}}{frac {v_{1}-v_{2}}{s_{1}-s_{o}}}left({frac {s_{o}}{v_{o}}}right)}Interpretation of the log form[edit]Consider a variable y{displaystyle y} to be some function f(x){displaystyle f(x)}, that is y=f(x){displaystyle y=f(x)}. If x{displaystyle x} increases from x{displaystyle x} to (x+h){displaystyle (x+h)} then the change in the value of y{displaystyle y} will be given by f(x+h)\u2212f(x){displaystyle f(x+h)-f(x)}. The proportional change, however, is given by:f(x+h)\u2212f(x)f(x){displaystyle {frac {f(x+h)-f(x)}{f(x)}}}The rate of proportional change at the point x{displaystyle x} is given by the above expression divided by the step change in the x{displaystyle x} value, namely h{displaystyle h}:Rate of proportional change ={displaystyle =}limh\u21920f(x+h)\u2212f(x)hf(x)=1f(x)limh\u21920f(x+h)\u2212f(x)h=1ydydx{displaystyle lim _{hrightarrow 0}{frac {f(x+h)-f(x)}{hf(x)}}={frac {1}{f(x)}}lim _{hrightarrow 0}{frac {f(x+h)-f(x)}{h}}={frac {1}{y}}{frac {dy}{dx}}}Using calculus, we know thatdln\u2061ydx=1ydydx{displaystyle {frac {dln y}{dx}}={frac {1}{y}}{frac {dy}{dx}}},therefore the rate of proportional change equals:dln\u2061ydx{displaystyle {frac {dln y}{dx}}}This quantity serves as a measure of the rate of proportional change of the function y{displaystyle y}. Just as dy\/dx{displaystyle dy\/dx} measures the gradient of the curve y=f(x){displaystyle y=f(x)} plotted on a linear scale, dln\u2061y\/dx{displaystyle dln y\/dx} measures the slope of the curve when plotted on a semi-logarithmic scale, that is the rate of proportional change. For example, a value of 0.05{displaystyle 0.05} means that the curve increases at 5%{displaystyle 5%} per unit x{displaystyle x}.The same argument can be applied to the case when we plot a function on both x{displaystyle x} and y{displaystyle y} logarithmic scales. In such a case, the following result is true:dln\u2061ydln\u2061x=xydydx{displaystyle {frac {dln y}{dln x}}={frac {x}{y}}{frac {dy}{dx}}}Differentiating in log space[edit]An approach that is amenable to algebraic calculation by computer algebra methods is to differentiate in log space. Since the elasticity can be defined logarithmically, that is:\u03b5sv=\u2202ln\u2061v\u2202ln\u2061s{displaystyle varepsilon _{s}^{v}={frac {partial ln v}{partial ln s}}}differentiating in log space is an obvious approach. Logarithmic differentiation is particularly convenient in algebra software such as Mathematica or Maple, where logarithmic differentiation rules can be defined.[7]Elasticity matrix[edit]The unscaled elasticities can be depicted in matrix form, called the unscaled elasticity matrix, E{displaystyle {mathcal {E}}}. Given a network with m{displaystyle m} molecular species and n{displaystyle n} reactions, the unscaled elasticity matrix is defined as:E=[\u2202v1\u2202s1\u22ef\u2202v1\u2202sm\u22ee\u22f1\u22ee\u2202vn\u2202s1\u22ef\u2202vn\u2202sm].{displaystyle {mathcal {E}}={begin{bmatrix}{dfrac {partial v_{1}}{partial s_{1}}}&cdots &{dfrac {partial v_{1}}{partial s_{m}}}\\vdots &ddots &vdots \\{dfrac {partial v_{n}}{partial s_{1}}}&cdots &{dfrac {partial v_{n}}{partial s_{m}}}end{bmatrix}}.}Likewise, is it also possible to define the matrix of scaled elasticities:\u03b5=[\u03b5s1v1\u22ef\u03b5smv1\u22ee\u22f1\u22ee\u03b5s1vn\u22ef\u03b5smvn].{displaystyle mathbf {varepsilon } ={begin{bmatrix}varepsilon _{s_{1}}^{v_{1}}&cdots &varepsilon _{s_{m}}^{v_{1}}\\vdots &ddots &vdots \\varepsilon _{s_{1}}^{v_{n}}&cdots &varepsilon _{s_{m}}^{v_{n}}end{bmatrix}}.}See also[edit]References[edit]^ Kacser, Henrik; Burns, J. (1973). “The control of flux”. Symposia of the Society for Experimental Biology. 27: 65\u2013104. PMID\u00a04148886.^ Heinrich, Reinhart; A. Rapoport, Tom (1974). “A Linear Steady-State Treatment of Enzymatic Chains: General Properties, Control and Effector Strength”. European Journal of Biochemistry. 42 (1): 89\u201395. doi:10.1111\/j.1432-1033.1974.tb03318.x. PMID\u00a04830198.^ a b A. Savageau, Michael (1976). Biochemical Systems Analysis. Addison Wesley Longman Publishing Company.^ a b L. Clarke, Bruce (1980). “Stability of Complex Reaction Networks”. Advances in Chemical Physics. 43: 1\u2013215. doi:10.1002\/9780470142622.ch1. ISBN\u00a09780470142622.^ Christensen, Carl D.; Hofmeyr, Jan-Hendrik S.; Rohwer, Johann M. (28 November 2018). “Delving deeper: Relating the behaviour of a metabolic system to the properties of its components using symbolic metabolic control analysis”. PLOS ONE. 13 (11): e0207983. doi:10.1371\/journal.pone.0207983. PMC\u00a06261606. PMID\u00a030485345.^ Yip, Evan; Sauro, Herbert (8 October 2021). “Computing Sensitivities in Reaction Networks using Finite Difference Methods”. arXiv:2110.04335 [q-bio.QM].^ H. Woods, James; M. Sauro, Herbert (1997). “Elasticities in Metabolic Control Analysis: Algebraic Derivation of Simplified Expressions”. Computer Applications in the Biosciences. 13 (2): 23\u2013130. doi:10.1093\/bioinformatics\/13.2.123. PMID\u00a09146958.Further reading[edit]Cornish-Bowden, Athel (1995). Fundamentals of Enzyme Kinetics. Portland Press.Fell D. (1997). Understanding the Control of Metabolism. Portland Press.Heinrich, Reinhart; Schuster, Stefan (1996). The Regulation of Cellular Systems. Chapman and Hall.     (adsbygoogle = window.adsbygoogle || []).push({});after-content-x4"},{"@context":"http:\/\/schema.org\/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"https:\/\/wiki.edu.vn\/en\/wiki41\/#breadcrumbitem","name":"Enzyklop\u00e4die"}},{"@type":"ListItem","position":2,"item":{"@id":"https:\/\/wiki.edu.vn\/en\/wiki41\/elasticity-coefficient-wikipedia\/#breadcrumbitem","name":"Elasticity coefficient – Wikipedia"}}]}]