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The Lineweaver–Burk plot derives from a transformation of the Michaelis–Menten equation, = + in which the rate is a function of the substrate concentration and two parameters , the limiting rate, and , the Michaelis constant.
In enzyme kinetics, a secondary plot uses the intercept or slope from several Lineweaver–Burk plots to find additional kinetic constants. [1] [2]For example, when a set of v by [S] curves from an enzyme with a ping–pong mechanism (varying substrate A, fixed substrate B) are plotted in a Lineweaver–Burk plot, a set of parallel lines will be produced.
On a Lineweaver-Burk plot, the presence of a noncompetitive inhibitor is illustrated by a change in the y-intercept, defined as 1/V max. The x-intercept, defined as −1/K M, will remain the same. In competitive inhibition, the inhibitor will bind to an enzyme at the active site, competing with the substrate.
A decade before Michaelis and Menten, Victor Henri found that enzyme reactions could be explained by assuming a binding interaction between the enzyme and the substrate. [11] His work was taken up by Michaelis and Menten, who investigated the kinetics of invertase, an enzyme that catalyzes the hydrolysis of sucrose into glucose and fructose. [12]
The plot is occasionally attributed to Augustinsson [5] and referred to the Woolf–Augustinsson–Hofstee plot [6] [7] [8] or simply the Augustinsson plot. [9] However, although Haldane, Woolf or Eadie were not explicitly cited when Augustinsson introduced the versus / equation, both the work of Haldane [10] and of Eadie [3] are cited at other places of his work and are listed in his ...
where k is the maximal transcription rate of gene X. Likewise, if the production of protein from gene Y is down-regulated (repressed) by a transcription factor Z, then the rate of production of protein Y can be modeled as a differential equation in terms of the concentration of activated Z protein:
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When plotted in the manner described above, the value of the y-intercept (at = / =) will correspond to (), and the slope of the line will be equal to /. The values of y-intercept and slope can be determined from the experimental points using simple linear regression with a spreadsheet .